Pathology Grand Rounds: December 8, 2022

Transcript

• 00:00Everybody or we are very fortunate
• 00:03today to have doctor Haluska here.
• 00:06Doctor Haluska is professor of John
• 00:10Hopkins and current chairman of
• 00:13Society of Cardiovascular Pathology.
• 00:16So I look at his CV,
• 00:17I look at that, my God,
• 00:18it's it's a really good example of
• 00:21academic pathologist can read that he
• 00:24graduated from Big Forest and did his
• 00:27AP and Fellowship at Johns Hopkins.
• 00:30For the diagnostic part,
• 00:31I think a lot of people have joined
• 00:34this diagnostic meeting in the morning,
• 00:36right is internationally well known
• 00:39cardiovascular pathologist not only
• 00:42practice in John Hopkins but also have
• 00:45consulting service from local hospital
• 00:47and also as far as from Texas, Texas.
• 00:51So as the investigator,
• 00:54he published 220 publications including
• 01:00reviews and Case report
• 01:02and he is an internationally well
• 01:05known investigator for my micro RNA,
• 01:08especially related to cardiovascular disease.
• 01:13His current research are supported by two
• 01:17R1SP I and three Co investigator R1 Grant.
• 01:22As at the educator, the the course
• 01:26director for the medical school,
• 01:29cost director for postgraduate,
• 01:32Fellows and resident.
• 01:34Anymore too much.
• 01:38He is the he had the frequently speaker
• 01:42at national and international meetings
• 01:45and organize several sessions in the USAP.
• 01:49And one thing he mentored about 40 trainees.
• 01:54Couple of them already showed
• 01:56their professor John Hopkins now.
• 01:59One thing I think not very classical
• 02:02typical of academic pathologist,
• 02:05he has a full patent and invention
• 02:08and he still have the potential
• 02:11to be building there. Yeah. Thank you.
• 02:16Thank you, Peter. Well,
• 02:17thank you very much for inviting me.
• 02:19Only 1/4 of what Peter
• 02:21said about me was right.
• 02:22I won't tell you which quarter,
• 02:23but not the impressive stuff I'm certain of.
• 02:26It is an absolute pleasure to be here.
• 02:29At Yale, yes.
• 02:33I do not know how to turn the chime off.
• 02:35Do you know? Currently, apparently.
• 02:40OK, I don't wanna disrupt anything.
• 02:46And I'm sure that's the sound of
• 02:47people coming on, which is fine.
• 02:48I I will know sort of.
• 02:50At my wedding we had a video at the
• 02:51end and I saw a guy walking on the
• 02:53video and the last two minutes of the
• 02:55wedding he missed the whole thing,
• 02:56but we we documented that he showed
• 02:59up late and our wedding started on
• 03:02time just like today, which is great.
• 03:06I I don't know if you're gonna find that.
• 03:11It's not going to bother me.
• 03:13Then you can bring up.
• 03:16Yes, Sir, I'm. That's where I am.
• 03:19This, yeah. Adopted. It's not here yet.
• 03:27Nope, doesn't give me
• 03:28that option. That's where
• 03:30I am. Very long time.
• 03:37Recipients.
• 03:49I think now everybody has, everyone has
• 03:52used these extra few minutes to join us.
• 03:54I don't think we'll be hearing
• 03:55the ringing much more.
• 03:56So I want to again thank you so much
• 03:58for inviting me to come to Yale today.
• 04:00It is an absolute pleasure to be here.
• 04:03For those of you who are watching as well,
• 04:05it's nice to see you all remotely.
• 04:07I'm going to be talking about
• 04:10diagnosing myocarditis challenges.
• 04:11And opportunities.
• 04:14Should I get this to move forward?
• 04:16And I should say,
• 04:17for the first time in my life,
• 04:19I actually have a disclosure.
• 04:20I just started consulting for a company.
• 04:22I haven't gotten a dime yet,
• 04:24but I'm awfully excited about the
• 04:26possibility of that happening and I
• 04:27needed to share that with you here.
• 04:29So I have a few objectives.
• 04:31They are to recognize the challenges
• 04:33in making a myocarditis diagnosis,
• 04:35explain why that challenge causes
• 04:37difficulties in the general population,
• 04:39and learn about new directions to
• 04:41improve the myocarditis diagnosis
• 04:43that we are undertaking.
• 04:45And this is what I'm going to
• 04:46try and talk to you.
• 04:46About today,
• 04:47I'll keep coming back to this slide,
• 04:49which is of course I want to give
• 04:51you a little bit of information
• 04:52about what is myocarditis.
• 04:53Then talk about different ways
• 04:55that myocarditis is diagnosed.
• 04:57Spend some time talking about
• 04:58the Dallas criteria,
• 04:59which is what we use in Histology and
• 05:02then our our attempts to revise the
• 05:05Dallas criteria and then diagnosing
• 05:08myocarditis beyond the immune cells.
• 05:10So let's start with a straightforward
• 05:12definition of myocarditis.
• 05:14This is inflammation of the
• 05:15heart with myocyte injury.
• 05:17And we have a couple of Histology
• 05:19slides showing this classic pattern
• 05:20of a inflammatory cell infiltrate.
• 05:22This happens to be a number of
• 05:24lymphocytes and some myocyte injury,
• 05:26both at a lower power and a
• 05:29higher power showing a number
• 05:30of these infiltrating cells.
• 05:32So that's a very straightforward definition.
• 05:34There are a number of causes of myocarditis
• 05:37that some of these are infectious.
• 05:39We have a number of different viruses.
• 05:41That are associated with myocarditis,
• 05:44viral myocarditis and that's
• 05:45something we can test for by PCR
• 05:48sometimes identify what these
• 05:49viruses are and type them a number
• 05:51of parasites can cause myocarditis.
• 05:53I brought up Lyme disease because I
• 05:54am here excited to be in Connecticut
• 05:56to give the talk.
• 05:57So I had to bring that up as a a big one.
• 05:59But Chagas disease is a really big
• 06:02problem in Central and South America
• 06:04as a cause of myocarditis and then
• 06:06we can also rarely see bacterial
• 06:09forms of myocarditis as well.
• 06:10There's also a number of non infectious.
• 06:13Forms of myocarditis,
• 06:14autoimmune diseases such as lupus,
• 06:17treatment related processes such as
• 06:19immune checkpoint and inhibitor myocarditis,
• 06:21something which didn't exist 10
• 06:23or 15 years ago,
• 06:24antipsychotic agents and then
• 06:26even post vaccinations.
• 06:28So there has been some reports which
• 06:30I think percentage of which are real
• 06:32that there are associations with the SARS,
• 06:34Kobe 2 vaccines and some
• 06:36other vaccines that have been
• 06:39reported in the past.
• 06:40There are also many different subtypes
• 06:42of myocarditis and this is again
• 06:44from a Histology point of view.
• 06:46We have what I call our garden
• 06:49variety lymphocytic myocarditis,
• 06:50lots of lymphocytes and myocyte damage.
• 06:53We have giant cell myocarditis,
• 06:55a very specific entity of myocarditis,
• 06:58notable by the presence of these
• 07:00large giant cells in the mix and a
• 07:03very aggressive form of myocarditis.
• 07:05And we can even have eosinophilic
• 07:07myocarditis with numerous eosinophils
• 07:09infiltrating from a variety.
• 07:11Processes one other.
• 07:15Type that gets lamped,
• 07:17lumped in with the other
• 07:18myocarditis forms is sarcoidosis,
• 07:20which is considered a
• 07:21granulomatous myocarditis.
• 07:22Some people might distinguish
• 07:24sarcoid as being a different process
• 07:26because it affects the entire body.
• 07:28A lot of people in the myocarditis
• 07:31world put it in as part of the process.
• 07:34There are a number of clinical
• 07:36features of myocarditis that we see,
• 07:38a big one being chest pain and I
• 07:40stole this picture off the Internet.
• 07:41I just thought it was a good example.
• 07:44New onset heart failure,
• 07:46arrhythmias and conduction disturbances,
• 07:49hemodynamic compromise and
• 07:50unfortunately debt where there's
• 07:52a report of over 40,000 yearly
• 07:54deaths from forms of myocarditis.
• 07:56A lot of that is Chagas disease,
• 07:58sort of chronic processes from that,
• 08:00but it also,
• 08:01we see this as viral myocarditis
• 08:02here in the United States.
• 08:04Which unfortunately takes some
• 08:05number of lives every year.
• 08:09So let's spend a little time talking
• 08:12about how myocarditis is diagnosed
• 08:14and we have biopsy based approaches,
• 08:16imaging based approaches and
• 08:18clinically based approaches as well.
• 08:21And let's start with the
• 08:23endomyocardial biopsy.
• 08:24So endomyocardial biopsies are
• 08:25performed here with the caves bioptome
• 08:27where they take this bioptome,
• 08:29they go through the internal jugular vein,
• 08:32go into the right side of the heart
• 08:34onto the septum and with little
• 08:36pinchers they grab little pieces
• 08:38of myocardium that look like this.
• 08:40They pull it out,
• 08:41they give it to us and we make a diagnosis.
• 08:44Typically we see from three
• 08:45to five pieces of myocardium,
• 08:47these small pieces from which
• 08:48we're asked to make the diagnosis.
• 08:51And then in the setting of myocarditis,
• 08:53we're looking for inflammatory cell
• 08:55infiltrates and myocyte damage.
• 08:57I've highlighted with a CD3A
• 09:00number of lymphocytes and with a
• 09:02C68A number of macrophages here.
• 09:05And we base this diagnosis of
• 09:08myocarditis on the Dallas criteria.
• 09:10Which I'm going to spend some
• 09:12more time talking about in a bit.
• 09:14I think this was a very useful paper
• 09:17that came out for clinicians which
• 09:20was the when to biopsy guidelines
• 09:22from 2007 and it has, I don't know,
• 09:24I think you can see that OK,
• 09:26but I'll I'll talk through it.
• 09:27It's a number of different clinical
• 09:29scenarios which are either good
• 09:31ideas to biopsy or maybe not
• 09:32as good ideas to biopsy for.
• 09:34And I put green arrows next to the
• 09:36scenarios where we're more likely to
• 09:38make the diagnosis of myocarditis and
• 09:39the ones at the top and the ones here
• 09:41as well are new onset heart failure.
• 09:44Of either less than two weeks
• 09:46duration or two weeks to three
• 09:48months duration can be associated
• 09:50with a dilated left ventricle,
• 09:52new ventricular arrhythmias and then
• 09:55here it's basically the same duration
• 09:57with some other symptomatology.
• 10:00So those scenarios are good times to look
• 10:03for myocarditis, new onset myocarditis.
• 10:05In a patient.
• 10:08No evidence was listed as AB or C&A is
• 10:11like your best evidence like randomized
• 10:14control trials with placebos and all that.
• 10:17There aren't any or at least
• 10:18there weren't any of 2007.
• 10:20So then B was other trials
• 10:22and C was experts best guess.
• 10:25And so you can see that even then
• 10:27there was a lot of experts best
• 10:29guess as to when we're good good
• 10:32times to perform biopsies.
• 10:34Another approach that people have is
• 10:36to do this by imaging cardiac MRI.
• 10:39And so they went to Lake Louise,
• 10:41which is a beautiful place up in Canada
• 10:43and came up with the Lake Louise criteria.
• 10:46A few years later,
• 10:47needing an excuse to probably
• 10:48go back to the lake,
• 10:49they came back with revised Lake
• 10:52Louise criteria which were improved
• 10:54over the original criteria and these
• 10:56used T1 and T2 imaging of the heart.
• 10:59So on the left we see a T1 weighted
• 11:02inversion recovery with Lake gadolinium.
• 11:05Enhancement and the orthogonal short
• 11:06axis view and what they're seeing I
• 11:09believe is this pattern here in the wall
• 11:11here this is T2 mapping which highlights
• 11:13fluid and it's showing mid wall edema.
• 11:15So in this black circle you see
• 11:18a little extra fluid that little
• 11:20pale area and in that same area
• 11:22again on T1 weighted inversion
• 11:25recovery Lake gadolinium enhancement
• 11:27shows that same area of edema.
• 11:30So putting these features together a good.
• 11:34I'll just.
• 12:04Sometimes I feel that these criteria
• 12:07get used in scenarios where they
• 12:09may not be as useful a well known.
• 12:12Scenario where this occurred
• 12:13was in the setting of COVID,
• 12:16and so a very influential paper
• 12:17came out in the summer of 2020,
• 12:20just a few months after COVID
• 12:22really became a big thing.
• 12:23This came out of Germany,
• 12:25and it was a study of 100 patients
• 12:27who had just recovered from COVID-19.
• 12:29Cardiac MRI revealed that 78%
• 12:32of them had cardiac involvement,
• 12:34and cardiac MRI suggested that 60%
• 12:36had ongoing myocardial inflammation.
• 12:39So 60% of people who had COVID,
• 12:42they claim now. Had. No.
• 12:46Per diem. I to a lot of us,
• 12:50I remember calling my cardiology colleagues,
• 12:52I said, are you seeing 6 of 10 patients
• 12:54who had COVID having myocarditis?
• 12:55And they said, no, we're not,
• 12:56we're not seeing this at all.
• 12:58I, I and others became very upset.
• 13:00I reached out to circulation and said
• 13:02we got to write something about this.
• 13:04And I got a note back saying,
• 13:06yeah, you can write something,
• 13:07but you can't do a hit piece
• 13:09or takedown of that article.
• 13:10So we, we kind of talked around it,
• 13:12but other people went after
• 13:14this specifically.
• 13:15And one of the problems was
• 13:17when this paper came out.
• 13:18In the middle of 2020,
• 13:20we didn't have a lot of data to
• 13:21prove that they weren't right,
• 13:23and again, it just seemed,
• 13:24anecdotally, really excessive.
• 13:28So I was able to work with Rick
• 13:30Vanderheide who was at LSU at the time
• 13:32and we collected all of the autopsy data.
• 13:34We could get all the autopsy
• 13:36series that were coming out with
• 13:39102030 cases from around the world
• 13:41and say what's the incidence
• 13:43of myocarditis and these cases.
• 13:45So these are people who died of COVID,
• 13:46so severe COVID,
• 13:48how much myocarditis are we seeing?
• 13:51And the answer was that we felt the
• 13:53true prevalence of myocarditis based on
• 13:55these autopsy series was much lower,
• 13:57probably less.
• 13:58And 2%,
• 13:58which seems to be more reasonable relative
• 14:01to data that has come since that time.
• 14:04Now we noticed a couple other things
• 14:05when we were doing this project.
• 14:07One is that people were using those
• 14:09Dallas criteria that I mentioned before,
• 14:11something we use for endomyocardial
• 14:13biopsy to make the diagnosis on X or
• 14:17deceased people's hearts, autopsy hearts.
• 14:19And it's not designed for that.
• 14:21It's designed specifically for biopsy.
• 14:23So that was inappropriate.
• 14:25Secondly,
• 14:25in a lot of series,
• 14:26people were suggesting they had seen.
• 14:30Myocarditis and showed a picture of
• 14:32what they described as myocarditis.
• 14:34But you look at that picture and
• 14:36say that's really not myocarditis
• 14:37and there's some,
• 14:38maybe a few more immune cells than expected,
• 14:40but we're not seeing the right
• 14:42features for myocarditis.
• 14:43And if you're showing me a picture,
• 14:44I would think you'd be taking the
• 14:46most obvious part of the myocarditis.
• 14:48So it LED us to believe that
• 14:50even in this scenario,
• 14:51some people were misusing
• 14:53the tools that we have to
• 14:55make the diagnosis of myocarditis.
• 14:57So that is a challenge.
• 15:00Some people have to make the
• 15:02diagnosis of myocarditis purely
• 15:04based on clinical features.
• 15:05No access to cardiac MRI,
• 15:07no access to endomyocardial biopsy.
• 15:10And these features include chest
• 15:12pain like I talked about earlier,
• 15:13St segment elevation on an EKG,
• 15:17elevations of erythrocyte
• 15:18sedimentation rate or CRP,
• 15:20high sensitivity troponin or
• 15:23elevated CKMB NT Pro BNP elevations
• 15:27and cardiac autoantibodies.
• 15:29However,
• 15:30all of these are nonspecific findings.
• 15:33So you can see all of these in other
• 15:36cardiovascular related diseases.
• 15:37Chest pain you obviously can
• 15:39see a myocardial infarction.
• 15:41Have that in aortic dissection.
• 15:43People even complain of
• 15:44chest pain who have GERD,
• 15:46so not the most specific thing.
• 15:48And all the other features can be
• 15:50seen in other either myocardial
• 15:52infarctions or heart failure.
• 15:55So we all got excited last year
• 15:57when a paper came out describing
• 15:59a new blood based biomarker which
• 16:01was initially called HSA Mirror
• 16:04chromosome 896 and I want to
• 16:06spend a moment talking about this.
• 16:07So this came out in the New England
• 16:10Journal of Medicine in May of 2021.
• 16:13And it was.
• 16:16Called the novel circulating micro RNA
• 16:18for the detection of acute myocarditis.
• 16:21Within just a couple of days
• 16:22of this paper coming out,
• 16:23I've gotten multiple emails from
• 16:24colleagues from all over the place.
• 16:25Hey, Mark, have you seen this paper?
• 16:27And the reason they asked is because,
• 16:29well, I'm a cardiovascular
• 16:30pathologist and I do micro RNA's.
• 16:32And so that's clearly in my wheelhouse
• 16:34of things that I would be interested in.
• 16:36And I was like, yeah, thank you.
• 16:37I did see it and I'm reading it right now.
• 16:41And So what they did was they started
• 16:43with a mouse and it's known that
• 16:45TH 17 cells and a type of immune
• 16:48cell is increased in myocarditis.
• 16:50And they found a micro RNA called
• 16:53mere 721 and micronas are just
• 16:56numbered short RNA's 21 bases or so.
• 16:59And I could go into much more detail,
• 17:00but I'll try and keep it simple.
• 17:02They found that this mere 721 in
• 17:05mice was elevated in myocarditis as
• 17:07seen here and it was not elevated
• 17:11in mycardial infarctions.
• 17:12That was pretty exciting.
• 17:13They then said, well,
• 17:14what's the human correlate of that micro RNA?
• 17:18And they found a sequence on
• 17:19chromosome 8 which they felt matched.
• 17:21And then they showed across multiple
• 17:24other cohorts that this micro RNA in
• 17:28humans was elevated in myocarditis.
• 17:30You can see that even normals had some
• 17:33expression of this mere chromosome 896,
• 17:36but again, it was elevated in myocarditis.
• 17:39So this paper came out.
• 17:40I think I got excited.
• 17:42I had already.
• 17:43Published a paper saying use of
• 17:45micrornas as cardiovascular biomarkers
• 17:46and we specifically said this is an
• 17:49area where they might be useful where
• 17:51some other places they wouldn't be.
• 17:53And at the time I was studying
• 17:55micro RNA expression in the lab,
• 17:57we had huge datasets of cellular
• 18:00microrna expression from sequencing.
• 18:01And I reached out to my postdoc a room
• 18:04and I said Arun, let's find this sequence,
• 18:07let's see where it's expressed.
• 18:09Just TH 17 cells or is it found
• 18:11in other cells like let's?
• 18:13Let's solve this.
• 18:13So I sent them scurrying away.
• 18:15He comes back a little later
• 18:17that day and says Mark.
• 18:18I don't see it.
• 18:19I can't find it in any of our data.
• 18:21I said whoa, whoa, whoa, this is weird.
• 18:24Let me go look further at this paper.
• 18:26So it turned out there's some
• 18:28real problems with this paper,
• 18:31which essentially is that
• 18:33this sequence doesn't exist.
• 18:35There was no micro RNA.
• 18:36There's no HSA chromosome 896.
• 18:40A couple things to point out
• 18:42here on the left.
• 18:43This is a normal micro RNA
• 18:46structure that you see this.
• 18:48It has a hairpin loop of
• 18:50roughly this dimension.
• 18:51This is the classic HSA Mirror 1/26
• 18:54and abundant well described micro RNA
• 18:57which they described in the paper as well.
• 18:59This is the mouse mirror 721 and this
• 19:03is human chromosome chromosome 896,
• 19:05which should make a hairpin loop
• 19:08but has this crazy structure.
• 19:10So that's not going to be part
• 19:12of the micro
• 19:12RNA machinery to process this.
• 19:14That was one thing that was weird.
• 19:16The second is that mirror.
• 19:19721 is located in the mouse in the
• 19:22locus of a gene called Cux one.
• 19:24Usually when a micro RNA is in
• 19:26a gene and intragenic region,
• 19:28it stays in that same regions,
• 19:30particularly over a short time period
• 19:33such as between mice and human and the
• 19:36sequence that they identified was on
• 19:38chromosome 8 and may of corresponded
• 19:40with a long non coding RNA in mice.
• 19:43It was definitely found in the
• 19:45area of a long coding RNA.
• 19:48Inhuman additionally, and most critically,
• 19:51is a micro RNA has an area
• 19:53called a seed sequence,
• 19:55and this six base or seven base nucleotide
• 19:58sequence at the end is completely invariant.
• 20:01It's the critical piece for binding of that
• 20:04micro RNA to its targets on Messenger RNAs,
• 20:06and they propose that two of the
• 20:09six nucleotides had changed.
• 20:10And the analogy that I have for
• 20:12that is suddenly being able to
• 20:14use your car key to open your
• 20:16house through the key rather than.
• 20:18Of your house key.
• 20:19It's a massive change in identification and
• 20:22everything would have to move in tandem.
• 20:25You'd have to switch out all the
• 20:27locks in your house at the same
• 20:29time to match your car key,
• 20:30and we don't have any evidence of that.
• 20:32So there's a lot of concerns in
• 20:35addition to not finding any reads.
• 20:37And when we reached out to a colleague
• 20:39who had even more data than we had,
• 20:40it wasn't present in 230 billion reads.
• 20:43I then additionally I called the
• 20:45holistica X Prize on Twitter.
• 20:46I said if anyone can find the sequence
• 20:47let me know, I'll pay you money.
• 20:49And I had a student from somewhere up
• 20:52in this area who found 200 base pair
• 20:55sequence reads and thyroid tissue,
• 20:57again suggesting either this was DNA
• 20:59contamination in the RNA sequencing data
• 21:01set or it's part of a larger sequence,
• 21:04but again not a short RNA.
• 21:06And the reason I'm going on and
• 21:08on and on about this is because
• 21:09we put all this together.
• 21:11We let the Newland Journal
• 21:12of Medicine know 8 days.
• 21:13After the paper came out that they
• 21:16were very serious concerns about
• 21:18this thing which was proposed as
• 21:21a biomarker and Long story short,
• 21:23it wasn't put out there to the
• 21:26public until September of this year.
• 21:28It was of to me embarrassing,
• 21:31but they refused to move on.
• 21:33This major concern and our major
• 21:35concern was please don't let anybody
• 21:38study this micro RNA biomarker
• 21:40because it's not a micro RNA,
• 21:42it's possible and I'm not a purist.
• 21:44That any small RNA sequence that can
• 21:47serve as a biomarker is a biomarker.
• 21:50If we're in green shoes is a good biomarker.
• 21:53Then let's look at people's shoes.
• 21:55I'm fine with that.
• 21:56But there was no connection between the two.
• 21:58So they had about a A1 and 2.5
• 22:00billion chance,
• 22:01assuming the number of RNA that
• 22:03you'd see that they
• 22:04were right. So a big concern,
• 22:07I met with Carlos last night
• 22:10and he also agreed with me.
• 22:11So I felt very vindicated about all of that.
• 22:15OK. So I want to move on and say
• 22:16basically that we got excited about a
• 22:18biomarker and we don't have a biomarker.
• 22:20So let's turn our attention
• 22:23back to the Dallas criteria.
• 22:26The Dallas criteria came about circa 1985.
• 22:30And the reason for this was at that time
• 22:32they were trying to do clinical trials
• 22:34of steroids to see if immunosuppression
• 22:36would be useful for myocarditis.
• 22:38And the problem was that pathologists
• 22:40didn't have the same criteria
• 22:42at different institutions.
• 22:44People had different things going on,
• 22:46and so they brought everybody
• 22:47together in Dallas.
• 22:48They got a bunch of microscopes.
• 22:50And lots of glass slides of myocarditis
• 22:52and they sat down and hammered out some
• 22:55criteria which were published here in 1986.
• 22:57And they basically had these three levels.
• 23:00They had the definition of myocarditis,
• 23:03which is myocardial necrosis
• 23:04degeneration or both in the absence
• 23:07of significant coronary artery
• 23:09disease with adjacent inflammatory
• 23:10infiltrate with or without fibrosis,
• 23:13borderline myocarditis,
• 23:14which was this intermediate think
• 23:16of dysplasia as a correlate.
• 23:18So it's not normal, but it's not.
• 23:20Myocarditis,
• 23:20so we'll just call it borderline
• 23:23myocarditis and no myocarditis,
• 23:25no evidence of inflammation and
• 23:27the borderline, somewhat unclear.
• 23:29It's inflammatory infiltrate too
• 23:31sparse or mysite damage not apparent.
• 23:34So we don't know what's too few
• 23:36cells to call it borderline,
• 23:38what's too many cells to call it borderline,
• 23:40it's just kind of nebulous space.
• 23:43Again, this is published in 1986.
• 23:45And if you perform subsequent biopsies,
• 23:47which we tend not to do anymore,
• 23:49you could diagnose it as ongoing.
• 23:51Resolved for resolving,
• 23:52so I skipped one in the middle.
• 23:57In 2013, a second set of criteria came about.
• 24:01Where the key changes were now to
• 24:04introduce immunohistochemistry 1986,
• 24:06we weren't really doing
• 24:08immunohistochemistry frequently and
• 24:09certainly not on endomyocardial biopsy.
• 24:12So here a European group,
• 24:13the European Society of Cardiology.
• 24:18Made essentially 2 changes to the criteria.
• 24:20One was again to implement
• 24:23immunohistochemistry,
• 24:23looking for CD3 lymphocytes,
• 24:25and to define 14 leukocytes per
• 24:28millimeter squared as definitive
• 24:31diagnosis of myocarditis. OK.
• 24:33So that's the setting of what we have.
• 24:35We kind of have an old criteria that
• 24:37I thought everybody used and a new
• 24:39criteria that maybe some people use.
• 24:41Cause I actually wasn't using that.
• 24:43And we decided between the Society
• 24:45for Cardiovascular Pathology,
• 24:46SBP and the European Society,
• 24:49we should study this.
• 24:50We should find out what
• 24:52people are using as criteria.
• 24:54So this is now the work of Monica de
• 24:57Gaspari and Chi Lin and I worked with
• 24:59them where we developed a survey to ask
• 25:02people about how they diagnose myocarditis.
• 25:04We then sent emails out to
• 25:06members of both of our societies.
• 25:08We tweeted about it.
• 25:09I sent emails and other people sent directed
• 25:11emails to people to ask them to participate.
• 25:14And we were thrilled to get
• 25:16exactly 100 participants.
• 25:17It's so much easier to do math on 100
• 25:19than 101 or 99, and that was great.
• 25:22So we had 100 pathologists respond.
• 25:24You can see that half of them
• 25:26were from North America, roughly,
• 25:27and half were roughly from Europe.
• 25:30And a wide range of.
• 25:32Of sort of experience with heart
• 25:35biopsies from less than 10 think a
• 25:37reasonable chunk to greater than 200.
• 25:40And I have a colleague in Germany.
• 25:43Who Karen Klingle,
• 25:44who sees thousands of cases every year.
• 25:47She I think is the referral
• 25:48Center for all of Germany.
• 25:50So she has a huge cohort of cases and a lot
• 25:52of experience and she participated as well.
• 25:55So we started to ask this group questions
• 25:56and the first question we asked is,
• 25:58do we all use the same criteria?
• 26:00No,
• 26:01we don't.
• 26:01You can see that half the people
• 26:04use Dallas criteria exclusively,
• 26:0628 used both criteria,
• 26:08the European and Dallas criteria,
• 26:10and 12 claim to use.
• 26:11The European eight people didn't use either,
• 26:14and this was somewhat dependent on
• 26:15where in the world they were located.
• 26:17In North America,
• 26:19people predominantly use
• 26:20just the Dallas criteria,
• 26:22whereas in Europe they seem to
• 26:24mostly use your the ESC and then
• 26:27potentially Dallas criteria as well.
• 26:29So very much depends on.
• 26:31Where they were, we use criteria, no.
• 26:34What about immunohistochemistry
• 26:35and viral PCR studies?
• 26:37Do we use these consistently?
• 26:40No.
• 26:40OK,
• 26:40on the left,
• 26:42you see that half the European
• 26:43groups use IHC in every case,
• 26:45and the other group do it in selected cases.
• 26:48And in the United States,
• 26:50there's a group that do not
• 26:52perform immunohistochemistry
• 26:53on any cases for myocarditis.
• 26:55And I will tell you that my
• 26:57colleagues at the Mayo Clinic,
• 26:59who are some of the best cardiovascular
• 27:00pathologists in the country,
• 27:01don't use immunohistochemistry because
• 27:03it's not part of the Dallas criteria.
• 27:06I'll mention before that sometimes
• 27:08people use viral PCR to type viruses.
• 27:11Some people consider that an
• 27:13important part of the diagnosis,
• 27:14other people do not.
• 27:15In Europe,
• 27:16about half the groups routinely perform it,
• 27:18and North America's only 22%.
• 27:21At my institution, the pediatric team
• 27:23performs it and the adults do not.
• 27:25So even in one institution we have
• 27:28different approaches to doing this.
• 27:31Well, do we use the same terminology to
• 27:33all of us use at least the same terms?
• 27:36Again, no. You can see that giant cell
• 27:39myocarditis was the most commonly used
• 27:41term as like a top line diagnosis,
• 27:44you syphilitic myocarditis,
• 27:46lymphocytic myocarditis and down.
• 27:48But note that borderline myocarditis
• 27:50was used by 55% of the group.
• 27:54So that intermediate diagnosis
• 27:56wasn't even used by everyone.
• 27:58So this might be concerning, I don't know.
• 28:02Our conclusions were that there is
• 28:04not a consistent approach and the way
• 28:06we make the diagnosis of myocarditis,
• 28:09we have different criteria,
• 28:10we have different use of
• 28:12immunohistochemistry,
• 28:13different use of viral PCR and other
• 28:15things which I didn't bring up here, but.
• 28:18But maybe there's good news.
• 28:20What if it doesn't matter how
• 28:22we get to the diagnosis,
• 28:23it's so obvious that we all get to
• 28:25the same diagnosis no matter what.
• 28:28OK, so maybe this is like, you know,
• 28:31trying to thin slice something
• 28:32that doesn't really matter.
• 28:33We're going to anyone doesn't
• 28:34matter what criteria they use are
• 28:36going to see the slide and go,
• 28:37that's myocarditis.
• 28:37We're all going to agree.
• 28:39That's not myocarditis.
• 28:40We're all gonna agree and that
• 28:41would be great.
• 28:42So wouldn't a bunch of experts
• 28:45all agree on what is myocarditis?
• 28:48And so we did that experiment as well.
• 28:50Here I had the pleasure
• 28:53of working with Dan Liu,
• 28:54one of our trainees at Johns
• 28:56Hopkins where he blessed his heart,
• 28:57digitized 100 heart biopsy cases
• 29:00on a slick 6 slide scanner.
• 29:03These are diagnosis of cases that
• 29:05either myself or my colleague Charles
• 29:07Steenbergen had made at Johns Hopkins,
• 29:0931 cases of myocarditis 32 that we had
• 29:12diagnosed as borderline myocarditis,
• 29:1537 cases of non myocarditis.
• 29:18All cases had H&E's, usually four slides,
• 29:22CD3, CD 68 and a Mason,
• 29:24trichrome,
• 29:24that were all scanned and made available.
• 29:27We had a panel of eight international
• 29:29experts who were invited to independently
• 29:32provide a diagnosis on each case.
• 29:34They basically use the system I used
• 29:36this morning with the trainees proscia,
• 29:38just digital slides with a scoring sheet.
• 29:41The cases were all randomized.
• 29:42We told them only that everybody had
• 29:45a diagnosis of rule out myocarditis.
• 29:47Our plan was that they would have a
• 29:49lot of agreement where they didn't
• 29:51have agreement between the groups.
• 29:52We would resolve this maybe by e-mail.
• 29:54So let's say seven of eight
• 29:56agreed that it was myocarditis.
• 29:57One person said borderline would say,
• 29:59hey, everyone else is saying myocarditis.
• 30:01What do you think?
• 30:02If they said OK, we would say that's great.
• 30:05If they say, Nope, I'm sticking to my guns,
• 30:07we say, that's fine,
• 30:08we'll have a shared zoom session
• 30:10and we'll talk about all the cases
• 30:12that we don't have agreement.
• 30:13So 100 cases, it should be great.
• 30:15Nothing could go wrong.
• 30:17Well, it turned out that getting to
• 30:20consensus was really challenging to me.
• 30:23Surprisingly challenging.
• 30:23Although when I told the colleague he's like,
• 30:25why are you thinking this would be easy?
• 30:27I don't know.
• 30:28So this is the initial consensus to the
• 30:31Johns Hopkins signed out original diagnosis.
• 30:34They had full consensus.
• 30:36All eight people agreed on the on
• 30:39the diagnosis of borderline cases.
• 30:41Three 3 * 16 agreed on
• 30:45myocarditis cases 18 all agreed.
• 30:48On non myocarditis cases and I
• 30:49should go back for a moment and
• 30:51say for the non myocarditis cases,
• 30:52I was specifically looking for
• 30:54ones that I had reported as
• 30:56having a little more inflammatory
• 30:57infiltrate than complete baseline.
• 30:59So it made it a little harder.
• 31:02You see, for the three borderline cases,
• 31:04while they all agreed,
• 31:06they didn't agree with me,
• 31:07all these people, those three cases,
• 31:09everyone said this is not myocarditis.
• 31:11So they're basically saying, sorry,
• 31:12Mark, you blew that diagnosis,
• 31:14OK, that's fine.
• 31:15We had moderate diagnosis then on 13,
• 31:18nine and 13 cases where this was at
• 31:21least six of the eight people agreeing.
• 31:24And then we had 28 cases overall
• 31:26where there was low agreement.
• 31:28We had some cases where people said
• 31:30non myocarditis, some people said.
• 31:32Borderline markers and other people said
• 31:35myocarditis all on the same slides.
• 31:37And that was interesting.
• 31:39So we said, OK,
• 31:41we,
• 31:41we worked through this and we had a
• 31:43couple of big zoom sessions where we
• 31:45got people to try and work on this.
• 31:48It didn't get that much better.
• 31:50First,
• 31:50I discovered that two of my experts don't
• 31:53use the intermediate borderline term.
• 31:55So they were refusing to use the
• 31:58term borderline myocarditis.
• 31:59Now at least one of them had an
• 32:01intermediate term that they would use,
• 32:02which was like myocardium
• 32:04with increased inflammation.
• 32:05And I'd say, well,
• 32:06can't you just call that borderline?
• 32:08No,
• 32:08my clinicians like either yes
• 32:10or no for making the diagnosis
• 32:13of myocarditis and they're happy
• 32:15to try to please the clinician.
• 32:18We had 10 cases that were mostly borderline,
• 32:20which we achieved no consensus.
• 32:22We we sat around and talked about
• 32:24them and couldn't get everybody to
• 32:26agree whether it was borderline or
• 32:28myocarditis or borderline or nothing.
• 32:30And we we just dropped those
• 32:32cases and moved on.
• 32:33And then we had one case of borderline Plus,
• 32:36which is not even a real term.
• 32:39We just invented it so we could get
• 32:40to a consensus because everyone agreed
• 32:42to calling this borderline plus.
• 32:43But this is the Histology of that
• 32:45case and you can kind of see why.
• 32:48This was challenging.
• 32:49We had clearly collections of immune cells,
• 32:52way too many,
• 32:53although they are on the surface here
• 32:55we had collections that were inside
• 32:56the tissue of many lymphocytes.
• 32:58Here's a collection by CD3 and
• 33:01another collection of CD3.
• 33:03So clearly lots and lots of cells.
• 33:05Some people wanted to call this
• 33:07myocarditis even without injury
• 33:09and some people just wanted to
• 33:11call this borderline.
• 33:12So all of this.
• 33:13Was a bit of a problem because even
• 33:16my experts don't agree on how to
• 33:19make the diagnosis of myocarditis.
• 33:21So to kind of sum all this up,
• 33:23we really have challenges
• 33:25in the world of myocarditis.
• 33:27Cardiac MRI is good,
• 33:29but is not necessarily robust
• 33:31in all clinical scenarios.
• 33:33There are no specific clinical
• 33:35symptoms or lab findings that
• 33:37are specific for myocarditis.
• 33:39The micronite biomarker that
• 33:40was claimed is not a micro RNA,
• 33:43probably to definitely not a
• 33:44biomarker one in 2.5 billion chance.
• 33:47Not all pathologists use the same
• 33:49criteria to make the diagnosis
• 33:51of myocarditis and even experts
• 33:53don't agree on diagnosing cases,
• 33:55particularly the intermediate grade lesions.
• 33:59But where there are challenges,
• 34:01there are opportunities.
• 34:02So what can we do to improve this?
• 34:06The first thing we want to do is try
• 34:08and get the diagnostic criteria right.
• 34:10Can we improve the Dallas criteria?
• 34:12And the 2nd is to develop better tissue
• 34:15based methods to diagnose myocarditis.
• 34:17So those are going to be the last two parts.
• 34:19Of the talk and the first part is going
• 34:22to be revising the Dallas criteria.
• 34:24So let's talk about some opportunities
• 34:26to improve the Dallas criteria.
• 34:28We can incorporate immunohistochemistry,
• 34:30which is not part of the original.
• 34:33We can better define myocyte injury
• 34:35as very nebulous and the original
• 34:37diagnosis open to interpretation.
• 34:39We can improve thresholds for immune cells.
• 34:42How many cells is it to say
• 34:44this is borderline?
• 34:45How many is it say this is too many to be
• 34:48in some intermediate category or categories?
• 34:50Validate terms and diagnosis to outcome data.
• 34:54I think that's going to be important
• 34:55to show that these are meaningful
• 34:57descriptors that we're using and a separate
• 35:00diagnosis on biopsies from autopsy,
• 35:02explanted hearts.
• 35:03Again,
• 35:03Dallas criteria were designed for biopsies,
• 35:06but people have been using them
• 35:08incorrectly on autopsy hearts
• 35:10or maybe explanted hearts.
• 35:11Can we use terms or develop terms and
• 35:15criteria specifically for those specimens?
• 35:18So one of the things that I like
• 35:20to point out is back in 1986,
• 35:23it was a lot of experts sitting around
• 35:25looking at slides and didn't have a
• 35:27lot of data to base these criteria on.
• 35:29And we have a lot more data now.
• 35:31People have been talking about
• 35:33biopsies and evaluating biopsies
• 35:34and and reporting outcome data.
• 35:36And these are two examples that
• 35:38came out in 2022,
• 35:39which I think are really useful
• 35:41to think about.
• 35:42So this group in Spain had a
• 35:45paper that looked at biopsies.
• 35:47With a composite end event of heart
• 35:50transplant left ventricular assist
• 35:52device or death and so those are
• 35:54the two things panels on the left
• 35:57side here and this dark purple area.
• 35:59Those are individuals who are Dallas
• 36:02criteria positive and the blue is
• 36:05Dallas criteria negative and that
• 36:07added up to the 23% or so here.
• 36:09This is Dallas criteria negative or
• 36:12and or sorry Dallas positive and
• 36:16or immunohistochemistry positive.
• 36:18Suggesting that immune cells more
• 36:20immune cells than what sort
• 36:22of tolerated as myocarditis and Dallas
• 36:24are meaningful to that bad outcome.
• 36:27So you don't have to necessarily
• 36:29see myocarditis with injury to get
• 36:31to a biopsy where that patient
• 36:33is going to have that outcome.
• 36:35I think that same data is supported
• 36:37here from a paper out of Japan and
• 36:39Cirque Journal where they looked
• 36:41at people who had what they called
• 36:44inflammatory dilated cardiomyopathy,
• 36:45meaning they saw too many immune cells
• 36:46in the setting of dilated cardiomyopathy.
• 36:49Which is probably very similar or the
• 36:51same thing as borderline myocarditis.
• 36:53And where they had more CD3 positive cells,
• 36:56those patients had worse outcomes,
• 36:58less survival free of cardiac death or
• 37:01left ventricular cyst device implantation.
• 37:04Where they saw fewer cells,
• 37:05those patients did better.
• 37:07Now note, it did take about 9 years to
• 37:10see like these really big differences.
• 37:12That's just a pretty long prediction
• 37:14in advance,
• 37:15but it does tell us that more
• 37:17immune cells are worse.
• 37:19And fewer.
• 37:19So it's something we should be
• 37:21cognizant of when we make new criteria,
• 37:23not look to lump everything together.
• 37:26So we decided to go after this and these
• 37:30are the goals that we set up for ourselves,
• 37:34very similar to what the opportunities
• 37:36were to develop revised biopsy criteria
• 37:38for a better definition of myocyte injury,
• 37:40better incorporation of immunohistochemistry,
• 37:42better classification based on the extent
• 37:46of injury and better classification
• 37:48based on types of myocarditis.
• 37:50So that's what we're doing on
• 37:52the biopsy side.
• 37:53On the autopsy or explant side,
• 37:55it's to define.
• 37:56Carditis based on evaluation of the
• 37:58whole heart and to synergize this
• 38:01terminology with the biopsy criteria
• 38:03and ultimately it's to validate all of
• 38:05these criteria with historical samples.
• 38:09And so the timeline that we've been
• 38:11working on is here in March of 2023,
• 38:14we met at the use CAP meeting and
• 38:16developed consensus that we wanted to go
• 38:19forward with revising the Dallas criteria.
• 38:21The SVP and the European Society both
• 38:23agreed that we should go forward with this.
• 38:26We then created 210 person teams to
• 38:29work on generating these new criteria.
• 38:32It started with the literature review.
• 38:34I showed you a couple of examples,
• 38:35but we grabbed hunt, not hundreds,
• 38:38that's too many, but.
• 38:39Scores and scores of papers that
• 38:41we then read,
• 38:42evaluated and sort of discussed
• 38:44amongst ourselves.
• 38:45We then did an adelphic question
• 38:47and answer where we took like the
• 38:49key questions related to biopsy,
• 38:51sent them out to everybody in the group
• 38:53and got everyone's anonymous feedback.
• 38:55And then saw what sort of where people
• 38:59were based on their own beliefs
• 39:01and experiences and ask people to
• 39:03find the data that supported it.
• 39:05Because if this is not data-driven,
• 39:07it's probably not worth doing in my opinion.
• 39:10Our goal is to have preliminary criteria
• 39:13for both of these by March of 2023.
• 39:15And on the biopsy side,
• 39:16we've already split into three or
• 39:18four groups to work on criteria
• 39:20ideas independently which we're going
• 39:22to bring together and have by the
• 39:25use CAP meeting and then spend a
• 39:27year evaluating this.
• 39:28We want to kick the tires on these criteria.
• 39:30We're going to go back to historical data,
• 39:33Johns Hopkins Place where
• 39:34we have historically done a
• 39:35lot of MRI cardiac biopsies.
• 39:37I mentioned Karen Klingle and Germany
• 39:39having so many cases you wouldn't believe.
• 39:42And seeing if the criteria that we've
• 39:44generated with have meaningful outcome or
• 39:47usefulness relative to where we are now.
• 39:49And some of the things that we've been
• 39:52playing with are in the Dallas criteria,
• 39:54expanding that borderline myocarditis
• 39:55to maybe a low and a high number
• 39:58of immune cells,
• 39:59better defining whether these are diffuse
• 40:01immune cells or clusters of immune cells.
• 40:04But these are all things we need
• 40:05to really evaluate and see how
• 40:07they're going to work for us.
• 40:08And then in March of 2024,
• 40:10again in conjunction with the use.
• 40:12That meeting which is going
• 40:13to be in Baltimore,
• 40:14we're gonna have a one day event
• 40:16to hopefully introduce the criteria
• 40:18to the larger world and take last
• 40:20feedback on them from a wider
• 40:22audience as whether these are useful.
• 40:24So all this is to say,
• 40:26we've been using the Dallas criteria
• 40:28for far too long and we are finally
• 40:30getting around to optimizing and
• 40:32improving them and we're very
• 40:33excited about this,
• 40:34what we hope is a good change
• 40:37for myocarditis. Now.
• 40:40That's one thing that we're doing.
• 40:42The next last thing I want to talk
• 40:45about is diagnosing myocarditis
• 40:47beyond immune cells.
• 40:49And what I really haven't mentioned
• 40:51so far is that myocarditis is
• 40:53a heterogeneous disease.
• 40:54And so when sometimes when that
• 40:56endomyocardial biopsy plucks
• 40:57those little bits of tissue from
• 40:59the side of the septum,
• 41:01it might miss that infiltrate.
• 41:03So The Dirty little secret in biopsying
• 41:05is we're only good at finding myocarditis
• 41:08about 50% of the time when it's there.
• 41:10And this is based on a study where they
• 41:12took autopsy hearts that had myocarditis,
• 41:15took a case bioptome and pulled little
• 41:17pieces off the septum and saw how frequently.
• 41:19They can make the diagnosis and
• 41:21actually the more pieces the better.
• 41:235 being better than three.
• 41:25My institution,
• 41:26they give me 3.
• 41:27So maybe we're only 30% good at
• 41:29finding myocarditis.
• 41:30So it is a problem because we can miss it.
• 41:33We could be just next to it and miss
• 41:35it or what we're calling borderline
• 41:38myocarditis could be really close to injury,
• 41:41but always here a few cells,
• 41:43but also for borderline.
• 41:44And I didn't say this before,
• 41:46anybody of my age or older is going
• 41:49to have a collection of lymphocytes.
• 41:51Somewhere in their heart.
• 41:52If you take enough samples of
• 41:53someone's heart over 50,
• 41:55you're going to see a collection.
• 41:56Is that meaningful?
• 41:57Probably not.
• 41:58So it's either a random collection that
• 42:00you bump into by accident on biopsy,
• 42:02or is the tip of the iceberg and
• 42:05you're just missing something nearby.
• 42:08So what we've started to think about is,
• 42:10let's say this is a biopsy that
• 42:12was performed this
• 42:13number one, and that star represents an
• 42:16area of inflammation and myocyte injury.
• 42:19If you biopsy that by Histology,
• 42:21you're going to be able
• 42:22to make the diagnosis.
• 42:23But we also suspect that the cells,
• 42:25the native cells in the heart
• 42:27are probably responding to that
• 42:29immune infiltrate and injury.
• 42:31The myocytes themselves,
• 42:32the endothelial cells,
• 42:34the native fibroblasts,
• 42:35they may be sensing this damage in this
• 42:38process and changing their signaling state.
• 42:41And the question is can we identify
• 42:43what that is and can we capture
• 42:45that information so if we instead
• 42:47of biopsying this piece of tissue?
• 42:50I'm biopsying this piece of tissue,
• 42:52but whatever this process is,
• 42:53is sending out a signal
• 42:55really wide out to here.
• 42:57Maybe I can still sense that signal
• 43:00adjacent that's going to increase
• 43:02our yield on endomyocardial biopsy.
• 43:04Now this won't be necessary for cases
• 43:06where very obvious myocarditis could be
• 43:08rendered even if my experts don't agree,
• 43:10but can get close.
• 43:12It will be useful in scenarios
• 43:13where there is a borderline type
• 43:15of diagnosis where we see some
• 43:17inflammation but don't see enough to
• 43:19make the diagnosis of myocarditis.
• 43:21Or in certain clinical scenarios where
• 43:23the suspicion is very high and again,
• 43:26we might have just missed that material.
• 43:29Now this has probably been a long
• 43:32standing dream for a for years and
• 43:34it's known that cardiac myocytes
• 43:36respond to inflammation and induce
• 43:39their own cytokines to cardiac injury.
• 43:41As you can see in this nice
• 43:43review from some years ago.
• 43:44And this is a paper from 2004 showing
• 43:47that tissue necrosis factor alpha or TNF
• 43:50alpha is increased in cardiac myocytes.
• 43:53So you can see that here and
• 43:55that's sort of a sign that these
• 43:57cells are changing their immune.
• 43:59Response.
• 44:00However, historically,
• 44:00if we wanted to look for differences
• 44:04between disease and normal tissues,
• 44:06we get the tissues,
• 44:07we grind it up,
• 44:08we look for gene expression differences,
• 44:10very straightforward.
• 44:11But if you have a lot of immune
• 44:13cells infiltrating in,
• 44:15that big immune signal you're going
• 44:16to see is really mostly coming from
• 44:19those immune cells and you're going to
• 44:21be missing the more subtle potentially
• 44:23signals that are coming from myocytes,
• 44:26fibroblasts,
• 44:26endothelial cells relative.
• 44:28So that's always been a challenge
• 44:30we can't really assign.
• 44:32Those signals to this the
• 44:34cells we want to look at.
• 44:36So that's where spatial transcriptomics
• 44:38can potentially help us out.
• 44:40OK.
• 44:40So we have started to do some
• 44:42work in collaboration with
• 44:44Luigi Adamo and Kevin Partilla.
• 44:47And we're using a method called
• 44:4910X Vizio and what it does is you
• 44:51can see in this top left corner.
• 44:54This is a glass slide and you can
• 44:56put 4 slices of tissue on the slide,
• 44:58which is shown actually here.
• 44:59These are endomyocardial biopsies.
• 45:02And across those squares,
• 45:04there's like a barcode address
• 45:06for each 55 Micron core or space.
• 45:09And then the tissue that's put
• 45:11up on top of that,
• 45:12we identify what the RNAs are.
• 45:15They're,
• 45:15they're tagged with that
• 45:17barcode of where that's located
• 45:18and then they're sequenced.
• 45:20And so we know what the expression
• 45:22is in each one of those regions
• 45:24all the way across. The tissue.
• 45:26And so that's this particular
• 45:27type of spatial transcriptomics
• 45:29or other approaches as well.
• 45:31And I'm gonna stop for a second and
• 45:33get on my soapbox and say something.
• 45:36We as pathologists have got
• 45:37to get engaged in this concept
• 45:39of spatial transcriptomics.
• 45:41I am a member of the Human
• 45:43Cell Atlas and Hub map,
• 45:44which are two big NIH and other studies
• 45:47to identify where every cell is
• 45:48located in the human body and discover
• 45:50all the cell types and there are
• 45:52not enough pathologists in the room.
• 45:55These are brilliant bioinformaticians.
• 45:57They do great science.
• 45:58But a lot of them don't know 110th of what
• 46:02you guys intuitively know about tissue.
• 46:04And it would benefit all of them if we as
• 46:07a society or a group get more engaged,
• 46:09particularly now that they're starting
• 46:11to move to spatial transcriptomics
• 46:13and really need our help.
• 46:14Kevin, get off my soapbox now.
• 46:16But I had to say that I feel
• 46:18very passionate about that.
• 46:19I sometimes go to these meetings and
• 46:20I'm the only pathologist in the room,
• 46:22and I I often shake my head.
• 46:24OK, so but. Back to this.
• 46:25So we decided to use this approach
• 46:28now spatial this method,
• 46:29these core sizes are 55 microns,
• 46:33which is not the size of a cell.
• 46:34They're bigger than a normal small cell,
• 46:37but a cardiac myocyte is a big cell.
• 46:39So the match is pretty close to 1:00 to 1:00.
• 46:42So we feel good about that.
• 46:45You can see here though,
• 46:46these are endomyocardial biopsies
• 46:47after we've already used them
• 46:49for clinical purposes.
• 46:50So the amount of tissue left wasn't great,
• 46:52but for these are myocarditis.
• 46:55For these are non myocarditis.
• 46:58We we did this with a core facility
• 47:00at Hopkins. We generated some data.
• 47:01The first thing I always like to
• 47:03do with data is kick the tires,
• 47:04make sure that it seems reasonable and
• 47:06it actually did. I was pretty happy.
• 47:09These are two macrophage markers,
• 47:13CD74TSB4X and you can see
• 47:14where one was high in a core,
• 47:16the other was high in a core.
• 47:17Each one of these dots represents
• 47:19a core from across these tissues.
• 47:21These are two markers of
• 47:24cardiac myocytes tropomyosin 1,
• 47:25myosin light chain two.
• 47:27Again there was.
• 47:28Very strong correlation
• 47:29collagens for fibroblasts and
• 47:31hemoglobins for red blood cells.
• 47:33So this method actually worked
• 47:35reasonably well at identifying
• 47:37what was present at each of
• 47:39those cells and if we did a UMAP,
• 47:41which is a way of sort of
• 47:44structuring the data in.
• 47:45Kind of from A3 dimensional
• 47:47where everything is located down
• 47:48to two-dimensional structure.
• 47:50You can see that this separated
• 47:52the myocarditis cases from
• 47:54the non myocarditis cases.
• 47:56So the signal, the,
• 47:57the question we were asking though is
• 47:59can we see interesting signals at a
• 48:01distance from the inflammatory cells?
• 48:03Can we pick up something that the
• 48:05myocytes next door are screaming,
• 48:06hey, hey,
• 48:07I'm seeing there's this
• 48:09inflammation going on over here.
• 48:10And so this is just a little bit of data.
• 48:13My buddy Luigi thinks he's going
• 48:15to make a company make millions.
• 48:16I don't think so.
• 48:17But I told him I wouldn't tell him what
• 48:19a gene name was and so he was happy.
• 48:21So this is an example of
• 48:24of what we're seeing.
• 48:26This is a collection of immune cells
• 48:28right here on the edge of a biopsy.
• 48:30And you'll note there's not
• 48:31a blue or Gray signal here.
• 48:33What we've done is we've removed any
• 48:36location that had CD 45 positivity or PT PRC.
• 48:41CD 45 is a pan immune cell marker.
• 48:43So we said let's ignore anywhere
• 48:45where there's an immune cell.
• 48:48Then let's see what is present
• 48:50in myocarditis samples.
• 48:53In nonimmune.
• 48:55Help.
• 48:57Whole of one of the genes that was
• 49:00identified where each one of these
• 49:02blue dots has a signal from that gene.
• 49:05And every Gray area is a place
• 49:07where it doesn't and you can see
• 49:09across this myocarditis biopsy
• 49:10we have lots and lots of these
• 49:13blue signals versus here on this
• 49:15non myocarditis case we have
• 49:17almost no CD 45 positivity.
• 49:20We immune cells are rare in normal
• 49:23heart although they are present and
• 49:25just an occasional spot of this blue.
• 49:28So that to me is is pretty optimistic
• 49:30that we are seeing signals coming from
• 49:32non immune cells that could be doing
• 49:35exactly what we're hoping for signaling.
• 49:37That inflammation is nearby.
• 49:40This is a a more recently I was able to
• 49:42look at a case of a chronic myocarditis,
• 49:44lots of immune cells but without
• 49:47myocyte inflammation from a
• 49:48a larger chunk of tissue.
• 49:50And here again this is CD45 which
• 49:53are these cells right here.
• 49:55The adipocytes in this location
• 49:57are this stream right along
• 50:00the side and so where you see.
• 50:02There are are.
• 50:09The first was that there was
• 50:11actually like a negative biomarker.
• 50:16Have reasonable expression
• 50:18levels of this marker.
• 50:19And then as we got closer to the immune
• 50:22infiltrate, which was over here,
• 50:23we started to see less of that biomarker
• 50:26and we also had positive biomarkers.
• 50:28So again, CD45 represents
• 50:30all the immune cells.
• 50:32If we go beyond that, you start to
• 50:34seeing there's more signal there.
• 50:36So we are somewhat optimistic we
• 50:38might be able to find something that
• 50:41will extend out from areas of injury
• 50:43and that can identify myocarditis.
• 50:45And I'll add that we're not
• 50:46the only people doing this,
• 50:47I've already heard.
• 50:48Of lots of other groups have had this idea.
• 50:50I don't think we're that clever.
• 50:55But as I said before,
• 50:56the goals are to identify biomarkers
• 50:58or a biomarker that can be used to
• 51:01diagnose myocarditis in the absence
• 51:02of inflammation or myocyte injury
• 51:04in the right clinical setting.
• 51:06And ultimately the goal is to
• 51:09increase the yield on our biopsies.
• 51:12So I'm going to end things now and
• 51:15give you a few take home messages.
• 51:17There are challenges as I said,
• 51:19how to diagnose myocarditis
• 51:21in 2022 remains in. Oh.
• 51:25Don't have a great way
• 51:28of making the diagnosis.
• 51:30Biopsying which has historically
• 51:32been called the gold standard
• 51:34is plagued by inconsistencies
• 51:35how we approach the diagnosis,
• 51:38whether we can agree on the diagnosis
• 51:40and whether we can even see the
• 51:42areas we need to make the diagnosis.
• 51:44But there are also opportunities
• 51:45we are going to be working towards
• 51:47improved and new myocarditis criteria
• 51:49for biopsies and whole hearts
• 51:51which should improve the way we
• 51:53approach the biopsies and we think
• 51:56that non immune cell signaling.
• 51:58On biopsy can indicate myocarditis occurring
• 52:01even if we can't see those immune cells.
• 52:05So I want to thank Zen Liu for the work
• 52:07he did when we worked with our experts,
• 52:09Luigi and Kevin on the last part of
• 52:11this with the spatial transcriptomics
• 52:13and then members of our society and
• 52:16the European Society for working
• 52:18to update and create criteria.
• 52:20And I'll end there and I'm happy
• 52:21to take any of your questions.
• 52:32This question. Yeah.
• 52:36Look at.
• 52:43Yeah. So the the question from home,
• 52:46if I make sure I'm getting
• 52:47this right as well,
• 52:47is people looked at CD3 and how that
• 52:51relates to steroid use immunosuppression.
• 52:55So I don't know that I've seen that.
• 52:57I haven't done that,
• 52:59I'll tell you that right now.
• 53:01And I have to look there,
• 53:03that's going to be one of the
• 53:04huge challenges that we're going
• 53:05to face when we try and evaluate
• 53:07these is what are the different
• 53:09treatments that patients have had,
• 53:10because that's going to impact
• 53:12on outcome as well, right.
• 53:14So normally at a time of biopsy early
• 53:16when we're diagnosed as acute myocarditis,
• 53:18they haven't necessarily
• 53:19gone on a treatment yet.
• 53:20So what we see is really more natively
• 53:24what's happening in the heart.
• 53:26So we could see the full
• 53:28gamut of inflammation there,
• 53:29but the question is if different practices
• 53:32and different institutions treat with
• 53:34steroids or don't treat with steroids,
• 53:37how do we figure that out for outcome?
• 53:39And that's a good question as well.
• 53:41And that's going to be very hard to do
• 53:43where we're going to look at different
• 53:45data sets and and figure that out.
• 53:48Second question,
• 53:49yes.
• 53:51That was something against
• 53:54what people think or.
• 53:58Yeah, I, I I don't remember anymore. I.
• 54:16Today.
• 54:21My question is how expanded would be these
• 54:26changes around the areas or permission?
• 54:30Because if it is really expanded
• 54:32then you would have a higher
• 54:35chance of violating for each
• 54:36and every other piece but.
• 54:41Yeah, and you will stop.
• 54:43Basically the same time
• 54:45concept of meeting the area.
• 54:48Yeah, you, you exactly elucidate the
• 54:51the question that we have no idea of,
• 54:54which is how far out will that signal
• 54:57extend relative to the biopsy.
• 54:59And the longer, the further out it goes,
• 55:01the more successful this is going
• 55:03to be and the less it extends out,
• 55:05the less successful it's going to be.
• 55:07And we've only shown we've only done this on.
• 55:105 myocarditis cases for
• 55:12acute and one chronic.
• 55:13We've put in some grants to try and get many,
• 55:16many more cases and find
• 55:18the markers that have the,
• 55:20the sort of the widest capture area.
• 55:22And that's going to be absolutely critical.
• 55:24And if we don't find anything,
• 55:25this obviously won't work.
• 55:27So high risk, high reward,
• 55:29but if we can't extend that out,
• 55:31we're going to be able
• 55:32to make more diagnosis.
• 55:33And I think that's a great thing
• 55:35that we can make that happen.
• 55:39So I just. Questions why is the?
• 55:49So that and we stop typing.
• 55:52Tell.
• 55:55Weather.
• 55:59Yeah, so that's a great question.
• 56:01Do we do subtyping of CD3?
• 56:04We do not. So one of the the I think
• 56:06challenges in the cardiovascular
• 56:08pathology space is that we have not
• 56:12really kept up in our field with.
• 56:14Things like this like subtyping CD3
• 56:16cells I on the research side it may
• 56:19have happened but most people in the
• 56:22cardiovascular space just use CD3 and CD68.
• 56:25In fact this came up last week
• 56:27when Peter had a journal club.
• 56:29When we're talking about C 68 positive
• 56:32cells were being increased seen in
• 56:34COVID and our colleague Jeff Zaffis
• 56:36was arguing that it's it's silly to
• 56:37just look at CD 68 that we have to
• 56:40sub classify macrophages because we
• 56:41know there's so many phenotypes of
• 56:43macrophages that's really meaningful but.
• 56:44They don't have the tool to do that
• 56:46and we just haven't implemented them.
• 56:49So we don't go beyond CD3.
• 56:51Should we?
• 56:52Yes, I mentioned TH 17 cells seem
• 56:54to be important in myocarditis
• 56:56and we are not doing anything
• 56:58clinically to chase that down either.
• 57:05Exactly.
• 57:10And ideas? So only small factory
• 57:13of people would have this.
• 57:21So once you know what possible,
• 57:23you know what you think is
• 57:26underlying, you know, facts.
• 57:29This small. Right, so you know.
• 57:35Out.
• 57:37Got it. Yeah. So the question is why
• 57:39does these small group have Microsoft?
• 57:41I thought you were gonna ask, well,
• 57:42why are so many people have cardiac
• 57:44symptoms without myocarditis,
• 57:45which to me is easier.
• 57:46We're seeing small vessel a thrombi,
• 57:49microthrombi in in people.
• 57:51We're seeing increased macrophages in
• 57:53the hearts of multiple studies of that.
• 57:55But that's not myocarditis,
• 57:57that's just other processes
• 57:59that are affecting the heart.
• 58:01As far as this group,
• 58:03I don't know why this 2% I would argue.
• 58:06Genetics is partly involved.
• 58:08Someone's set up for this, possibly.
• 58:12Sort of an autoimmune process
• 58:14that can get going as well.
• 58:16I have not kept up with the
• 58:18basic science data on this.
• 58:20I'm sure there is a,
• 58:21I'm sure there's hundreds of papers.
• 58:23Whether some of them are good or not,
• 58:24I don't know either.
• 58:26But what we do know from COVID,
• 58:28having looked at lots of
• 58:29cases I'm sure Peter agrees,
• 58:31is we see lots of macrophages,
• 58:33I even see more macrophages and people
• 58:35have heart failure after getting a vaccine,
• 58:37but it's not a classic myocarditis and
• 58:39that's actually something that we're
• 58:41thinking about with the Dallas criteria.
• 58:43Is do we?
• 58:44Discussed some of these rare types of
• 58:47myocarditis and be provide criteria
• 58:49that are more specific to them
• 58:52such as if you see this many miles
• 58:55sites and I've seen a ton of Maya
• 58:57sites in a couple of these cases,
• 58:59but that's not typical for myocarditis
• 59:00which is a lymphocytic disease.
• 59:02We've always thought about whether
• 59:03or not that should be sufficient to
• 59:05make the diagnosis of myocarditis.
• 59:07So that's something that we're
• 59:09working through as well.
• 59:12After that.
• 59:17Ohh.
• 59:20We have talked about smoking in
• 59:22the smoking nut in the mice,
• 59:24which they activate phase
• 59:27two and one. So that made.
• 59:34Now.
• 59:38Subpopulation.
• 59:42So that will be.
• 59:46No, only one. Yeah, yeah, yeah.
• 59:54Favorite.
• 01:00:03You heard it here first.
• 01:00:09Yeah. Super fresh. Thank you for sharing.
• 01:00:13Yeah.
• 01:00:16Great. Well, with that, I think
• 01:00:19I'll thank you all for your time.
• 01:00:21It's been wonderful. Thank you.
• 01:00:28There was nothing in the chat.
• 01:00:35There's some studies in the machine learning.
• 01:00:40Reason.