PURPOSE: We sought to determine whether metabolic volume-based measurements on FDG PET/CT scans could provide additional information for predicting outcome in patients with stage III non-small-cell lung cancer (NSCLC) treated with induction chemotherapy. METHODS: Included in the study were 32 patients with stage III NSCLC who were treated with induction platinum-based chemotherapy followed in 21 by surgery. All patients had an FDG PET/CT scan before and after the induction chemotherapy. Tumours were delineated using adaptive threshold methods. The SUVmax, SUVpeak, SUVmean, tumour volume (TV), total lesion glycolysis (TLG), and volume and largest diameter on the CT images (CTV and CTD, respectively) were calculated. Index ratios of the primary tumour were calculated by dividing the follow-up measurements by the baseline measurements. The prognostic value of each parameter for event-free survival (EFS) was determined using Cox regression models. RESULTS: The median follow-up time was 19 months (range 6-43 months). Baseline PET and CT parameters were not significant prognostic factors. After induction therapy, only SUVmax, SUVpeak, SUVmean, TV, TLG and CTV were prognostic factors for EFS, in contrast to CTD. Of the index ratios, only TV and TLG ratios were prognostic factors for EFS. Patients with a TLG ratio <0.48 had a longer EFS than those with a TLG ratio >0.48 (13.9 vs. 9.2 months, p = 0.04). After adjustment for the effect of surgical treatment, all the parameters significantly correlated with EFS remained significant. CONCLUSION: SUV, metabolic volume-based indices, and CTV after induction chemotherapy give independent prognostic information in stage III NSCLC. However, changes in metabolic TV and TLG under induction treatment provide more accurate prognostic information than SUV alone, and CTD and CTV.
PURPOSE: We sought to determine whether metabolic volume-based measurements on FDG PET/CT scans could provide additional information for predicting outcome in patients with stage III non-small-cell lung cancer (NSCLC) treated with induction chemotherapy. METHODS: Included in the study were 32 patients with stage III NSCLC who were treated with induction platinum-based chemotherapy followed in 21 by surgery. All patients had an FDG PET/CT scan before and after the induction chemotherapy. Tumours were delineated using adaptive threshold methods. The SUVmax, SUVpeak, SUVmean, tumour volume (TV), total lesion glycolysis (TLG), and volume and largest diameter on the CT images (CTV and CTD, respectively) were calculated. Index ratios of the primary tumour were calculated by dividing the follow-up measurements by the baseline measurements. The prognostic value of each parameter for event-free survival (EFS) was determined using Cox regression models. RESULTS: The median follow-up time was 19 months (range 6-43 months). Baseline PET and CT parameters were not significant prognostic factors. After induction therapy, only SUVmax, SUVpeak, SUVmean, TV, TLG and CTV were prognostic factors for EFS, in contrast to CTD. Of the index ratios, only TV and TLG ratios were prognostic factors for EFS. Patients with a TLG ratio <0.48 had a longer EFS than those with a TLG ratio >0.48 (13.9 vs. 9.2 months, p = 0.04). After adjustment for the effect of surgical treatment, all the parameters significantly correlated with EFS remained significant. CONCLUSION: SUV, metabolic volume-based indices, and CTV after induction chemotherapy give independent prognostic information in stage III NSCLC. However, changes in metabolic TV and TLG under induction treatment provide more accurate prognostic information than SUV alone, and CTD and CTV.
Authors: Binsheng Zhao; Geoffrey R Oxnard; Chaya S Moskowitz; Mark G Kris; William Pao; Pingzhen Guo; Valerie M Rusch; Marc Ladanyi; Naiyer A Rizvi; Lawrence H Schwartz Journal: Clin Cancer Res Date: 2010-06-09 Impact factor: 12.531
Authors: Daniel J Boffa; Frank C Detterbeck; Erica J Smith; Ramon Rami-Porta; John Crowley; Daniel Zelterman; Lynn Tanoue; Anthony W Kim; Peter Goldstraw Journal: J Thorac Oncol Date: 2010-11 Impact factor: 15.609
Authors: J A Roth; E N Atkinson; F Fossella; R Komaki; M Bernadette Ryan; J B Putnam; J S Lee; H Dhingra; L De Caro; M Chasen; W K Hong Journal: Lung Cancer Date: 1998-07 Impact factor: 5.705
Authors: Corneline J Hoekstra; Sigrid G Stroobants; Egbert F Smit; Johan Vansteenkiste; Harm van Tinteren; Pieter E Postmus; Richard P Golding; Bonne Biesma; Frans J H M Schramel; Nico van Zandwijk; Adriaan A Lammertsma; Otto S Hoekstra Journal: J Clin Oncol Date: 2005-11-20 Impact factor: 44.544
Authors: H Young; R Baum; U Cremerius; K Herholz; O Hoekstra; A A Lammertsma; J Pruim; P Price Journal: Eur J Cancer Date: 1999-12 Impact factor: 9.162
Authors: Kenneth J Biehl; Feng-Ming Kong; Farrokh Dehdashti; Jian-Yue Jin; Sasa Mutic; Issam El Naqa; Barry A Siegel; Jeffrey D Bradley Journal: J Nucl Med Date: 2006-11 Impact factor: 10.057
Authors: Sara Carvalho; Ralph T H Leijenaar; Emmanuel Rios Velazquez; Cary Oberije; Chintan Parmar; Wouter van Elmpt; Bart Reymen; Esther G C Troost; Michel Oellers; Andre Dekker; Robert Gillies; Hugo J W L Aerts; Philippe Lambin Journal: Acta Oncol Date: 2013-09-09 Impact factor: 4.089
Authors: Ivayla Apostolova; Julian Rogasch; Ralph Buchert; Heinz Wertzel; H Jost Achenbach; Jens Schreiber; Sandra Riedel; Christian Furth; Alexandr Lougovski; Georg Schramm; Frank Hofheinz; Holger Amthauer; Ingo G Steffen Journal: BMC Cancer Date: 2014-12-01 Impact factor: 4.430