PURPOSE: We evaluated the potential of sequential fluorine-18 fluorodeoxyglucose ((18) F-FDG) positron emission tomography (PET)/computed tomography (CT) and MRI (PET/MRI) after one cycle of neoadjuvant chemotherapy to predict a poor histologic response in osteosarcoma. METHODS: A prospective study was conducted on 30 patients with osteosarcoma treated with two cycles of neoadjuvant chemotherapy and surgery. All patients underwent PET/MRI before, after one cycle, and after the completion of neoadjuvant chemotherapy, respectively. Imaging parameters [maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and tumor volume based on magnetic resonance (MR) images (MRV)] and their % changes were calculated on each PET/MRI data set, and histological responses were evaluated on the postsurgical specimen. RESULTS: A total of 17 patients (57%) exhibited a poor histologic response after two cycles of chemotherapy. Unlike the little volumetric change in MRI, PET parameters significantly decreased after one and two cycles of chemotherapy, respectively. After one cycle of chemotherapy, SUVmax, MTV, and TLG predicted the poor responders. Among these parameters, either MTV ≥ 47 mL or TLG ≥ 190 g after one cycle of chemotherapy was significantly associated with a poor histologic response on multivariate logistic regression analysis (OR 8.98, p = 0.039). The sensitivity, specificity, and accuracy of these parameters were 71%, 85% and 77%; and 71%, 85% and 77 %, respectively. CONCLUSION: The histologic response to neoadjuvant chemotherapy in osteosarcoma can be predicted accurately by FDG PET after one course of chemotherapy. Among PET parameters, MTV and TLG were independent predictors of the histologic response.
PURPOSE: We evaluated the potential of sequential fluorine-18 fluorodeoxyglucose ((18) F-FDG) positron emission tomography (PET)/computed tomography (CT) and MRI (PET/MRI) after one cycle of neoadjuvant chemotherapy to predict a poor histologic response in osteosarcoma. METHODS: A prospective study was conducted on 30 patients with osteosarcoma treated with two cycles of neoadjuvant chemotherapy and surgery. All patients underwent PET/MRI before, after one cycle, and after the completion of neoadjuvant chemotherapy, respectively. Imaging parameters [maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and tumor volume based on magnetic resonance (MR) images (MRV)] and their % changes were calculated on each PET/MRI data set, and histological responses were evaluated on the postsurgical specimen. RESULTS: A total of 17 patients (57%) exhibited a poor histologic response after two cycles of chemotherapy. Unlike the little volumetric change in MRI, PET parameters significantly decreased after one and two cycles of chemotherapy, respectively. After one cycle of chemotherapy, SUVmax, MTV, and TLG predicted the poor responders. Among these parameters, either MTV ≥ 47 mL or TLG ≥ 190 g after one cycle of chemotherapy was significantly associated with a poor histologic response on multivariate logistic regression analysis (OR 8.98, p = 0.039). The sensitivity, specificity, and accuracy of these parameters were 71%, 85% and 77%; and 71%, 85% and 77 %, respectively. CONCLUSION: The histologic response to neoadjuvant chemotherapy in osteosarcoma can be predicted accurately by FDG PET after one course of chemotherapy. Among PET parameters, MTV and TLG were independent predictors of the histologic response.
Authors: Gi Jeong Cheon; Min Suk Kim; Jun Ah Lee; Soo-Yong Lee; Wan Hyeong Cho; Won Seok Song; Jae-Soo Koh; Ji Young Yoo; Dong Hyun Oh; Duk Seop Shin; Dae-Geun Jeon Journal: J Nucl Med Date: 2009-08-18 Impact factor: 10.057
Authors: Colleen M Costelloe; Homer A Macapinlac; John E Madewell; Nancy E Fitzgerald; Osama R Mawlawi; Eric M Rohren; A Kevin Raymond; Valerae O Lewis; Peter M Anderson; Roland L Bassett; Robyn K Harrell; Edith M Marom Journal: J Nucl Med Date: 2009-03 Impact factor: 10.057
Authors: Ashok J Theruvath; Florian Siedek; Anne M Muehe; Jordi Garcia-Diaz; Julian Kirchner; Ole Martin; Michael P Link; Sheri Spunt; Allison Pribnow; Jarrett Rosenberg; Ken Herrmann; Sergios Gatidis; Jürgen F Schäfer; Michael Moseley; Lale Umutlu; Heike E Daldrup-Link Journal: Radiology Date: 2020-05-05 Impact factor: 11.105
Authors: Craig Gerrand; Nick Athanasou; Bernadette Brennan; Robert Grimer; Ian Judson; Bruce Morland; David Peake; Beatrice Seddon; Jeremy Whelan Journal: Clin Sarcoma Res Date: 2016-05-04