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CHIRP Computerized Histologic Risk Predictor (CHiRP) for Early Stage Lung Cancers

CHIRP 早期肺癌计算机化组织学风险预测器 (CHiRP)

基本信息

批准号：
10541900
负责人：
Pingfu Fu
金额：
$ 55.22万
依托单位：
EMORY UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-01-01 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10541900
关键词：
Adjuvant Adjuvant Chemotherapy Algorithms Architecture Biological Assay Cancer Diagnostics Cancer Patient Clinic Clinical Clinical Trials Clinical Trials Cooperative Group Collaborations Complement Computer software Computers Cytotoxic Chemotherapy Data Diagnosis Diagnostic tests Disease Outcome Early Diagnosis Economics Eligibility Determination Epithelium Excision Exhibits Genomics Guidelines Hematoxylin and Eosin Staining Method Histologic Image Image Analysis International Licensing Link Lung Malignant neoplasm of lung Marketing Measurement Medicare/Medicaid Molecular Morphology National Comprehensive Cancer Network Non-Small-Cell Lung Carcinoma Nuclear Operative Surgical Procedures Outcome Pathologist Patients Pattern Penetration Performance Production Quality-Adjusted Life Years Reading Recurrence Recurrent disease Regulatory Pathway Reporting Resources Risk Risk Marker Shapes Slide System Technology Testing Texture Tissue Stains Tissues Training Tumor-Infiltrating Lymphocytes Validation Visual chemotherapy cohort companion diagnostics computerized cost density diagnostic assay diagnostic tool disorder risk industry partner innovation low and middle-income countries lung cancer screening malignant breast neoplasm mortality oncotype precision medicine predicting response predictive test prognostic prognostic assays prospective prototype randomized, clinical trials side effect success treatment effect treatment response tumor tumor heterogeneity years of life lost

项目摘要

SUMMARY: In 2016 a total of 224,390 patients in the US were diagnosed with non-small cell lung cancer (NSCLC) and 16% of these patients (35,902) were diagnosed as early stage (I and II) and eligible for adjuvant cytotoxic chemotherapy (adj chemo). However, more than 50% of these patients may have low risk disease and hence may not receive added benefit from adj chemo, while suffering its side-effects. From an economic standpoint, unnecessary adj chemo for early stage NSCLC results in a loss of over $35,000 for each quality- adjusted life year lost. With increased lung cancer screening, we can expect an increase in diagnosis of early stage NSCLC. Two large completed randomized clinical trials of NSCLC (International Adjuvant Lung Cancer Trial (IALT) and JBR10) involving surgery with and without adj chemo, only found survival benefit in higher stage patients (>=Stage III). Unfortunately there are currently no validated predictive companion diagnostic (CDx) tools to identify (1) which stage II NSCLC are at a lower risk for disease recurrence and hence will not receive additional benefit from adj chemo and (2) which stage 1A, 1B patients are at elevated risk and hence will benefit? Extant genomic assays have only been shown to be prognostic (i.e. they predict mortality or recurrence) in early stage NSCLC, 1–5, but this does not imply they are predictive (i.e. they do not predict treatment response). Recently, our group validated the computerized histologic risk predictor (CHiRP), an approach that relies solely on computer extracted morphologic measurements (e.g. cellular orientation, texture, shape, architecture) from standard H&E tissue slide images to predict early recurrence in early stage NSCLC. CHiRP has been shown to be prognostic with an accuracy>85% in three independent clinical cohorts (N=290); higher compared to what has been previously reported for molecular based prognostic tests. However, to show that CHiRP is predictive, we need access to randomized clinical trial data involving early stage NSCLC patients treated with surgery and surgery+ adj chemo. The only two trials that fit these criteria are IALT and JBR10. Since molecular tests are tissue destructive, validation is more difficult compared to a tissue non-destructive approach like CHiRP; clinical trial groups are often reluctant to share tissue blocks since it is a valuable resource. For this study we have obtained preliminary approval for use of the slide images from IALT and JBR10 to establish CHiRP as a predictive Affordable Precision Medicine (APM) solution. This Academic-Industry partnership will leverage long-standing collaborations between (1) the Madabhushi group at Case Western who bring expertise in computational histomorphometric imaging, (2) the Velcheti group at the Cleveland Clinic (CCF) with clinical expertise in treatment and management of early stage NSCLC, and (3) Inspirata Inc., a cancer diagnostics company which has recently licensed a number of histomorphometry based technologies from the Madabhushi group and who will bring quality management systems and production software standards to help create a pre-commercial CHiRP test.

摘要：2016年，美国共有224，390名患者被诊断患有非小细胞肺癌。这些患者中有16%（35，902例）被诊断为早期（I期和II期），有资格接受辅助化疗。细胞毒性化学疗法（形容词化疗）。然而，这些患者中超过50%可能患有低风险疾病，因此可能不会从辅助化疗中获得额外的益处，同时遭受其副作用。从经济从这个角度来看，早期NSCLC的不必要的辅助化疗导致每种质量的损失超过35，000美元- 调整生命年损失。随着肺癌筛查的增加，我们可以预期早期诊断的增加。晚期NSCLC。两项已完成的NSCLC大型随机临床试验（国际辅助性肺癌试验（IALT）和JBR 10）涉及手术加或不加辅助化疗，仅发现较高分期的生存获益患者（>= III期）。不幸的是，目前还没有经过验证的预测伴随诊断（CDx）工具确定（1）哪些II期NSCLC的疾病复发风险较低，因此不会接受辅助化疗的额外益处和（2）哪些1A、1B期患者风险较高，因此将受益？现存的基因组测定仅在早期癌症中显示出预后性（即它们预测死亡率或复发）。 1-5期NSCLC，但这并不意味着它们是预测性的（即它们不能预测治疗反应）。最近，我们的研究小组验证了计算机组织学风险预测（CHiRP），这是一种依赖于仅基于计算机提取的形态学测量结果（例如，细胞方向、纹理、形状、架构）从标准H&E组织切片图像中预测早期NSCLC的早期复发。CHiRP已被证明在三个独立的临床队列（N=290）中，准确率>85%的预后;与先前已报道用于基于分子的预后测试。然而，为了证明CHiRP具有预测性，我们需要获得涉及接受手术治疗的早期NSCLC患者的随机临床试验数据，手术+化疗符合这些标准的仅有两项试验是IALT和JBR 10。由于分子测试是组织破坏性，与CHiRP等组织非破坏性方法相比，验证更加困难;临床试验组通常不愿意共享组织块，因为它是有价值的资源。在这项研究中，获得了使用IALT和JBR 10的幻灯片图像的初步批准，以将CHiRP确定为经济实惠的精准医疗（APM）解决方案。这种学术界与工业界的伙伴关系将利用（1）凯斯西方的Madabhushi小组带来了计算组织形态学成像的专业知识，（2）克利夫兰诊所（CCF）的Velcheti小组在治疗和管理早期阶段的临床专业知识 NSCLC，和（3）Inspirata Inc.，一家癌症诊断公司最近批准了一些来自Madabhushi集团的基于组织形态学的技术，系统和生产软件标准，以帮助创建一个预商用CHiRP测试。

项目成果

期刊论文数量（95）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer.

DOI：
10.1016/j.ebiom.2021.103481
发表时间：
2021-07
期刊：
EBioMedicine
影响因子：
11.1
作者：
Wang X;Bera K;Barrera C;Zhou Y;Lu C;Vaidya P;Fu P;Yang M;Schmid RA;Berezowska S;Choi H;Velcheti V;Madabhushi A
通讯作者：
Madabhushi A

Computer-extracted features of nuclear morphology in hematoxylin and eosin images distinguish stage II and IV colon tumors.

DOI：
10.1002/path.5864
发表时间：
2022-05
期刊：
The Journal of pathology
影响因子：
0
作者：
通讯作者：

A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises.

DOI：
10.1109/jproc.2021.3054390
发表时间：
2021-05
期刊：
Proceedings of the IEEE. Institute of Electrical and Electronics Engineers
影响因子：
0
作者：
通讯作者：

Novel imaging biomarkers predict outcomes in stage III unresectable non-small cell lung cancer treated with chemoradiation and durvalumab.

DOI：
10.1136/jitc-2021-003778
发表时间：
2022-03
期刊：
Journal for immunotherapy of cancer
影响因子：
10.9
作者：
Jazieh K;Khorrami M;Saad A;Gad M;Gupta A;Patil P;Viswanathan VS;Rajiah P;Nock CJ;Gilkey M;Fu P;Pennell NA;Madabhushi A
通讯作者：
Madabhushi A

Multi-Compartment Spatially-Derived Radiomics From Optical Coherence Tomography Predict Anti-VEGF Treatment Durability in Macular Edema Secondary to Retinal Vascular Disease: Preliminary Findings.