2023
DOI: 10.1016/j.diii.2022.10.008
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Radiomics: A review of current applications and possibilities in the assessment of tumor microenvironment

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Cited by 26 publications
(5 citation statements)
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“…Recent evidence supports the plausibility of this hypothesis, given the clinical relevance of these two regions [35][36][37][38][39]. Moreover, traditional radiomics studies often rely on handcrafted radiomic features [40][41][42][43][44], making them susceptible to uncertainties related to robustness and generalization. This susceptibility remains a significant impediment to model deployment.…”
Section: Discussionmentioning
confidence: 94%
“…Recent evidence supports the plausibility of this hypothesis, given the clinical relevance of these two regions [35][36][37][38][39]. Moreover, traditional radiomics studies often rely on handcrafted radiomic features [40][41][42][43][44], making them susceptible to uncertainties related to robustness and generalization. This susceptibility remains a significant impediment to model deployment.…”
Section: Discussionmentioning
confidence: 94%
“…However, the quantitative information that may be extracted from associated CT data has not been exploited so far in the field of FL. Yet, CT TA is now considered as a new technique that allows a quantitative assessment of tumor heterogeneity, and many studies have recently shown its ability to predict PFS and OS in several types of cancer, as well as response to treatment [ 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 35 ].…”
Section: Discussionmentioning
confidence: 99%
“…CT texture analysis (TA) is a relatively recently emerging technique for quantifying tumor heterogeneity based on an analysis of the distribution and relationship of pixel gray levels in the image [ 21 , 22 ]. CT TA can provide information regarding survival and response to treatment for many solid cancer types, such as colorectal [ 23 ], melanoma [ 24 , 25 ], esophageal [ 26 ], head and neck [ 27 ], non-small-cell lung [ 28 , 29 ], cerebral [ 30 ], or hepatocellular carcinoma [ 31 , 32 ]. However, data regarding hematological malignancies are scarce.…”
Section: Introductionmentioning
confidence: 99%
“…Radiomics uses advanced data analysis techniques to assess biological indicators of breast cancer non-invasively before surgery ( 13 ), it offers significant potential in distinguishing between benign and malignant breast lesions, categorizing and grading breast cancer, and forecasting treatment response and risk of recurrence ( 14 , 15 ), it also has major potential in evaluating the tumor microenvironment ( 16 ). Most current radiomics research to predict high Ki-67 expression relies on single-mode imaging or Magnetic Resonance Imaging (MRI).…”
Section: Introductionmentioning
confidence: 99%