Share：
Share this content in WeChat
X
[Chinese][PDF]6433
• Review •
Research progress of CT and MRI with radiomics to predict microsatellite instability in colorectal cancer
PENG Leping  ZHANG Xiuling  SHI Liuyan  HUANG Gang  MA Yaqiong  AI Kai  WANG Lili  MA Wenting  MA Xiaomei 

Cite this article as: PENG L P, ZHANG X L, SHI L Y, et al. Research progress of CT and MRI with radiomics to predict microsatellite instability in colorectal cancer[J]. Chin J Magn Reson Imaging, 2024, 15(6): 218-223. DOI:10.12015/issn.1674-8034.2024.06.035.


[Abstract] Colorectal cancer is a common malignant tumor of the digestive tract with high mortality, and its pathogenesis is closely related to the genetic changes of tumor cells. Microsatellite instability (MSI) is a common genetic change that causes colorectal development and plays a crucial role in the development and progression of tumors and in the treatment and prognosis of patients. In recent years, medical imaging methods with the advantages of non-invasiveness and individualization have begun to make initial progress in evaluating high MSI (MSI-H) status in colorectal cancer. With the continuous optimization of software technology and the rise of artificial intelligence, computed tomography (CT) and MRI with radiomics methods have become increasingly important in the preoperative prediction, treatment, efficacy monitoring, and prognosis assessment of MSI-H status in colorectal cancer. This review aims to summarize the advantages and prospects of CT and MRI techniques and radiomics methods in predicting the MSI-H status of colorectal cancer, to provide more accurate and non-invasive MSI prediction methods for clinical practice, and provide new ideas for the selection of treatment measures for colorectal cancer patients.
[Keywords] colorectal cancer；high microsatellite instability；computed tomography；magnetic resonance imaging；radiomics

PENG Leping1   ZHANG Xiuling1   SHI Liuyan1   HUANG Gang3   MA Yaqiong3   AI Kai2   WANG Lili3*   MA Wenting3   MA Xiaomei3  

1 The First Clinical College of Medicine, Gansu University of Chinese Medicine, Lanzhou 730000,China

2 Philips (China) Investment Co. LTD, Shanghai 200040, China

3 Department of Radiology, Gansu Provincial People's Hospital, Lanzhou 730000,China

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

Conflicts of interest   None.

Received  2024-03-01
Accepted  2024-06-03
DOI: 10.12015/issn.1674-8034.2024.06.035
Cite this article as: PENG L P, ZHANG X L, SHI L Y, et al. Research progress of CT and MRI with radiomics to predict microsatellite instability in colorectal cancer[J]. Chin J Magn Reson Imaging, 2024, 15(6): 218-223. DOI:10.12015/issn.1674-8034.2024.06.035.

[1]
XIA C F, DONG X S, LI H, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants[J]. Chin Med J, 2022, 135(5): 584-590. DOI: 10.1097/CM9.0000000000002108.
[2]
SMEDT L D, 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.
[3]
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.
[4]
ZHANG Y Y, HE K, GUO Y, et al. A novel multimodal radiomics model for preoperative prediction of lymphovascular invasion in rectal cancer[J/OL]. Front Oncol, 2020, 10: 457 [2024-02-18]. https://pubmed.ncbi.nlm.nih.gov/32328460/. DOI: 10.3389/fonc.2020.00457.
[5]
LI M L, ZHANG J, DAN Y B, et al. A clinical-radiomics nomogram for the preoperative prediction of lymph node metastasis in colorectal cancer[J/OL]. J Transl Med, 2020, 18(1): 46[2024-02-18]. https://pubmed.ncbi.nlm.nih.gov/32000813/. DOI: 10.1186/s12967-020-02215-0.
[6]
CUI Y F, LIU H H, REN J L, et al. Development and validation of a MRI-based radiomics signature for prediction of KRAS mutation in rectal cancer[J]. Eur Radiol, 2020, 30(4): 1948-1958. DOI: 10.1007/s00330-019-06572-3.
[7]
PEI Q, YI X P, CHEN C, et al. Pre-treatment CT-based radiomics nomogram for predicting microsatellite instability status in colorectal cancer[J]. Eur Radiol, 2022, 32(1): 714-724. DOI: 10.1007/s00330-021-08167-3.
[8]
SHIN J, SEO N, BAEK S E, et al. MRI radiomics model predicts pathologic complete response of rectal cancer following chemoradiotherapy[J]. Radiology, 2022, 303(2): 351-358. DOI: 10.1148/radiol.211986.
[9]
HUANG H Y, HAN L J, GUO J B, et al. Multiphase and multiparameter MRI-based radiomics for prediction of tumor response to neoadjuvant therapy in locally advanced rectal cancer[J/OL]. Radiat Oncol, 2023, 18(1): 179 [2024-02-18]. https://pubmed.ncbi.nlm.nih.gov/37907928/. DOI: 10.1186/s13014-023-02368-4.
[10]
XIE Z D, ZHANG Q W, WANG X J, et al. Development and validation of a novel radiomics nomogram for prediction of early recurrence in colorectal cancer[J/OL]. Eur J Surg Oncol, 2023, 49(12): 107118 [2024-02-18]. https://pubmed.ncbi.nlm.nih.gov/37844471/. DOI: 10.1016/j.ejso.2023.107118.
[11]
LIANG L, LI X, NONG L, et al. Analysis of microsatellite instability in endometrial cancer: the significance of minimal microsatellite shift[J]. J Peking Univ Health Sci, 2023, 55(2): 254-261. DOI: 10.19723/j.issn.1671-167X.2023.02.008.
[12]
BENSON A B, VENOOK A P, AL-HAWARY M M, et al. Colon cancer, version 2.2021, NCCN clinical practice guidelines in oncology[J]. J Natl Compr Canc Netw, 2021, 19(3): 329-359. DOI: 10.6004/jnccn.2021.0012.
[13]
MI M, WENG S S, XU Z H, et al. CSCO guidelines for colorectal cancer version 2023: Updates and insights[J]. Chin J Cancer Res, 2023, 35(3): 233-238. DOI: 10.21147/j.issn.1000-9604.2023.03.02.
[14]
LATHAM A, SRINIVASAN P, KEMEL Y, et al. Microsatellite instability is associated with the presence of lynch syndrome pan-cancer[J]. J Clin Oncol, 2019, 37(4): 286-295. DOI: 10.1200/JCO.18.00283.
[15]
PELTOMÄKI P, NYSTRÖM M, MECKLIN J P, et al. Lynch syndrome genetics and clinical implications[J]. Gastroenterology, 2023, 164(5): 783-799. DOI: 10.1053/j.gastro.2022.08.058.
[16]
ACHILLI P, CRIPPA J, GRASS F, et al. Survival impact of adjuvant chemotherapy in patients with stage IIA colon cancer: analysis of the National Cancer Database[J]. Int J Cancer, 2021, 148(1): 161-169. DOI: 10.1002/ijc.33203.
[17]
GANESH K, STADLER Z K, CERCEK A, et al. Immunotherapy in colorectal cancer: rationale, challenges and potential[J]. Nat Rev Gastroenterol Hepatol, 2019, 16(6): 361-375. DOI: 10.1038/s41575-019-0126-x.
[18]
LI J X, HU H B, QIN G, et al. Biomarkers of pathologic complete response to neoadjuvant immunotherapy in mismatch repair-deficient colorectal cancer[J]. Clin Cancer Res, 2024, 30(2): 368-378. DOI: 10.1158/1078-0432.CCR-23-2213.
[19]
INCHINGOLO R, MAINO C, CANNELLA R, et al. Radiomics in colorectal cancer patients[J]. World J Gastroenterol, 2023, 29(19): 2888-2904. DOI: 10.3748/wjg.v29.i19.2888.
[20]
WU J J, LV Y, WANG N, et al. The value of single-source dual-energy CT imaging for discriminating microsatellite instability from microsatellite stability human colorectal cancer[J]. Eur Radiol, 2019, 29(7): 3782-3790. DOI: 10.1007/s00330-019-06144-5.
[21]
PFUDERER P L, BALLHAUSEN A, SEIDLER F, et al. High endothelial venules are associated with microsatellite instability, hereditary background and immune evasion in colorectal cancer[J]. Br J Cancer, 2019, 121(5): 395-404. DOI: 10.1038/s41416-019-0514-6.
[22]
WANG H H, ZHAO K, XU Z Y, et al. The value of contrast-enhanced CT in assessing microsatellite instability with colorectal cancer[J]. Oncoradiology, 2022, 31(2): 121-129. DOI: 10.19732/j.cnki.2096-6210.2022.02.004.
[23]
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.
[24]
CHEN S, DU W Z, CAO Y H, et al. Preoperative contrast-enhanced CT imaging and clinicopathological characteristics analysis of mismatch repair-deficient colorectal cancer[J/OL]. Cancer Imaging, 2023, 23(1): 97 [2024-02-19]. https://pubmed.ncbi.nlm.nih.gov/37828626/. DOI: 10.1186/s40644-023-00591-6.
[25]
CAO Y T, ZHANG G J, ZHANG J, et al. Predicting microsatellite instability status in colorectal cancer based on triphasic enhanced computed tomography radiomics signatures: a multicenter study[J/OL]. Front Oncol, 2021, 11: 687771 [2024-02-19]. https://pubmed.ncbi.nlm.nih.gov/34178682/. DOI: 10.3389/fonc.2021.687771.
[26]
MA Y, LIN C S, LIU S, et al. Radiomics features based on internal and marginal areas of the tumor for the preoperative prediction of microsatellite instability status in colorectal cancer[J/OL]. Front Oncol, 2022, 12: 1020349 [2024-02-19]. https://pubmed.ncbi.nlm.nih.gov/36276101/. DOI: 10.3389/fonc.2022.1020349.
[27]
ZHAO Y, FU X, LOPEZ J I, et al. Selection of metastasis competent subclones in the tumour interior[J]. Nat Ecol Evol, 2021, 5(7): 1033-1045. DOI: 10.1038/s41559-021-01456-6.
[28]
GOLIA PERNICKA J S, GAGNIERE J, CHAKRABORTY J, et al. Radiomics-based prediction of microsatellite instability in colorectal cancer at initial computed tomography evaluation[J]. Abdom Radiol, 2019, 44(11): 3755-3763. DOI: 10.1007/s00261-019-02117-w.
[29]
YING M L, PAN J F, LU G H, et al. Development and validation of a radiomics-based nomogram for the preoperative prediction of microsatellite instability in colorectal cancer[J/OL]. BMC Cancer, 2022, 22(1): 524 [2024-02-19]. https://pubmed.ncbi.nlm.nih.gov/35534797/. DOI: 10.1186/s12885-022-09584-3.
[30]
LI Z, ZHONG Q, ZHANG L, et al. Computed tomography-based radiomics model to preoperatively predict microsatellite instability status in colorectal cancer: a multicenter study[J/OL]. Front Oncol, 2021, 11: 666786 [2024-02-19]. https://pubmed.ncbi.nlm.nih.gov/34277413/. DOI: 10.3389/fonc.2021.666786.
[31]
YUAN H, PENG Y, XU X R, et al. A tumoral and peritumoral CT-based radiomics and machine learning approach to predict the microsatellite instability of rectal carcinoma[J]. Cancer Manag Res, 2022, 14: 2409-2418. DOI: 10.2147/CMAR.S377138.
[32]
WU J J, ZHANG Q H, ZHAO Y, et al. Radiomics analysis of iodine-based material decomposition images with dual-energy computed tomography imaging for preoperatively predicting microsatellite instability status in colorectal cancer[J/OL]. Front Oncol, 2019, 9: 1250 [2024-02-19].https://pubmed.ncbi.nlm.nih.gov/31824843/. DOI: 10.3389/fonc.2019.01250.
[33]
CHEN X B, HE L, LI Q S, et al. Non-invasive prediction of microsatellite instability in colorectal cancer by a genetic algorithm-enhanced artificial neural network-based CT radiomics signature[J]. Eur Radiol, 2023, 33(1): 11-22. DOI: 10.1007/s00330-022-08954-6.
[34]
WANG Y, MA L Y, GUO H F, et al. Efficiency of CT radiomics model in assessing the microsatellite instability of colorectal cancer liver metastasis[J/OL]. Curr Med Imaging, 2023 [2024-02-19]. https://pubmed.ncbi.nlm.nih.gov/37622558/. DOI: 10.2174/1573405620666230825113524.
[35]
HEIMBACH J K, KULIK L M, FINN R S, et al. AASLD guidelines for the treatment of hepatocellular carcinoma[J]. Hepatology, 2018, 67(1): 358-380. DOI: 10.1002/hep.29086.
[36]
FENG Q, YU H, SUN S H, et al. The value of diffusion kurtosis imaging in assessing mismatch repair gene expression of rectal carcinoma: preliminary findings[J/OL]. PLoS One, 2019, 14(2): e0211461 [2024-02-19]. https://pubmed.ncbi.nlm.nih.gov/30716105/. DOI: 10.1371/journal.pone.0211461.
[37]
TANG C, LU G X, XU J M, et al. Diffusion kurtosis imaging and MRI-detected extramural venous invasion in rectal cancer: correlation with clinicopathological prognostic factors[J]. Abdom Radiol, 2023, 48(3): 844-854. DOI: 10.1007/s00261-022-03782-0.
[38]
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.
[39]
BAGHERI M, GHORBANI F, AKBARI-LALIMI H, et al. Histopathological graded liver lesions: what role does the IVIM analysis method have?[J]. MAGMA, 2023, 36(4): 565-575. DOI: 10.1007/s10334-022-01060-0.
[40]
YAN C, LIU S, PAN X, et al. Role of intravoxel incoherent motion MRI in preoperative evaluation of DNA mismatch repair status in rectal cancers[J/OL]. Clin Radiol, 2019, 74(10): 814.e21-e28 [2024-02-19]. https://pubmed.ncbi.nlm.nih.gov/31427042/. DOI: 10.1016/j.crad.2019.07.004.
[41]
XU Q Y, XU Y Y, WANG J, et al. Distinguishing mesorectal tumor deposits from metastatic lymph nodes by using diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging in rectal cancer[J]. Eur Radiol, 2023, 33(6): 4127-4137. DOI: 10.1007/s00330-022-09328-8.
[42]
KIM H R, KIM S H, NAM K H. Association between dynamic contrast-enhanced MRI parameters and prognostic factors in patients with primary rectal cancer[J]. Curr Oncol, 2023, 30(2): 2543-2554. DOI: 10.3390/curroncol30020194.
[43]
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.
[44]
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 [2024-02-20]. https://pubmed.ncbi.nlm.nih.gov/34307164/. DOI: 10.3389/fonc.2021.697497.
[45]
XIANG S, ZHENG L B, ZHU L, et al. Radiomics-based prediction of microsatellite instability in stage Ⅱ and Ⅲ rectal cancer patients based on T2WI MRI and diffusion-weighted imaging[J]. Chin J Surg, 2023, 61(9): 782-787. DOI: 10.3760/cma.j.cn112139-20230315-00106.
[46]
LI Z, ZHANG J, ZHONG Q, et al. 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[J]. Eur Radiol, 2023, 33(3): 1835-1843. DOI: 10.1007/s00330-022-09160-0.
[47]
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.
[48]
ZHANG W, HUANG Z X, ZHAO J, et al. Development and validation of magnetic resonance imaging-based radiomics models for preoperative prediction of microsatellite instability in rectal cancer[J/OL]. Ann Transl Med, 2021, 9(2): 134 [2024-02-20]. https://pubmed.ncbi.nlm.nih.gov/33569436/. DOI: 10.21037/atm-20-7673.
[49]
JIN J, WANG H, CHEN Y L. Predictive value of multimodal magnetic resonance imaging based radiomics model for micro-satellite instability of rectal cancer[J]. Chin J Dig Surg, 2023, 22(6): 779-787. DOI: 10.3760/cma.j.cn115610-20230509-00201.
[50]
ZHANG Y, LIU J, WU C Y, et al. Preoperative prediction of microsatellite instability in rectal cancer using five machine learning algorithms based on multiparametric MRI radiomics[J/OL]. Diagnostics, 2023, 13(2): 269 [2024-02-20]. https://pubmed.ncbi.nlm.nih.gov/36673079/. DOI: 10.3390/diagnostics13020269.

PREV Advances in application of four dimensional flow MRI in liver diseases
NEXT Research Progress of ultra-high-field magnetic resonance imaging in musculoskeletal system
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn