PO.BCS01.07 · 生物信息与计算

Comparison of digital and artificial intelligence (AI)-computational algorithms for quantifying low/ultralow human epidermal growth factor receptor 2 (HER2) protein expression in metastatic breast cancer (mBC) from clinical samples

海报缩略图:Comparison of digital and artificial intelligence (AI)-computational algorithms for quantifying low/ultralow human epidermal growth factor receptor 2 (HER2) protein expression in metastatic breast cancer (mBC) from clinical samples
编号 1455 展板 18 时间 4/20 09:00–12:00 区域 Section 4 主讲 Savitri Krishnamurthy, MD
分会场 Digital Pathology 2
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作者与单位

Savitri Krishnamurthy1, Dhanrajan Tiruchinapalli2, Clara lam2, Simon M. Collin3, Rosemary Taylor4, Linlin Luo5, Anupriya Dutta5, Ehab A. Elgabry6, Michele S. Woo7, Grace E. Kwon8, Robert Egger9, Jennifer A. Hipp10, Lauren Brunner9, Jeppe S. Thagaard11, Thomas W. Ramsing12, Henrik Høeg13, Wonkyung Jung14, Heon Song14, Chang Ho Ahn15, Vladimir Kravtsov16, Patrick Frey17, Ralf Banisch17, Stella Redpath2

1Department of Pathology, Division of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX,2US Medical Affairs, Oncology, AstraZeneca Pharmaceuticals LP, Gaithersburg, MD,3Global Medical Affairs, AstraZeneca, Cambridge, United Kingdom,4Oncology Biometrics, Oncology R&D, AstraZeneca, Macclesfield, United Kingdom,5Global Medical Affairs, AstraZeneca Pharmaceuticals LP, Gaithersburg, MD,6Medical Affairs, Daiichi Sankyo Inc., Basking Ridge, NJ,7US Medical Affairs, Daiichi Sankyo Inc., Basking Ridge, NJ,8Daiichi Sankyo Inc., Basking Ridge, NJ,9PathAI, Inc., Boston, MA,10Pathology, PathAI, Inc., Boston, MA,11Visiopharm, Hørsholm, Denmark,12Visiopharm, Copenhagen, Denmark,13R&D, Visiopharm, Hørsholm, Denmark,14Lunit, Seoul, Korea, Republic of,15Medicine Department, Lunit, Seoul, Korea, Republic of,16Machine Learning, Mindpeak GmbH, Hamburg, Germany,17Mindpeak GmbH, Hamburg, Germany

摘要 Abstract

Background Based on DESTINY-Breast04 (HER2-low) and -06 (HER2-low/-ultralow) trials, T-DXd is approved for HER2-low (immunohistochemistry [IHC] 1+ or IHC 2+/in situ hybridization negative) or -ultralow (IHC 0 with membrane staining in ≤10% of tumor cells) mBC. Whole slide images (WSIs) from mBC biopsy samples scored HER2 IHC 0/1+ were rescored by pathologists and using digital pathology (DP) to evaluate concordance. Methods This retrospective real-world evidence study included 384 WSIs collected 2020-2023, stained with PATHWAY HER2 (4B5) assay scored as HER2 IHC 0 (n = 246) or 1+ (n = 138). Three pathologists each performed 2 blinded readings per WSI using 2023 ASCO/CAP guidelines; if readings differed, a reconciled score was used. Consensus was agreement by ≥2 of 3 pathologists. The same WSIs were analysed with 4 AI-computational DP tools in development. Concordance vs manual consensus was measured by overall percentage agreement (OPA) and Cohen κ, with review time recorded. Results Of 384 WSIs, 375 had aligned HER2 IHC scores by pathologist review; 9 had discordance. Among consensus cases, 2/3 agreement occurred in 154 WSIs (41.1%) and 3/3 in 221 (58.9%); 81 (21.6%) WSIs were reclassified as IHC 0 absent membrane staining, 85 (22.7%) as IHC 0 with membrane staining, 203 (51.4%) as IHC 1+, and 6 (1.6%) as IHC 2+. HER2 IHC rescoring results with the 4 DP tools are shown in Table 1. OPA (95% CI) between consensus and DP-assisted scores across all HER2 IHC score categories was 74% (69-78%), 73% (68-77%), 69% (64-74%), and 55% (50-60%). Cohen κ (95% CI) ranged from 0.33-0.59. Median review times were shorter with DP vs manual review. Conclusion Preliminary analysis suggests integrating AI-computational DP tools into HER2 IHC clinical workflows may reduce pathologist review time. Further analysis is underway to assess concordance of DP tools with manual scoring. Table 1. HER2 IHC Re-scores (including HER2-low/ultralow) of WSIs and Median Time to Review HER2 IHC 0 absent membrane staining n (%) HER2 IHC 0 with membrane staining n (%) HER2 IHC 1+ n (%) HER2 IHC 2+ n (%) HER2 IHC 3+ n (%) Missing results a n (%) OPA score between manual consensus and DP Tool, % (95% CI) Cohen κ (95% CI) Review time, median (range), minutes Manual consensus N = 375 81 (21.6) 85 (22.7) 203 (54.1) 6 (1.6) 0 0 Not applicable Not applicable 6.7 (3.0-11.5) DP tool RV73X N = 375 72 (19.2) 100 (26.7) 176 (46.9) 5 (1.3) 0 22 (5.9) 74 (69-78) 0.59 (0.52-0.66) 2.1 (0.3-50.2) DP tool MQ52G N = 375 77 (20.5) 126 (33.6) 168 (44.8) 4 (1.1) 0 0 73 (68-77) 0.57 (0.51-0.64) 0.7 (0.1-8.5) DP tool KL84Q N = 375 82 (21.9) 137 (36.5) 145 (38.7) 10 (2.7) 1 (0.3) 0 69 (64-74) 0.53 (0.46-0.60) 2.4 (0.5-25.8) DP tool ZX19P N = 375 27 (7.2) 201 (53.6) 130 (34.7) 6 (1.6) 3 (0.8) 8 (2.1) 55 (50-60) 0.33 (0.27-0.39) Not available a’ Full dataset: 375 WSIs; Missing results = WSIs without a DP tool output
利益披露 Disclosure
S. Krishnamurthy, None. D. Tiruchinapalli, AstraZeneca Pharmaceuticals LP Employment. C. lam, AstraZeneca Employment, Stock Option. S. M. Collin, AstraZeneca Pharmaceuticals Ltd Employment, Stock Option. R. Taylor, AstraZeneca Pharmaceuticals Ltd. Employment, Stock Option. L. Luo, AstraZeneca Pharmaceuticals Ltd. Employment, Stock Option. A. Dutta, AstraZeneca Pharmaceuticals LP Independent Contractor. E. A. Elgabry, Daiichi Sankyo Employment. M. S. Woo, Daiichi Sankyo Inc. Employment, Stock, Travel, Other, Owner of Daiichi Sankyo Restricted Stock Units (RSU) and Stock Appreciation Rights (SAR), Business travel supported by company as part of employment. G. E. Kwon, Daiichi Sankyo, Inc. Employment. R. Egger, PathAI, Inc. Employment. J. A. Hipp, PathAI, Inc. Employment, Stock. L. Brunner, PathAI, Inc. Employment. J. S. Thagaard, Visiopharm Employment. T. W. Ramsing, VisioPharm Employment. H. Høeg, Visiopharm Employment. W. Jung, Lunit Employment. H. Song, Lunit Employment. C. Ahn, Lunit Employment, Stock, Stock Option. V. Kravtsov, Mindpeak GmbH Employment. P. Frey, Mindpeak GmbH Employment, Stock Option. R. Banisch, Mindpeak GmbH Employment. S. Redpath, AstraZeneca Pharmaceuticals Ltd Employment, Stock Option.

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