PURPOSE: To evaluate the diagnostic and prognostic abilities of PET tumor segmentation-derived indices of metabolic activity for the assessment of response to neoadjuvant chemoradiotherapy and progression-free survival in patients with esophageal cancer. METHODS: Twenty-five patients with histologically confirmed esophageal cancer were retrospectively evaluated. The patients underwent PET-CT imaging before and after completion of neoadjuvant therapy. Images were evaluated visually and quantitatively with a three-dimensional threshold-based region-growing program, which calculates SUVm, SUVa of the entire tumor, metabolic tumor length (Lm) and volume (Vm) before and after therapy (SUVm1, SUVm2, SUVa1, SUVa2, Lm1, Lm2, Vm1, and Vm2, respectively). Percentage changes in these metabolic variables before and after therapy were also calculated (%SUVm, %SUVa, %Lm, %Vm, respectively). RESULTS: SUVm1 (P = 0.018), SUVa1 (P = 0.019), Lm1 (P = 0.016), and Vm1 (P = 0.016) correlated with T-status. Advanced stage tumors (T3 + T4) had significantly higher glucose metabolism, metabolic length, and volume. Moreover, Lm1 >47.4 mm and Vm1 >29 cm3 were the best predictors of the level of tumor invasiveness. SUVm1 >12.7 and SUVa1 >5.9 could differentiate patients with positive lymph nodes from those without at presentation. %SUVa >32.3% and the SUVa1 >5.5 proved to be reliable predictors of pathologic response. SUVa2 >3.55 and SUVm2 >4.35 were the best predictors of disease progression during follow-up, with the latter having the best prognostic value. CONCLUSIONS: This study showed that FDG-PET tumor segmentation-derived indices of metabolic activity play a definite role in the evaluation of response to neoadjuvant chemoradiotherapy and progression-free survival in patients with esophageal cancer.
PURPOSE: To evaluate the diagnostic and prognostic abilities of PET tumor segmentation-derived indices of metabolic activity for the assessment of response to neoadjuvant chemoradiotherapy and progression-free survival in patients with esophageal cancer. METHODS: Twenty-five patients with histologically confirmed esophageal cancer were retrospectively evaluated. The patients underwent PET-CT imaging before and after completion of neoadjuvant therapy. Images were evaluated visually and quantitatively with a three-dimensional threshold-based region-growing program, which calculates SUVm, SUVa of the entire tumor, metabolic tumor length (Lm) and volume (Vm) before and after therapy (SUVm1, SUVm2, SUVa1, SUVa2, Lm1, Lm2, Vm1, and Vm2, respectively). Percentage changes in these metabolic variables before and after therapy were also calculated (%SUVm, %SUVa, %Lm, %Vm, respectively). RESULTS: SUVm1 (P = 0.018), SUVa1 (P = 0.019), Lm1 (P = 0.016), and Vm1 (P = 0.016) correlated with T-status. Advanced stage tumors (T3 + T4) had significantly higher glucose metabolism, metabolic length, and volume. Moreover, Lm1 >47.4 mm and Vm1 >29 cm3 were the best predictors of the level of tumor invasiveness. SUVm1 >12.7 and SUVa1 >5.9 could differentiate patients with positive lymph nodes from those without at presentation. %SUVa >32.3% and the SUVa1 >5.5 proved to be reliable predictors of pathologic response. SUVa2 >3.55 and SUVm2 >4.35 were the best predictors of disease progression during follow-up, with the latter having the best prognostic value. CONCLUSIONS: This study showed that FDG-PET tumor segmentation-derived indices of metabolic activity play a definite role in the evaluation of response to neoadjuvant chemoradiotherapy and progression-free survival in patients with esophageal cancer.
Authors: Christopher P Twine; S Ashley Roberts; Wyn G Lewis; B Vicki Dave; Claire E Rawlinson; David Chan; Mark Robinson; Tom D Crosby Journal: Surg Endosc Date: 2010-04 Impact factor: 4.584
Authors: James Welsh; Arya Amini; Anna Likhacheva; Jeremy Erasmus J; Daniel Gomez; Marta Davila; Reza J Mehran; Ritsuko Komaki; Zhongxing Liao; Wayne L Hofstetter; Jeffrey Lee H; Manoop S Bhutani; Jaffer A Ajani Journal: Curr Oncol Rep Date: 2011-06 Impact factor: 5.075
Authors: Mathieu Hatt; John A Lee; Charles R Schmidtlein; Issam El Naqa; Curtis Caldwell; Elisabetta De Bernardi; Wei Lu; Shiva Das; Xavier Geets; Vincent Gregoire; Robert Jeraj; Michael P MacManus; Osama R Mawlawi; Ursula Nestle; Andrei B Pugachev; Heiko Schöder; Tony Shepherd; Emiliano Spezi; Dimitris Visvikis; Habib Zaidi; Assen S Kirov Journal: Med Phys Date: 2017-05-18 Impact factor: 4.071