Imaging as a Predictor of Therapeutic Response 2017 RSNA Clinical - PowerPoint PPT Presentation

Imaging as a Predictor of Therapeutic Response 2017 RSNA Clinical Trials Methodology Workshop David A. Mankoff, MD, PhD Department of Radiology (Nuclear Medicine) Perelman School of Medicine University of Pennsylvania Philadelphia, PA

Imaging and Therapeutic Response � Clinical scenarios and questions � Cancer biomarker approaches for functional and molecular imaging � Prognosis � Prediction � Response � Biologic response

Guiding Cancer Therapy: Clinical Needs Relapse Survival Therapy Post/Rx Pre/Rx Early Mid/Rx /Aggressive Dz? Response? Residual Disease? /Rx Targets /Yes/no /How much?

How Can Biomarkers Guide Cancer Therapy? � Goals in cancer treatment � Characterize tumor biology pre/Rx � Individualized, specific therapy � Static response may be acceptable � The implied needs for cancer biomarkers � Characterize tumor biology, predict behavior � Identify targets, predict response � Measure tumor response (early!) � Relate response to survival

Biomarkers and Cancer Therapy What Can Imaging Do? � Goals in cancer treatment � Characterize tumor biology pre/Rx � Individualized, specific therapy � Static response may be acceptable � The implied questions for cancer imaging � Characterize in vivo tumor biology / prognosis � Identify targets, predict response / prediction � Measure tumor response (early!) / response � Relate response to survival / biologic response

Guidelines for Biomarker Studies: REMARK

Imaging and Therapeutic Response � Clinical scenarios and questions � Cancer biomarker approaches for functional and molecular imaging � Prognosis � Prediction � Response � Biologic response

Study Design for:

FDG Predicts Survival in Recurrent Thyroid Cancer / Robbins, JCEM, 2006 FDG 131 I / PET FDG/ FDG+ L Cervical High TG, LN Neg Scan

University of Washington KA Krohn

Tumor Hypoxia Quantified by PET Predicts Survival FMISO PET FMISO PET H Cu/ATSM PET Brain Tumor Cervical Cancer & N Cancer Low FMISO Low Uptake Uptake High FMISO High Uptake Uptake (Spence, Clin (Rajendran, Clin Can (Dehdashti, Int J Radiat Cancer Res, 2008) Res, 2007) Oncol Biol Phys, 2003)

ACRIN 6684 MULTICENTER, PHASE II ASSESSMENT OF TUMOR HYPOXIA IN GLIOBLASTOMA USING 18 F/FLUOROMISONIDAZOLE (FMISO) WITH PET AND MRI Elizabeth Gerstner, MD, PI Radiotherapy and Diagnosis Outcomes: Temazolamide and Surgery Progression Overall Survival (OS) FMISO PET MRI FMISO PET MRI

ACIN 6684: Hypoxia PET and MRI Predict GBM PFS and OS Gerstner, Clin Cancer Res, 22:5079, 2016

Imaging and Therapeutic Response � Clinical scenarios and questions � Cancer biomarker approaches for functional and molecular imaging � Prognosis � Prediction � Response � Biologic response

Outcomes for Cancer Imaging: Prediction � Predictor of response to specific therapy � Positive / predicts who will respond � Negative / predicts who will not respond

Study Predictive Assays Design for: Assay / + Response Response Rate Rate � Examples of in vitro assay � ER / Endocrine therapy for breast cancer � TS / 5/FU for colon cancer � HER2 / Trastuzumab for breast cancer

Targeted Breast Cancer Therapy: The Estrogen Receptor (ER) and Endocrine Treatment (Johnson and Dowsett, Nar Rev Cancer 3:821, 2002)

18 F/Fluoroestradiol (FES): PET Estrogen Receptor (ER) Imaging Provides a Quantitative Estimate of ER Expression vs Radioligand Binding vs IHC � �� 8 (%ID/mL x 10 /4 ) Tumor Uptake 6 � * 4 2 �� 0 (Kieswetter, J Nucl 0 150 200 50 100 Med, 25: 1212, 1984) ER Concentration (fmoles/mg protein) (Peterson, J Nucl Med 49: (Mintun, Radiology 169:45, 367, 2008) 1988)

FES Uptake Predicts Breast Cancer Response to Hormonal Therapy Post/Rx Pre/Rx Example 1 � Recurrent sternal lesion Excellent response � ER+ primary after 6 wks � Recurrent Dz Letrozole strongly FES+ FES FDG FDG Example 2 � Newly Dx ’ ’ d ’ ’ met breast CA No response to several � ER+ primary different � FES/negative hormonal Rx ’ ’ s ’ ’ bone mets (Linden, J Clin Onc, 2006) University of Washington

���������������������������������������������� 2�!$��!�� 3�-� $� FES PET Primary Aim FDG PET MBC from ER+ Endocrine Therapy Response Primary PFS Validation Aim 3, 6 month assessment Biopsy � �������� ���!���"# � ��� $���� �����%� %������� & ��� �'���� $�'���� ������ $�'�� ���!���"# & ��� $��$��(�����)�$�*��+��,-+���./ & ����)�����0��1���� $� � �����0��1���$������ Group Meeting • Nov 14/16, 2013 21

Cancer Markers: Prognostic, Predictive, or Both? Non/targeted therapy PFS ER/directed therapy No therapy ER/ ER+

Imaging and Therapeutic Response � Clinical scenarios and questions � Cancer biomarker approaches for functional and molecular imaging � Prognosis � Prediction � Response � Biologic response � Future directions

Outcomes for Cancer Imaging: Response � Accuracy of response assessment � Response or not / R versus NR � Degree of response – residual dz versus CR � Surrogate outcome measure � Predictor of DFS, OS

Study Measuring Response Design for: Relapse & Therapy Pre/Rx Response Survival Pre/Rx Post/Rx Difference Predictor of TTP Sens, Spec, ROC Outcomes: and Survival for Response

Functional and Molecular Imaging Response Neo/Adjuvant Therapy of Locally Advanced Breast Cancer (LABC) Surgery Chemotherapy Pre/Rx 4m 2m Baseline Final Mid/Rx

FDG PET to Monitor Breast Cancer Response to Therapy Wahl, J Clin Oncol 11:2101, 1993 Chemotherapy Surgery Pre/ (Path Response) Rx P < .001 P = NS (N=11) Baseline Mid/Rx

Change in MIBI Uptake Predicts Response Pathologic Complete Response Uptake vs Response Progressive Disease ROC for CR versus PR A z =0.96 (A z for size chng = 0.77) (Mankoff, Cancer, 1998)

Functional Imaging Predicts Outcome 99m Tc/MIBI Serial Imaging Residual Uptake Predicts Outcome Change in Uptake Predicts Response � 6 4 4 Low MIBI Uptake 4 6 7 5 Disease/Free 4 6 5 4 High MIBI Uptake Survival 4 6 � 5 (P < .001) 4 6 4 4 (N=62) 4 5 4 � 4 4 � � � # � � � �� � � � Low MIBI Uptake � 6 4 4 Overall 4 6 7 5 Survival 4 6 5 4 High MIBI Uptake 4 6 � 5 (P < .01) (Dunnwald, Cancer, 103: 680, 2005) 4 6 4 4 4 5 4 � 4 4 � � � # � � � �� � � �

Biologic Events in Response to Successful Cancer Therapy Rationale for Measuring Early Response by Cell Proliferation Imaging Rx DNA Synthesis Cellular Proliferation or Cell Death Viable Cell Number Tumor size

ACRIN 6688 Study Outline � ����������������������� ��������������������� � �������������������������������� � ���������������������������!� ��������������������� "��#$%�������������!�����!���������������������&��� ��������������������� ���������' 8 �( )*+���+,�+ ����������������� &)*+��' �������������������� 8 �( )*+���+,�+ ���������������������� &)*+�.' ������������������������� �( )*+���+,�+ ��������������������� &)*+�-' ������������������ � �������������������%� ������������������������������������ � "��#$%�������������!%�����/���������� �������

ACRIN 6688: FLT PET to Measure Early Breast Cancer Response (PI: Lale Kostakoglu) ���� �!���"# 7�$������ Best ∆SUV max cut/off for predicting pCR = /51% (sensitivity 56%;specificity 79%). *9������%�0+�:��0'� .�$+��4�5+��"01/

Imaging and Therapeutic Response � Clinical scenarios and questions � Cancer biomarker approaches for functional and molecular imaging � Prognosis � Prediction � Response � Biologic response � Future directions

Outcomes for Cancer Imaging: Biologic Response � Can functional/molecular response better predict outcome? � Predict DFS, OS, etc � And what are the biologic insights � Surrogate outcome measure?