Daniele Palatresi1, Filippo Fedeli1, Ginevra Danti2, Elisa Pasqualini3, Francesca Castiglione4, Luca Messerini5, Daniela Massi3, Silvia Bettarini6, Paolo Tortoli6, Simone Busoni6, Silvia Pradella1, Vittorio Miele1. 1. Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy. 2. Department of Radiology, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy. ginevra.danti@gmail.com. 3. Pathology Unit, Department of Health Sciences, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy. 4. Histopathology and Molecular Diagnostics Unit, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy. 5. Department of Experimental and Clinical Medicine, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy. 6. Medical Physics Department, Careggi University Hospital, Largo Brambilla 3, 50134, Florence, Italy.
Abstract
PURPOSE: Our primary purpose was to search for computed tomography (CT) radiomic features of gastrointestinal stromal tumors (GISTs) that could potentially correlate with the risk class according to the Miettinen classification. Subsequently, assess the existence of features with possible predictive value in differentiating responder from non-responder patients to first-line therapy with Imatinib. METHODS: A retrospective study design was carried out using data from June 2009 to December 2020. We analyzed all the preoperative CTs of patients undergoing surgery for GISTs. We segmented non-contrast-enhanced CT (NCECT) and contrast-enhanced venous CT (CECT) images obtained either on three different CT scans (heterogeneous cohort) or on a single CT scan (homogeneous cohort). We then divided the patients into two groups according to Miettinen classification criteria and based on the predictive value of response to first-line therapy with Imatinib. RESULTS: We examined 54 patients with pathological confirmation of GISTs. For the heterogeneous cohort, we found a statistically significant relationship between 57 radiomic features for NCECT and 56 radiomic features for CECT using the Miettinen risk classification. In the homogeneous cohort, we found the same relationship between 8 features for the NCECT and 5 features for CECT, all included in the heterogeneous cohort. The various radiomic features are distributed with different values in the two risk stratification groups according to the Miettinen classification. We also found some features for groups predictive of response to first-line therapy with Imatinib. CONCLUSIONS: We found radiomic features that correlate with statistical significance for both the Miettinen risk classification and the molecular subtypes of response. All features found in the homogeneous study cohort were also found in the heterogeneous cohort. CT radiomic features may be useful in assessing the risk class and prognosis of GISTs.
PURPOSE: Our primary purpose was to search for computed tomography (CT) radiomic features of gastrointestinal stromal tumors (GISTs) that could potentially correlate with the risk class according to the Miettinen classification. Subsequently, assess the existence of features with possible predictive value in differentiating responder from non-responder patients to first-line therapy with Imatinib. METHODS: A retrospective study design was carried out using data from June 2009 to December 2020. We analyzed all the preoperative CTs of patients undergoing surgery for GISTs. We segmented non-contrast-enhanced CT (NCECT) and contrast-enhanced venous CT (CECT) images obtained either on three different CT scans (heterogeneous cohort) or on a single CT scan (homogeneous cohort). We then divided the patients into two groups according to Miettinen classification criteria and based on the predictive value of response to first-line therapy with Imatinib. RESULTS: We examined 54 patients with pathological confirmation of GISTs. For the heterogeneous cohort, we found a statistically significant relationship between 57 radiomic features for NCECT and 56 radiomic features for CECT using the Miettinen risk classification. In the homogeneous cohort, we found the same relationship between 8 features for the NCECT and 5 features for CECT, all included in the heterogeneous cohort. The various radiomic features are distributed with different values in the two risk stratification groups according to the Miettinen classification. We also found some features for groups predictive of response to first-line therapy with Imatinib. CONCLUSIONS: We found radiomic features that correlate with statistical significance for both the Miettinen risk classification and the molecular subtypes of response. All features found in the homogeneous study cohort were also found in the heterogeneous cohort. CT radiomic features may be useful in assessing the risk class and prognosis of GISTs.
Authors: P G Casali; S Bielack; N Abecassis; H T Aro; S Bauer; R Biagini; S Bonvalot; I Boukovinas; J V M G Bovee; B Brennan; T Brodowicz; J M Broto; L Brugières; A Buonadonna; E De Álava; A P Dei Tos; X G Del Muro; P Dileo; C Dhooge; M Eriksson; F Fagioli; A Fedenko; V Ferraresi; A Ferrari; S Ferrari; A M Frezza; N Gaspar; S Gasperoni; H Gelderblom; T Gil; G Grignani; A Gronchi; R L Haas; B Hassan; S Hecker-Nolting; P Hohenberger; R Issels; H Joensuu; R L Jones; I Judson; P Jutte; S Kaal; L Kager; B Kasper; K Kopeckova; D A Krákorová; R Ladenstein; A Le Cesne; I Lugowska; O Merimsky; M Montemurro; B Morland; 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; S J Strauss; 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: Christopher L Corless; Karla V Ballman; Cristina R Antonescu; Violetta Kolesnikova; Robert G Maki; Peter W T Pisters; Martin E Blackstein; Charles D Blanke; George D Demetri; Michael C Heinrich; Margaret von Mehren; Shreyaskumar Patel; Martin D McCarter; Kouros Owzar; Ronald P DeMatteo Journal: J Clin Oncol Date: 2014-03-17 Impact factor: 44.544
Authors: Christopher D M Fletcher; Jules J Berman; Christopher Corless; Fred Gorstein; Jerzy Lasota; B Jack Longley; Markku Miettinen; Timothy J O'Leary; Helen Remotti; Brian P Rubin; Barry Shmookler; Leslie H Sobin; Sharon W Weiss Journal: Hum Pathol Date: 2002-05 Impact factor: 3.466