Prediction of microsatellite instability in colorectal cancer based on MRI-ADC and clinicopathological features

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WEI Zhaokun KANG Yujie PENG Leping ZHANG Xiuling ZHANG Xu MA Xiaomei JIA Yingmei XIONG Shengyuan WANG Lili

Cite this article as: WEI Z K, KANG Y J, PENG L P, et al. Prediction of microsatellite instability in colorectal cancer based on MRI-ADC and clinicopathological features[J]. Chin J Magn Reson Imaging, 2025, 16(1): 48-53, 88. DOI:10.12015/issn.1674-8034.2025.01.008.

Abstract

[Abstract] Objective To investigate the application value of MRI apparent diffusion coefficient (ADC) combined with clinicopathological characteristics in predicting microsatellite instability (MSI) of colorectal cancer.Materials and Methods The clinicopathologic data of 144 patients with colorectal cancer confirmed by pathology were analyzed retrospectively. All patients underwent abdominal or pelvic MRI examination before surgery. According to immunohistochemistry (IHC) results, patients were divided into MSI group and microsatellite stability (MSS) group. The MSI group included cases with high frequency MSI (MSI-H) and low frequency MSI (MSI-L). SPSS software was used to compare the clinical baseline data of patients, and binary logistic regression was used to analyze MSI risk factors for colorectal cancer. Multivariate regression independent predictors were included to construct a nomogram model. Receiver operating characteristic (ROC) was used to evaluate the diagnostic efficacy of ADC model and ADC-clinicopathological combined model, and the area under the curve (AUC) was calculated. DeLong test was used to compare the model differences. Calibration curves were used to evaluate the predictive accuracy of the model, and decision and impact curves were used to evaluate the clinical utility of the predictive model.Results One hundred and forty-four patients with colorectal cancer were included, including 16 patients in MSI group and 128 patients in MSS group. ADC value (1.107 ± 0.335) × 10^-3 mm²/s in MSI group was higher than that in MSS group (0.868 ± 0.262) × 10^-3 mm²/s, P = 0.011. Among the collected clinicpathological features, the history of chronic gastroenteritis (P < 0.001), D2-40 (P = 0.009), clinical stage (P < 0.001), showed statistically significant differences between the MSI group and the MSS group. The above four independent predictors were combined to form a nomogram. Among the ADC model and the ADC-clinicopathologic feature combined model, the ADC-clinicopathologic feature combined model predicted the MSI performance of colorectal cancer better. The AUC was 0.901 [95% (confidence interval, CI): 0.783 to 1.000], and the sensitivity and specificity were 87.5% and 93.0%, respectively.Conclusions This study shows that the ADC model and the ADC-clinicopathological features combined model have good predictive performance for MSI status of colorectal cancer, and the ADC-clinicopathological features combined model has the best performance. This study can provide a safe and non-invasive method for predicting MSI of colorectal cancer before clinical operation.

[Keywords] colorectal cancer；microsatellite instability；clinicopathological features；apparent diffusion coefficient；magnetic resonance imaging

Contributor Information

WEI Zhaokun¹ KANG Yujie² PENG Leping¹ ZHANG Xiuling¹ ZHANG Xu³ MA Xiaomei¹ JIA Yingmei¹ XIONG Shengyuan¹ WANG Lili^1*

¹ Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China

² Department of Radiology, Gansu Cancer Hospital, Lanzhou 730000, China

³ Endoscopic Diagnosis and Treatment Center, Gansu Provincial Hospital, Lanzhou 730000, China

Corresponding author: WANG L L, E-mail: wanglilihq@163.com

Conflicts of interest None.

Publication Information

Received 2024-04-15

Accepted 2025-01-10

DOI: 10.12015/issn.1674-8034.2025.01.008

Text

References

[1]

GÜLŞEN T, ERGENÇ M, ŞENOL Z, et al. Clinicopathological outcomes of microsatellite instability in colorectal cancer[J]. J Cancer Res Ther, 2024, 20(1): 103-111. DOI: 10.4103/jcrt.jcrt_1560_22.

[2]

BAIDOUN F, SAAD A M, ABDEL-RAHMAN O. Prognostic and predictive value of microsatellite instability status among patients with colorectal cancer[J]. J Comp Eff Res, 2021, 10(16): 1197-1214. DOI: 10.2217/cer-2021-0013.

[3]

KAWAKAMI H, ZAANAN A, SINICROPE F A. Microsatellite instability testing and its role in the management of colorectal cancer[J/OL]. Curr Treat Options Oncol, 2015, 16(7): 30 [2024-04-03]. https://pubmed.ncbi.nlm.nih.gov/26031544/. DOI: 10.1007/s11864-015-0348-2.

[4]

DE SMEDT L, LEMAHIEU J, PALMANS S, et al. Microsatellite instable vs stable colon carcinomas: analysis of tumour heterogeneity, inflammation and angiogenesis[J]. Br J Cancer, 2015, 113(3): 500-509. DOI: 10.1038/bjc.2015.213.

[5]

LI J J, XU Q, LUO C, et al. Clinicopathologic characteristics of resectable colorectal cancer with mismatch repair protein defects in Chinese population: Retrospective case series and literature review[J/OL]. Medicine, 2020, 99(24): e20554 [2024-04-25]. https://pubmed.ncbi.nlm.nih.gov/32541478/. DOI: 10.1097/MD.0000000000020554.

[6]

CERCEK A, DOS SANTOS FERNANDES G, ROXBURGH C S, et al. Mismatch repair-deficient rectal cancer and resistance to neoadjuvant chemotherapy[J]. Clin Cancer Res, 2020, 26(13): 3271-3279. DOI: 10.1158/1078-0432.CCR-19-3728.

[7]

MEI W J, MI M, QIAN J, et al. Clinicopathological characteristics of high microsatellite instability/mismatch repair-deficient colorectal cancer: A narrative review[J/OL]. Front Immunol, 2022, 13: 1019582 [2024-04-25]. https://pubmed.ncbi.nlm.nih.gov/36618386/. DOI: 10.3389/fimmu.2022.1019582.

[8]

DENG K, CHEN X D. Progress in imaging research on microsatellite instability of colorectal cancer[J]. Int J Med Radiol, 2024, 47(1): 74-78. DOI: 10.19300/j.2024.Z20758.

[9]

LI Z B, DAI H, LIU Y X, et al. Radiomics analysis of multi-sequence MR images for predicting microsatellite instability status preoperatively in rectal cancer[J/OL]. Front Oncol, 2021, 11: 697497 [2024-04-25]. https://pubmed.ncbi.nlm.nih.gov/34307164/. DOI: 10.3389/fonc.2021.697497.

[10]

KIM S, LEE J H, PARK E J, et al. Prediction of microsatellite instability in colorectal cancer using a machine learning model based on PET/CT radiomics[J]. Yonsei Med J, 2023, 64(5): 320-326. DOI: 10.3349/ymj.2022.0548.

[11]

SONG J L, LI Z W, YANG L J, et al. Metabolic activity via 18F-FDG PET/CT is predictive of microsatellite instability status in colorectal cancer[J/OL]. BMC Cancer, 2022, 22(1): 808 [2024-04-25]. https://pubmed.ncbi.nlm.nih.gov/35869469/. DOI: 10.1186/s12885-022-09871-z.

[12]

BIAN X L, SUN Q, WANG M, et al. Preoperative prediction of microsatellite instability status in colorectal cancer based on a Multiphasic enhanced CT radiomics nomogram model[J/OL]. BMC Med Imaging, 2024, 24(1): 77 [2024-04-28]. https://pubmed.ncbi.nlm.nih.gov/38566000/. DOI: 10.1186/s12880-024-01252-1.

[13]

WU J J, LIU A L, ZHAO Y, et al. Texture analysis of iodine-based material decomposition images with spectral CT imaging for predicting microsatellite instability status in colorectal cancer[J]. Chin J Med Imag Technol, 2019, 35(11): 1683-1688. DOI: 10.13929/j.1003-3289.201905067.

[14]

MA C J, TIAN S F, CHEN L H, et al. Quantitative assessment of microsatellite instability in endometrial cancer by T2 mapping combined with mDixon-Quant multiparameter imaging[J]. Chin J Magn Reson Imag, 2022, 13(8): 48-54. DOI: 10.12015/issn.1674-8034.2022.08.009.

[15]

REN J P, ZHANG M, LIU W Y, et al. Assessing microsatellite instability of endometrial adenocarcinoma with multimodal intravoxel incoherentmotion MRI[J]. Int J Med Radiol, 2023, 46(4): 396-401. DOI: 10.19300/j.2023.L20205.

[16]

MA W T, ZHU Y H, WEI Z K, et al. Dynamic contrast enhanced-MRI and diffusion weighted imaging parameters for predicting microsatellite instability of colorectal cancer[J]. Chin J Med Imag Technol, 2023, 39(10): 1526-1530. DOI: 10.13929/j.issn.1003-3289.2023.10.017.

[17]

MENG X, TIAN S F, ZHANG Q H, et al. Improved differentiation between stage I-II endometrial carcinoma and endometrial polyp with combination of APTw and IVIM MR imaging[J]. Magn Reson Imag, 2023, 102: 43-48. DOI: 10.1016/j.mri.2023.04.001.

[18]

WANG L L, LEI J K, LI S H, et al. Microsatellite instability of rectal cancer based on magnetic resonance diffusion kurtosis imaging[J]. Chin J Magn Reson Imag, 2023, 14(8): 73-78. DOI: 10.12015/issn.1674-8034.2023.08.012.

[19]

ZHANG W, YIN H K, HUANG Z X, et al. Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer[J]. Cancer Med, 2021, 10(12): 4164-4173. DOI: 10.1002/cam4.3957.

[20]

LEFEBVRE T L, UENO Y, DOHAN A, et al. Development and validation of multiparametric MRI-based radiomics models for preoperative risk stratification of endometrial cancer[J]. Radiology, 2022, 305(2): 375-386. DOI: 10.1148/radiol.212873.

[21]

LAN Y, LIU F, GE J, et al. Consistency analysis of MMR protein expression and MSI in colorectal cancer[J]. Chin J Clin Exp Pathol, 2022, 38(9): 1120-1122. DOI: 10.13315/j.cnki.cjcep.2022.09.021.

[22]

RASHTAK S, RUAN X Y, DRULINER B R, et al. Peripheral neutrophil to lymphocyte ratio improves prognostication in colon cancer[J/OL]. Clin Colorectal Cancer, 2017, 16(2): 115-123.e3 [2024-04-03]. https://pubmed.ncbi.nlm.nih.gov/28365393/. DOI: 10.1016/j.clcc.2017.01.008.

[23]

GALON J, COSTES A, SANCHEZ-CABO F, et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome[J]. Science, 2006, 313(5795): 1960-1964. DOI: 10.1126/science.1129139.

[24]

KOREHISA S, IKEDA T, OKANO S, et al. A novel histological examination with dynamic three-dimensional reconstruction from multiple immunohistochemically stained sections of a PD-L1-positive colon cancer[J]. Histopathology, 2018, 72(4): 697-703. DOI: 10.1111/his.13400.

[25]

BAUER K, MICHEL S, REUSCHENBACH M, et al. Dendritic cell and macrophage infiltration in microsatellite-unstable and microsatellite-stable colorectal cancer[J]. Fam Cancer, 2011, 10(3): 557-565. DOI: 10.1007/s10689-011-9449-7.

[26]

ZHOU T. Effect of ki-67 and microsatellite instability on prognosis in stage ⅡandⅢRectal cancer[J]. J Med Inf, 2021, 34(23): 66-68. DOI: 10.3969/j.issn.1006-1959.2021.23.018.

[27]

TURNER K M, DELMAN A M, WIMA K, et al. Microsatellite instability is associated with worse overall survival in resectable colorectal liver metastases[J]. Am J Surg, 2023, 225(2): 322-327. DOI: 10.1016/j.amjsurg.2022.08.007.

[28]

TAIEB J, SVRCEK M, COHEN R, et al. Deficient mismatch repair/microsatellite unstable colorectal cancer: Diagnosis, prognosis and treatment[J]. Eur J Cancer, 2022, 175: 136-157. DOI: 10.1016/j.ejca.2022.07.020.

[29]

PIETRANTONIO F, LONARDI S, CORTI F, et al. Nomogram to predict the outcomes of patients with microsatellite instability-high metastatic colorectal cancer receiving immune checkpoint inhibitors[J/OL]. J Immunother Cancer, 2021, 9(8): e003370 [2024-04-03]. https://pubmed.ncbi.nlm.nih.gov/34429334/. DOI: 10.1136/jitc-2021-003370.

[30]

HU H B, KANG L, ZHANG J W, et al. Neoadjuvant PD-1 blockade with toripalimab, with or without celecoxib, in mismatch repair-deficient or microsatellite instability-high, locally advanced, colorectal cancer (PICC): a single-centre, parallel-group, non-comparative, randomised, phase 2 trial[J]. Lancet Gastroenterol Hepatol, 2022, 7(1): 38-48. DOI: 10.1016/S2468-1253(21)00348-4.

[31]

OOKI A, SHINOZAKI E, YAMAGUCHI K. Immunotherapy in colorectal cancer: current and future strategies[J]. J Anus Rectum Colon, 2021, 5(1): 11-24. DOI: 10.23922/jarc.2020-064.

[32]

MANZ S M, LOSA M, FRITSCH R, et al. Efficacy and side effects of immune checkpoint inhibitors in the treatment of colorectal cancer[J/OL]. Therap Adv Gastroenterol, 2021, 14: 17562848211002018 [2024-04-22]. https://pubmed.ncbi.nlm.nih.gov/33948110/. DOI: 10.1177/17562848211002018.

[33]

MANZOOR S, SABER-AYAD M, MAGHAZACHI A A, et al. MLH1 mediates cytoprotective nucleophagy to resist 5-Fluorouracil-induced cell death in colorectal carcinoma[J]. Neoplasia, 2022, 24(2): 76-85. DOI: 10.1016/j.neo.2021.12.003.

[34]

OVERMAN M J, MCDERMOTT R, LEACH J L, et al. Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre, phase 2 study[J]. Lancet Oncol, 2017, 18(9): 1182-1191. DOI: 10.1016/S1470-2045(17)30422-9.

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