Featured Publications
Histopathologic and Machine Deep Learning Criteria to Predict Lymphoma Transformation in Bone Marrow Biopsies.
Irshaid L, Bleiberg J, Weinberger E, Garritano J, Shallis RM, Patsenker J, Lindenbaum O, Kluger Y, Katz SG, Xu ML. Histopathologic and Machine Deep Learning Criteria to Predict Lymphoma Transformation in Bone Marrow Biopsies. Archives Of Pathology & Laboratory Medicine 2021, 146: 182-193. PMID: 34086849, DOI: 10.5858/arpa.2020-0510-oa.Peer-Reviewed Original ResearchMeSH KeywordsBiopsyBone MarrowDeep LearningHumansLeukemia, Lymphocytic, Chronic, B-CellLymphoma, FollicularMachine LearningReproducibility of ResultsRetrospective StudiesConceptsLarge cell transformationChronic lymphocytic leukemiaBone marrow biopsyMarrow biopsyFollicular lymphomaIndolent B-cell lymphomaLarge lymphoma cellsClinical disease progressionDiagnosis of FLFinal outcome dataB-cell lymphomaLarge tumor cellsEase of procedureAggressive chemotherapyLow morbidityLymph nodesWorse prognosisWhole slide scansHistologic findingsPatient's probabilityDisease progressionLymphocytic leukemiaLymphoma transformationClinical questionsOutcome data
2021
IRF8 is a Reliable Monoblast Marker for Acute Monocytic Leukemias
Katz SG, Edappallath S, Xu ML. IRF8 is a Reliable Monoblast Marker for Acute Monocytic Leukemias. The American Journal Of Surgical Pathology 2021, 45: 1391-1398. PMID: 34172624, DOI: 10.1097/pas.0000000000001765.Peer-Reviewed Original ResearchConceptsChronic myelomonocytic leukemiaAcute monocytic leukemiaBlast countCore biopsyMyelomonocytic leukemiaBone marrowPredictive valueMonocytic leukemiaBone marrow core biopsiesCases of AMoLMarrow core biopsiesAcute myeloid leukemia subtypesExpression of IRF8Acute myeloid leukemiaTrephine core biopsiesReliable surface markersDendritic cell progenitorsNegative predictive valuePositive predictive valuePotential biomarker candidatesBlast increaseMonocytic blastsUseful immunostainsBlast percentageReactive monocytosis