Correlation of CT radiomic features for GISTs with pathological classification and molecular subtypes: preliminary and monocentric experience

Palatresi, Daniele; Fedeli, Filippo; Danti, Ginevra; Pasqualini, Elisa; Castiglione, Francesca; Messerini, Luca; Massi, Daniela; Bettarini, Silvia; Tortoli, Paolo; Busoni, S.; Pradella, Silvia; Miele, Vittorio

doi:10.1007/s11547-021-01446-5

Cited by 29 publications

(17 citation statements)

References 26 publications

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“…Other excluded articles discussed the efficacy of a specific TKI treatment but did not quantify the efficacy of imaging features in predicting or monitoring response [ 22 , 23 ]. Of the 90 eligible articles, 67 were concerning response prediction [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , ...…”

Section: Resultsmentioning

confidence: 99%

Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review

et al. 2022

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Gastrointestinal stromal tumors (GISTs) are rare mesenchymal neoplasms. Tyrosine kinase inhibitor (TKI) therapy is currently part of routine clinical practice for unresectable and metastatic disease. It is important to assess the efficacy of TKI treatment at an early stage to optimize therapy strategies and eliminate futile ineffective treatment, side effects and unnecessary costs. This systematic review provides an overview of the imaging features obtained from contrast-enhanced (CE)-CT and 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/CT to predict and monitor TKI treatment response in GIST patients. PubMed, Web of Science, the Cochrane Library and Embase were systematically screened. Articles were considered eligible if quantitative outcome measures (area under the curve (AUC), correlations, sensitivity, specificity, accuracy) were used to evaluate the efficacy of imaging features for predicting and monitoring treatment response to various TKI treatments. The methodological quality of all articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies, v2 (QUADAS-2) tool and modified versions of the Radiomics Quality Score (RQS). A total of 90 articles were included, of which 66 articles used baseline [18F]FDG-PET and CE-CT imaging features for response prediction. Generally, the presence of heterogeneous enhancement on baseline CE-CT imaging was considered predictive for high-risk GISTs, related to underlying neovascularization and necrosis of the tumor. The remaining articles discussed therapy monitoring. Clinically established imaging features, including changes in tumor size and density, were considered unfavorable monitoring criteria, leading to under- and overestimation of response. Furthermore, changes in glucose metabolism, as reflected by [18F]FDG-PET imaging features, preceded changes in tumor size and were more strongly correlated with tumor response. Although CE-CT and [18F]FDG-PET can aid in the prediction and monitoring in GIST patients, further research on cost-effectiveness is recommended.

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Section: Resultsmentioning

confidence: 99%

Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review

et al. 2022

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“…CT examination is considered to be the first choice for preoperative tumor staging, surgical planning, and postoperative follow-up among GIST patients ( 31 ). In addition, existing studies suggest that the degree of malignancy of neoplasms can be further evaluated by analyzing the relationship between CT imaging features and risk stratification to optimize the preoperative therapeutic schedule and guide the surgical treatment ( 32 ). Zhou et al ( 33 ) conducted a multivariate logistic regression analysis of CT signs in 129 GIST patients and found that tumor diameter >10 cm and mixed growth mode were independent predictors of high-risk GIST.…”

Section: Discussionmentioning

confidence: 99%

The relationship between Ki-67 expression and imaging signs and pathological features in GISTs

Xiao

Zhang²,

Wang³

et al. 2023

Front. Surg.

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IntroductionTo investigate the correlations between the Ki-67 index and plain-scan computerized tomography (CT) signs and pathological features of gastrointestinal stromal tumor (GIST) tissue.Materials and methodsData from 186 patients with GIST diagnosed by pathology and immunohistochemistry (IHC) in Peking University First Hospital from May 2016 to May 2022 were analyzed. The patients were divided into two groups: Ki-67 ≤5% and >5%. Correlation analysis, univariate and multivariate Logistic regression analysis were used to explore the correlations between CT signs, pathological features, and Ki-67 expression.ResultsUnivariate indicators correlated with the Ki-67 index were mitotic count, pathological grade, tumor hemorrhage, tumor necrosis, tumor size, and tumor density. Multivariate Logistic regression indicated that the mitotic count [odds ratio (OR) 10.222, 95% confidence interval (CI) 4.312–31.039], pathological grade (OR 2.139, 95% CI 1.397–3.350), and tumor size (OR 1.096, 95% CI 1.020–1.190) were independently associated with the Ki-67 expression level. The concordance indexes (C-index) for the pathological features and CT signs models were 0.876 (95% CI 0.822–0.929) and 0.697 (95% CI 0.620–0.774), respectively, with positive predictive values of 93.62% and 58.11% and negative predictive values of 81.29% and 75.89%, respectively. After internal verification by the Bootstrap method, the fitting degree of the pathological features model was found to be better than that of the CT signs model.ConclusionMitotic count, pathological risk grading, and tumor size are independent risk factors correlating with high Ki-67 index. These results indicate that the Ki-67 index reflects tumor malignancy and can predict recurrence and metastasis of GIST.

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“…With such techniques, it is also possible to derive information directly from the images on the molecular and genomic characteristics of the tumor (radiogenomics) with the ultimate intent of extracting indications on aggressiveness, prognosis, and therapeutic response [ 77 , 133 , 201 , 202 , 203 , 204 , 205 , 206 , 207 , 208 , 209 , 210 , 211 , 212 , 213 , 214 , 215 , 216 , 217 , 218 , 219 , 220 , 221 , 222 , 223 , 224 , 225 , 226 , 227 , 228 , 229 , 230 , 231 , 232 ].…”

Section: Precision Medicine: Radiomics and Radiogenomics—the New Fron...mentioning

confidence: 99%

Gender Medicine in Clinical Radiology Practice

Giacobbe

Granata

Trovato

et al. 2023

JPM

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Gender Medicine is rapidly emerging as a branch of medicine that studies how many diseases common to men and women differ in terms of prevention, clinical manifestations, diagnostic-therapeutic approach, prognosis, and psychological and social impact. Nowadays, the presentation and identification of many pathological conditions pose unique diagnostic challenges. However, women have always been paradoxically underestimated in epidemiological studies, drug trials, as well as clinical trials, so many clinical conditions affecting the female population are often underestimated and/or delayed and may result in inadequate clinical management. Knowing and valuing these differences in healthcare, thus taking into account individual variability, will make it possible to ensure that each individual receives the best care through the personalization of therapies, the guarantee of diagnostic-therapeutic pathways declined according to gender, as well as through the promotion of gender-specific prevention initiatives. This article aims to assess potential gender differences in clinical-radiological practice extracted from the literature and their impact on health and healthcare. Indeed, in this context, radiomics and radiogenomics are rapidly emerging as new frontiers of imaging in precision medicine. The development of clinical practice support tools supported by artificial intelligence allows through quantitative analysis to characterize tissues noninvasively with the ultimate goal of extracting directly from images indications of disease aggressiveness, prognosis, and therapeutic response. The integration of quantitative data with gene expression and patient clinical data, with the help of structured reporting as well, will in the near future give rise to decision support models for clinical practice that will hopefully improve diagnostic accuracy and prognostic power as well as ensure a more advanced level of precision medicine.

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Correlation of CT radiomic features for GISTs with pathological classification and molecular subtypes: preliminary and monocentric experience

Cited by 29 publications

References 26 publications

Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review

Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review

The relationship between Ki-67 expression and imaging signs and pathological features in GISTs

Gender Medicine in Clinical Radiology Practice

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