2020
Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group
Amgad M, Stovgaard ES, Balslev E, Thagaard J, Chen W, Dudgeon S, Sharma A, Kerner JK, Denkert C, Yuan Y, AbdulJabbar K, Wienert S, Savas P, Voorwerk L, Beck AH, Madabhushi A, Hartman J, Sebastian MM, Horlings HM, Hudeček J, Ciompi F, Moore DA, Singh R, Roblin E, Balancin ML, Mathieu MC, Lennerz JK, Kirtani P, Chen IC, Braybrooke JP, Pruneri G, Demaria S, Adams S, Schnitt SJ, Lakhani SR, Rojo F, Comerma L, Badve SS, Khojasteh M, Symmans WF, Sotiriou C, Gonzalez-Ericsson P, Pogue-Geile KL, Kim RS, Rimm DL, Viale G, Hewitt SM, Bartlett JMS, Penault-Llorca F, Goel S, Lien HC, Loibl S, Kos Z, Loi S, Hanna MG, Michiels S, Kok M, Nielsen TO, Lazar AJ, Bago-Horvath Z, Kooreman LFS, van der Laak JAWM, Saltz J, Gallas BD, Kurkure U, Barnes M, Salgado R, Cooper LAD. Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group. Npj Breast Cancer 2020, 6: 16. PMID: 32411818, PMCID: PMC7217824, DOI: 10.1038/s41523-020-0154-2.Peer-Reviewed Original ResearchTumor-infiltrating lymphocytesComputer-aided diagnosticsPotential of machineAssessment of algorithmsInternational Immuno-Oncology Biomarker Working GroupHER2-positive breast cancerBiomarker Working GroupComputational workflowPrognostic workflowsVisual guidelinesTIL assessmentInfiltrating lymphocytesBreast cancerPredictive featuresSolid tumorsInter-reader variabilityWorkflowClinical validationComputational assessmentRipe opportunityComputational methodsReporting guidelinesLymphocytesVisual scoringClinical translation
2018
Utility of CD8 score by automated quantitative image analysis in head and neck squamous cell carcinoma
Hartman DJ, Ahmad F, Ferris R, Rimm D, Pantanowitz L. Utility of CD8 score by automated quantitative image analysis in head and neck squamous cell carcinoma. Oral Oncology 2018, 86: 278-287. PMID: 30409313, PMCID: PMC6260977, DOI: 10.1016/j.oraloncology.2018.10.005.Peer-Reviewed Original ResearchConceptsCD8 T cellsImmune cell densityOropharyngeal HNSCCT cellsNeck squamous cell carcinomaCD8 cell densityImmune cell infiltratesSquamous cell carcinomaWhole tissue sectionsEntire tumor sectionHPV infectionMedian survivalCell infiltrateHNSCC patientsCell carcinomaHNSCC casesClinicopathologic parametersOnly predictorTumor sectionsBetter outcomesClinical practiceTumor microenvironmentCell densityClinical validationCells/An international multicenter study to evaluate reproducibility of automated scoring for assessment of Ki67 in breast cancer
Rimm DL, Leung SCY, McShane LM, Bai Y, Bane AL, Bartlett JMS, Bayani J, Chang MC, Dean M, Denkert C, Enwere EK, Galderisi C, Gholap A, Hugh JC, Jadhav A, Kornaga EN, Laurinavicius A, Levenson R, Lima J, Miller K, Pantanowitz L, Piper T, Ruan J, Srinivasan M, Virk S, Wu Y, Yang H, Hayes DF, Nielsen TO, Dowsett M. An international multicenter study to evaluate reproducibility of automated scoring for assessment of Ki67 in breast cancer. Modern Pathology 2018, 32: 59-69. PMID: 30143750, DOI: 10.1038/s41379-018-0109-4.Peer-Reviewed Original ResearchConceptsIntraclass correlation coefficientBreast cancerBreast Cancer Working GroupAssessment of Ki67Pre-specified analysisCancer Working GroupInternational multicenter studyMulticenter studySubsequent clinical validationInternational Ki67Biopsy sectionsClinical valueBiomarker Ki67Breast tumorsKi67 immunohistochemistryEvaluation of reproducibilityKi67Clinical validationTumor cellsObserved intraclass correlation coefficientScoring methodCorrelation coefficientKi67 scoringMaximum scoreCancer