OBJECTIVE: To analyze patterns of response in soft tissue sarcomas exposed to pazopanib using CT-morphologic and textural features and their suitability for evaluating therapeutic response. METHODS: Retrospective evaluation of CT response and texture patterns in 33 patients (23 female; mean age: 61.2 years, range, 30-85 years) with soft tissue sarcomas treated with pazopanib from October 2008 to July 2017. Response evaluation was based on modified (m)CHOI-criteria and RECISTv.1.1 and classified as partial response (PR), stable disease (SD), progressive disease (PD). The following CT-texture (CTTA)-parameters were calculated: mean, entropy and uniformity of intensity/average/skewness/entropy of co-occurrence matrix and contrast of neighboring-gray-level-dependence-matrix. RESULTS: Following mCHOI-criteria, 12 patients achieved PR, 7 SD and 14 PD. As per RECISTv.1.1 9 patients obtained PR, 9 SD and 15 PD. Frequent patterns of response were tumor liquefaction and necrosis (n=4/33, 12.1% each). Further patterns included shrinkage and cavitation (n=2/33, 6.1% each). In responders, differences in mean heterogeneity (p=0.01), intensity (p=0.03), average (p=0.03) and entropy of skewness (p=0.01) were found at follow-up whereas in non-responders, CTTA-parameters did not change significantly. Baseline-CTTA-features differed between responders and non-responders in terms of uniformity of skewness (p=0.045). Baseline-CTTA-parameters did not correlate with any morphologic response pattern. CONCLUSION: Most frequent patterns of response to pazopanib were tumor liquefaction and necrosis. Single CT-textural features show strong association with the response to pazopanib-although limited in relation to specific response patterns. ADVANCES IN KNOWLEDGE: Tumor liquefication and necrosis are important patterns of response to pazopanib. CT-texture analysis has limited associations with specific response patterns.
OBJECTIVE: To analyze patterns of response in soft tissue sarcomas exposed to pazopanib using CT-morphologic and textural features and their suitability for evaluating therapeutic response. METHODS: Retrospective evaluation of CT response and texture patterns in 33 patients (23 female; mean age: 61.2 years, range, 30-85 years) with soft tissue sarcomas treated with pazopanib from October 2008 to July 2017. Response evaluation was based on modified (m)CHOI-criteria and RECISTv.1.1 and classified as partial response (PR), stable disease (SD), progressive disease (PD). The following CT-texture (CTTA)-parameters were calculated: mean, entropy and uniformity of intensity/average/skewness/entropy of co-occurrence matrix and contrast of neighboring-gray-level-dependence-matrix. RESULTS: Following mCHOI-criteria, 12 patients achieved PR, 7 SD and 14 PD. As per RECISTv.1.1 9 patients obtained PR, 9 SD and 15 PD. Frequent patterns of response were tumor liquefaction and necrosis (n=4/33, 12.1% each). Further patterns included shrinkage and cavitation (n=2/33, 6.1% each). In responders, differences in mean heterogeneity (p=0.01), intensity (p=0.03), average (p=0.03) and entropy of skewness (p=0.01) were found at follow-up whereas in non-responders, CTTA-parameters did not change significantly. Baseline-CTTA-features differed between responders and non-responders in terms of uniformity of skewness (p=0.045). Baseline-CTTA-parameters did not correlate with any morphologic response pattern. CONCLUSION: Most frequent patterns of response to pazopanib were tumor liquefaction and necrosis. Single CT-textural features show strong association with the response to pazopanib-although limited in relation to specific response patterns. ADVANCES IN KNOWLEDGE: Tumor liquefication and necrosis are important patterns of response to pazopanib. CT-texture analysis has limited associations with specific response patterns.
Authors: P G Casali; N Abecassis; H T Aro; S Bauer; R Biagini; S Bielack; S Bonvalot; I Boukovinas; J V M G Bovee; T Brodowicz; J M Broto; A Buonadonna; E De Álava; A P Dei Tos; X G Del Muro; P Dileo; M Eriksson; A Fedenko; V Ferraresi; A Ferrari; S Ferrari; A M Frezza; S Gasperoni; H Gelderblom; T Gil; G Grignani; A Gronchi; R L Haas; B Hassan; P Hohenberger; R Issels; H Joensuu; R L Jones; I Judson; P Jutte; S Kaal; B Kasper; K Kopeckova; D A Krákorová; A Le Cesne; I Lugowska; O Merimsky; M Montemurro; M A Pantaleo; R Piana; P Picci; S Piperno-Neumann; A L Pousa; P Reichardt; M H Robinson; P Rutkowski; A A Safwat; P Schöffski; S Sleijfer; S Stacchiotti; K Sundby Hall; M Unk; F Van Coevorden; W T A van der Graaf; J Whelan; E Wardelmann; O Zaikova; J Y Blay Journal: Ann Oncol Date: 2018-10-01 Impact factor: 32.976
Authors: Anna Maria Frezza; Robin L Jones; Salvatore Lo Vullo; Naofumi Asano; Francesca Lucibello; Eytan Ben-Ami; Ravin Ratan; Pawel Teterycz; Kjetil Boye; Mehdi Brahmi; Emanuela Palmerini; Alexander Fedenko; Bruno Vincenzi; Antonella Brunello; Ingrid M E Desar; Robert S Benjamin; Jean Yves Blay; Javier Martin Broto; Paolo G Casali; Hans Gelderblom; Giovanni Grignani; Alessandro Gronchi; Kirsten Sundby Hall; Olivier Mir; Piotr Rutkowski; Andrew J Wagner; Olga Anurova; Paola Collini; Angelo P Dei Tos; Uta Flucke; Jason L Hornick; Ingvild Lobmaier; Terrier Philippe; Piero Picci; Dominique Ranchere; Salvatore L Renne; Marta Sbaraglia; Khin Thway; Michal Wagrodzki; Wei-Lien Wang; Akihiko Yoshida; Luigi Mariani; Akira Kawai; Silvia Stacchiotti Journal: JAMA Oncol Date: 2018-09-13 Impact factor: 31.777
Authors: E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij Journal: Eur J Cancer Date: 2009-01 Impact factor: 9.162
Authors: Fergus Davnall; Connie S P Yip; Gunnar Ljungqvist; Mariyah Selmi; Francesca Ng; Bal Sanghera; Balaji Ganeshan; Kenneth A Miles; Gary J Cook; Vicky Goh Journal: Insights Imaging Date: 2012-10-24