Pathology Grand Rounds: December 8, 2022

December 08, 2022

Information

Diagnosing Myocarditis - Challenges and Opportunities, by Marc Halushka, MD

ID9255

To CiteDCA Citation Guide

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&amp;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&amp;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.