Development and external validation of a multiparametric MRI-based radiomics model for preoperative prediction of microsatellite instability status in rectal cancer: a retrospective multicenter study

Li, Zhi; Zhang, Jing; Zhong, Qian; Zhan, Feng; Shi, Yushu; Xu, Liang; Zhang, Rui; Yu, Fang; Lv, Biao; Tian, Yang; Huang, Chencui; Cui, Feng; Chen, Feng

doi:10.1007/s00330-022-09160-0

Cited by 15 publications

(24 citation statements)

References 28 publications

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“…The initial search yielded 97 records from the four public databases. After the removal of 48 duplicates, 37 ineligible studies, 12 studies were finally included in this systematic review [27][28][29][30][31][32][33][34][35][36][37][38]. Among them, 10 studies with available data were able to construct a 2 × 2 contingency table [27-31, 33-35, 37, 38].…”

Section: Resultsmentioning

confidence: 99%

“…A total of 4,320 patients were included, with a sample size ranging from 90 to 837 (median 238) and a male/female ratio of 1.5 (2,592/1,728). Four studies were performed as multicenter research, with a sample size in the external cohorts ranging from 61 to 441 (median 82) [30,35,37,38]. Five studies exclusively focused on rectal cancer, while the others on CRC [29,32,[36][37][38].…”

Section: General Characteristics and The Incidence Of Msimentioning

confidence: 99%

“…Four studies were performed as multicenter research, with a sample size in the external cohorts ranging from 61 to 441 (median 82) [30,35,37,38]. Five studies exclusively focused on rectal cancer, while the others on CRC [29,32,[36][37][38].…”

Section: General Characteristics and The Incidence Of Msimentioning

confidence: 99%

“…The incidence of MSI ranged from 8 to 34% (median: 19%). Among nine studies with available data, a majority of studies (8/9) reported an interval between imaging examination and surgery of less than 2 weeks [27,29,30,33,34,[36][37][38]. Table 1 provides detailed information about the basic characteristics of the included studies.…”

Section: General Characteristics and The Incidence Of Msimentioning

confidence: 99%

“…(1) Imaging acquisition and tumor segmentation Among the included studies, seven used CT imaging, four MRI [29,32,37,38], and one PET/CT [33]. Six studies applied images from one phase/sequence [27][28][29][34][35][36]; the most frequently used phase was the portal venous phase of CT imaging (7/12) [27,28,30,31,[34][35][36].…”

Section: Study Characteristicsmentioning

confidence: 99%

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Systematic review of machine learning-based radiomics approach for predicting microsatellite instability status in colorectal cancer

Wang

Xu²,

Wang

et al. 2023

Radiol med

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This study aimed to systematically summarize the performance of the machine learning-based radiomics models in the prediction of microsatellite instability (MSI) in patients with colorectal cancer (CRC). It was conducted according to the preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA) guideline and was registered at the PROSPERO website with an identifier CRD42022295787. Systematic literature searching was conducted in databases of PubMed, Embase, Web of Science, and Cochrane Library up to November 10, 2022. Research which applied radiomics analysis on preoperative CT/MRI/PET-CT images for predicting the MSI status in CRC patients with no history of anti-tumor therapies was eligible. The radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) were applied to evaluate the research quality (full score 100%). Twelve studies with 4,320 patients were included. All studies were retrospective, and only four had an external validation cohort. The median incidence of MSI was 19% (range 8–34%). The area under the receiver operator curve of the models ranged from 0.78 to 0.96 (median 0.83) in the external validation cohort. The median sensitivity was 0.76 (range 0.32–1.00), and the median specificity was 0.87 (range 0.69–1.00). The median RQS score was 38% (range 14–50%), and half of the studies showed high risk in patient selection as evaluated by QUADAS-2. In conclusion, while radiomics based on pretreatment imaging modalities had a high performance in the prediction of MSI status in CRC, so far it does not appear to be ready for clinical use due to insufficient methodological quality.

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