Nitin Ohri1, Bilal Piperdi2, Madhur K Garg3, William R Bodner4, Rasim Gucalp5, Roman Perez-Soler6, Steven M Keller7, Chandan Guha8. 1. Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States. Electronic address: ohri.nitin@gmail.com. 2. Department of Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States. Electronic address: bpiperdi@montefiore.org. 3. Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States. Electronic address: mgarg@montefiore.org. 4. Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States. Electronic address: wbodner@montefiore.org. 5. Department of Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States. Electronic address: rgucalp@montefiore.org. 6. Department of Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States. Electronic address: rperezso@montefiore.org. 7. Department of Cardiothoracic Surgery, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467-2490, United States. Electronic address: skeller@montefiore.org. 8. Department of Radiation Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, 111 East 210th Street, Bronx, NY 10467, United States. Electronic address: cguha@montefiore.org.
Abstract
PURPOSE: Locoregional progression following definitive chemoradiotherapy (CRT) for locally advanced non-small cell lung cancer (NSCLC) is common. In this study, we explore the utility of pre-treatment PET for predicting sites of disease progression following CRT. METHODS: We identified patients treated at our institution with definitive, concurrent CRT for stage III NSCLC in the years 2007-2010 who underwent staging FDG-PET/CT. Using a semiautomatic gradient-based tool, visible thoracic hypermetabolic lesions were contoured on each patient's pre-treatment PET. Post-treatment imaging was reviewed to identify specific locations of disease progression. Patients' maximum SUV (SUVmax_pat) and metabolic tumor volume (MTV_pat) were evaluated as predictors of clinical outcomes using logrank testing. Competing risks analysis was performed to examine the relationship between lesion (tumor or lymph node) MTV (MTV_les) and the risk of local disease progression. Patient death and progression in other sites were treated as competing risks. RESULTS: 28 patients with 82 hypermetabolic lesions (27 pulmonary tumors, 55 lymph nodes) met inclusion criteria. Median follow-up was 39.0 months for living patients. Median progression-free survival (PFS) was 12.4 months, and median overall survival (OS) was 31.8 months. Low MTV_pat was associated with improved PFS (median 14.3 months for MTV<60 cc vs. 9.7 months for MTV>60 cc, p=0.039). MTV_les was strongly associated with the risk of local disease progression. The 2-year cumulative incidence rate (CIR) for progression in lesions larger than 25 cc was 45%, compared to 5% for lesions under 25 cc (p<0.001). CONCLUSION: Pre-treatment PET can be used to identify specific lesions at high risk for treatment failure following definitive CRT for locally advanced NSCLC. Selective treatment intensification to high-risk lesions should be studied as a strategy to improve clinical outcomes in this patient population.
PURPOSE: Locoregional progression following definitive chemoradiotherapy (CRT) for locally advanced non-small cell lung cancer (NSCLC) is common. In this study, we explore the utility of pre-treatment PET for predicting sites of disease progression following CRT. METHODS: We identified patients treated at our institution with definitive, concurrent CRT for stage III NSCLC in the years 2007-2010 who underwent staging FDG-PET/CT. Using a semiautomatic gradient-based tool, visible thoracic hypermetabolic lesions were contoured on each patient's pre-treatment PET. Post-treatment imaging was reviewed to identify specific locations of disease progression. Patients' maximum SUV (SUVmax_pat) and metabolic tumor volume (MTV_pat) were evaluated as predictors of clinical outcomes using logrank testing. Competing risks analysis was performed to examine the relationship between lesion (tumor or lymph node) MTV (MTV_les) and the risk of local disease progression. Patientdeath and progression in other sites were treated as competing risks. RESULTS: 28 patients with 82 hypermetabolic lesions (27 pulmonary tumors, 55 lymph nodes) met inclusion criteria. Median follow-up was 39.0 months for living patients. Median progression-free survival (PFS) was 12.4 months, and median overall survival (OS) was 31.8 months. Low MTV_pat was associated with improved PFS (median 14.3 months for MTV<60 cc vs. 9.7 months for MTV>60 cc, p=0.039). MTV_les was strongly associated with the risk of local disease progression. The 2-year cumulative incidence rate (CIR) for progression in lesions larger than 25 cc was 45%, compared to 5% for lesions under 25 cc (p<0.001). CONCLUSION: Pre-treatment PET can be used to identify specific lesions at high risk for treatment failure following definitive CRT for locally advanced NSCLC. Selective treatment intensification to high-risk lesions should be studied as a strategy to improve clinical outcomes in this patient population.
Authors: Eunsin Lee; Jing Zeng; Robert S Miyaoka; Jatinder Saini; Paul E Kinahan; George A Sandison; Tony Wong; Hubert J Vesselle; Ramesh Rengan; Stephen R Bowen Journal: Med Phys Date: 2017-06-01 Impact factor: 4.071
Authors: Stephen R Bowen; Daniel S Hippe; Hannah M Thomas; Balukrishna Sasidharan; Paul D Lampe; Christina S Baik; Keith D Eaton; Sylvia Lee; Renato G Martins; Rafael Santana-Davila; Delphine L Chen; Paul E Kinahan; Robert S Miyaoka; Hubert J Vesselle; A McGarry Houghton; Ramesh Rengan; Jing Zeng Journal: Adv Radiat Oncol Date: 2021-11-21
Authors: Kevin P Horn; Hannah M T Thomas; Hubert J Vesselle; Paul E Kinahan; Robert S Miyaoka; Ramesh Rengan; Jing Zeng; Stephen R Bowen Journal: Clin Nucl Med Date: 2021-11-01 Impact factor: 10.782