Gastrointestinal stromal tumors (GIST): a proposal of a “CT-based predictive model of Miettinen index” in predicting the risk of malignancy

Mazzei, Maria Antonietta; Squitieri, Nevada Cioffi; Vindigni, Carla; Guerrini, Susanna; Gentili, Francesco; Sadotti, Giulia; Mercuri, Paola; Righi, Lorenzo; Lucii, Gabriele; Mazzei, Francesco Giuseppe; Marrelli, Daniele; Volterrani, Luca

doi:10.1007/s00261-019-02209-7

Cited by 44 publications

(38 citation statements)

References 35 publications

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“…Some works successfully investigated the feasibility of CT in predicting histopathological response of GC after NAC, by measuring tumor volume and maximum diameter reduction rate (35,36), despite visual assessment may be affected by a large inter and intraobserver variability and reduction of tumor volume is not always correlated with response to therapy. Also advanced imaging modalities, such as dual energy CT (DECT) and CT perfusion were investigated in predicting histopathological response of AGC after NAC (37-39), however, CT perfusion is still affected by some important issues (40,41), in particular regarding the reproducibility and the possibility to compare its results with different proprietary softwares (42,43) whereas DECT is affected by the fact that not all neoplastic lesions are hypervascular and that the reduction of vascularization after chemotherapy is not always strictly related to tumor response (44)(45)(46). In this sense TA, analyzing the distribution of pixels or voxels gray level in digital images, makes possible to extrapolate mathematical parameters (texture features) which reflect the underlying structure of the objects showed in the image (21)(22)(23).…”

Section: Discussionmentioning

confidence: 99%

Delta-radiomics and response to neoadjuvant treatment in locally advanced gastric cancer—a multicenter study of GIRCG (Italian Research Group for Gastric Cancer)

Mazzei¹,

Giacomo²,

Bagnacci³

et al. 2021

Quant Imaging Med Surg

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Background: To predict response to neoadjuvant chemotherapy (NAC) of gastric cancer (GC), prior to surgery, would be pivotal to customize patient treatment. The aim of this study is to investigate the reliability of computed tomography (CT) texture analysis (TA) in predicting the histo-pathological response to NAC in patients with resectable locally advanced gastric cancer (AGC).Methods: Seventy (40 male, mean age 63.3 years) patients with resectable locally AGC, treated with NAC and radical surgery, were included in this retrospective study from 5 centers of the Italian Research Group for Gastric Cancer (GIRCG). Population was divided into two groups: 29 patients from one center (internal cohort for model development and internal validation) and 41 from other four centers (external cohort for independent external validation). Gross tumor volume (GTV) was segmented on each pre-and post-NAC multidetector CT (MDCT) image by using a dedicated software (RayStation), and 14 TA parameters were then extrapolated. Correlation between TA parameters and complete pathological response (tumor regression grade, TRG1), was initially investigated for the internal cohort. The univariate significant variables were tested on the external cohort and multivariate logistic analysis was performed.Results: In multivariate logistic regression the only significant TA variable was delta gray-level cooccurrence matrix (GLCM) contrast (P=0.001, Nagelkerke R 2 : 0.546 for the internal cohort and P=0.014, Nagelkerke R 2 : 0.435 for the external cohort). Receiver operating characteristic (ROC) curves, generated from the logistic regression of all the patients, showed an area under the curve (AUC) of 0.763.Conclusions: Post-NAC GLCM contrast and dissimilarity and delta GLCM contrast TA parameters seem to be reliable for identifying patients with locally AGC responder to NAC.

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Section: Discussionmentioning

confidence: 99%

Delta-radiomics and response to neoadjuvant treatment in locally advanced gastric cancer—a multicenter study of GIRCG (Italian Research Group for Gastric Cancer)

Mazzei¹,

Giacomo²,

Bagnacci³

et al. 2021

Quant Imaging Med Surg

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“…For instance, NCCN expert consensus suggests that possible high‐risk EUS features include irregularity, heterogeneity, echogenic foci, and cystic spaces 16 . Of the studies investigating the usefulness of imaging features on CT or EUS, an association with oncologic outcomes and aggressiveness is only consistently reported for imaging size 21,30,32–34 . Furthermore, these studies do not use real‐world imaging data, but rather retrospective reassessment of images with study specific radiologists, introducing a non‐generalizable reporting bias.…”

Section: Discussionmentioning

confidence: 99%

“…For instance, Chen et al 21 found that size, exophytic growth, and cystic spaces were associated with aggressiveness, while Kim et al 23 found no EUS imaging features useful for risk‐stratifying GISTs between 2 and 5 cm. Similarly, necrosis, margins, ulceration, lymph nodes, irregularity, and heterogeneity have all been variably implicated or exonerated throughout the literature 29–34 . Such reports often use a study‐specific radiologist with retrospective image reassessment, leading to reporting bias, and decrease in real‐world generalizability 21,34 .…”

Section: Introductionmentioning

confidence: 99%

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Preoperative imaging of gastric GISTs underestimates pathologic tumor size: A retrospective, single institution analysis

Apte

Radonjic

Wong

et al. 2021

Journal of Surgical Oncology

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Background How well imaging size agrees with pathologic size of gastric gastrointestinal stromal tumors (GISTs) is unknown. GIST risk stratification is based on pathologic size, location, and mitotic rate. To inform decision making, the size discrepancy between imaging and pathology for gastric GISTs was investigated. Methods Imaging and pathology reports were reviewed for 113 patients. Bland–Altman analyses and intraclass correlation (ICC) assessed agreement of imaging and pathology. Changes in clinical risk category due to size discrepancy were identified. Results Computed tomography (CT) (n = 110) and endoscopic ultrasound (EUS) (n = 50) underestimated pathologic size for gastric GISTs by 0.42 cm, 95% confidence interval (CI): (0.11, 0.73), p = 0.008 and 0.54 cm, 95% CI: (0.25, 0.82), p < 0.001, respectively. ICCs were 0.94 and 0.88 for CT and EUS, respectively. For GISTs ≤ 3 cm, size underestimation was 0.24 cm for CT (n = 28), 95% CI: (0.01, 0.47), p = 0.039 and 0.56 cm for EUS (n = 26), 95% CI: (0.27, 0.84), p < 0.0001. ICCs were 0.72 and 0.55 for CT and EUS, respectively. Spearman's correlation was ≥0.84 for all groups. For GISTs ≤ 3 cm, 6/28 (21.4% p = 0.01) on CT and 7/26 (26.9% p = 0.005) on EUS upgraded risk category using pathologic size versus imaging size. No GISTs ≤ 3 cm downgraded risk categories. Size underestimation persisted for GISTs ≤ 2 cm on EUS (0.39 cm, 95% CI: [0.06, 0.72], p = 0.02, post hoc analysis). Conclusion Imaging, particularly EUS, underestimates gastric GIST size. Caution should be exercised using imaging alone to risk‐stratify gastric GISTs, and to decide between surveillance versus surgery.

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“…Chu et al found that iodine images were helpful in determining the solid or cystic nature of a lesion, improving also the evaluation of relationships between tumor, main pancreatic duct and vessels (42). Considering pancreatic lesions different from PDAC, virtual monoenergetic images and iodine maps may better indicate the complexity of cystic lesions (39,43,44). DECT has been also investigated for the differentiation of serous and mucinous cysts.…”

Section: Pancreasmentioning

confidence: 99%

Dual energy CT in gland tumors: a comprehensive narrative review and differential diagnosis

Gentili¹,

Guerrini²,

Mazzei³

et al. 2020

Gland Surg

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Dual energy CT (DECT)with image acquisition at two different photon X-ray levels allows the characterization of a specific tissue or material/elements, the extrapolation of virtual unenhanced and monoenergetic images, and the quantification of iodine uptake; such special capabilities make the DECT the perfect technique to support oncological imaging for tumor detection and characterization and treatment monitoring, while concurrently reducing the dose of radiation and iodine and improving the metal artifact reduction. Even though its potential in the field of oncology has not been fully explored yet, DECT is already widely used today thanks to the availability of different CT technologies, such as dual-source, singlesource rapid-switching, single-source sequential, single-source twin-beam and dual-layer technologies.Moreover DECT technology represents the future of the imaging innovation and it is subject to ongoing development that increase according its clinical potentiality, in particular in the field of oncology. This review points out recent state-of-the-art in DECT applications in gland tumors, with special focus on its potential uses in the field of oncological imaging of endocrine and exocrine glands.

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Gastrointestinal stromal tumors (GIST): a proposal of a “CT-based predictive model of Miettinen index” in predicting the risk of malignancy

Cited by 44 publications

References 35 publications

Delta-radiomics and response to neoadjuvant treatment in locally advanced gastric cancer—a multicenter study of GIRCG (Italian Research Group for Gastric Cancer)

Delta-radiomics and response to neoadjuvant treatment in locally advanced gastric cancer—a multicenter study of GIRCG (Italian Research Group for Gastric Cancer)

Preoperative imaging of gastric GISTs underestimates pathologic tumor size: A retrospective, single institution analysis

Dual energy CT in gland tumors: a comprehensive narrative review and differential diagnosis

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