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Clinical Article
Microsatellite instability of rectal cancer based on magnetic resonance diffusion kurtosis imaging
WANG Lili  LEI Jiankai  LI Shenghu  CUI Yaqiong  WEI Zhaokun  SONG Xuhui  MA Jun  LI Daming  MA Xiaomei  JIA Yingmei  HUANG Gang 

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 Imaging, 2023, 14(8): 73-78. DOI:10.12015/issn.1674-8034.2023.08.012.

[Abstract] Objective To investigate the correlation between the microsatellite instability (MSI) status and each parameter of diffusion kurtosis image (DKI) in rectal cancer, and to provide imaging detection indicators for evaluating the MSI status before and after rectal cancer treatment.Materials and Methods Eighty eight patients with a pathologically definite diagnosis of rectal cancer were included for analysis. All patients underwent MRI examination within one week before radical resection of rectal cancer surgery. The examination sequence contained DKI imaging. The obtained data were imported into the dedicated software to acquire DKI parameters such as mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusion (MD), axial diffusion (Da), radial diffusion (Dr), fractional anisotropy (FA), and postoperative pathobiological characteristics. These parameters were used for statistical analysis. Intra-class correlation coefficient was used to evaluate the measurement consistency between two observers. The Kolmogorov-Smirnov test was to assess the normal distribution of DKI parameters. Spearman correlation coefficient was employed to examine the correlation between each quantitative parameter of DKI and MSI and microsatellite stability (MSS). Spearman correlation coefficient was used to compare the correlation between each quantitative parameter of DKI and MSI and MSS. The ROC curve analysis was performed to analyze each parameter of DKI associated with the presence of MSI to observe its value in predicting MSI. The DeLong test was utilized to compare the statistical differences in the AUC of each parameter. P values less than 0.05 were considered statistically significant.Results The correlation coefficient values between MSI and the DKI parameters were as follows: 0.258 (95% CI: 0.122-0.386) for Da, 0.346 (95% CI: 0.191-0.476) for Dr, -0.276 (95% CI: -0.421--0.118) for Ka, and -0.260 (95% CI: -0.383--0.139) for MK. There was indeed a weak positive correlation observed between MSI and Da as well as Dr, while a weak negative correlation was found between Ka and MK. However, no significant correlation was observed between MSI and MD, FA, or Kr (P>0.05). The AUC values for Da, Dr, Ka, and MK in diagnosing MSI in rectal cancer were 0.759 (95% CI: 0.654-0.865), 0.847 (95% CI: 0.749-0.945), 0.777 (95% CI: 0.651-0.902), and 0.758 (95% CI: 0.665-0.856), respectively. The corresponding cut-off values were 0.65, 0.68, 0.55, and 0.70.Conclusions There is a correlation between MSI status and DKI parameters in rectal cancer, and they have some predictive value for it. This correlation is expected to make DKI parameters an optional method for predicting MSI status.
[Keywords] rectal cancer;microsatellite instability;magnetic resonance imaging;diffusion kurtosis imaging

WANG Lili1   LEI Jiankai2   LI Shenghu3   CUI Yaqiong1   WEI Zhaokun1   SONG Xuhui1   MA Jun1   LI Daming1   MA Xiaomei1   JIA Yingmei1   HUANG Gang1*  

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

2 Department of Radiology, Gaotai Traditional Chinese Medicine Hospital, Zhangye 734300, China

3 Department of Radiology, Wuxi Traditional Chinese Medicine Hospital, Wuxi 214000, China

Corresponding author: Huang G, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS Gansu Province Youth Fund Program Project (No. 20JR5RA143); Internal Fund of Gansu Provincial People's Hospital (No. 20GSSY4-45).
Received  2023-02-24
Accepted  2023-07-21
DOI: 10.12015/issn.1674-8034.2023.08.012
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 Imaging, 2023, 14(8): 73-78. DOI:10.12015/issn.1674-8034.2023.08.012.

China Anti-Cancer Association, China Anti-Cancer Association Colorectal Cancer Professional Committee. CACA guidelines for holistic integrative management of cancer-Rectal cancer[J/OL]. Chin J Colorectal Dis Electron Ed, 2022, 11(2):89-103 [2023-01-10]. DOI: 10.3877/cma.j.issn.2095-3224.2022.02.001.
BENSON A B, VENOOK A P, AL-HAWARY M M, et al. Rectal cancer, version 2.2022, NCCN clinical practice guidelines in oncology[J]. J Natl Compr Canc Netw, 2022, 20(10): 1139-1167. DOI: 10.6004/jnccn.2022.0051.
CHEN G. Current situation and progress of immunotherapy for colorectal cancer[J]. J Precis Med, 2019, 34(1): 1-5. DOI: 10.13362/j.jpmed.201901001.
ZHANG X, WU T, CAI X Y, et al. Neoadjuvant immunotherapy for MSI-H/dMMR locally advanced colorectal cancer: new strategies and unveiled opportunities[J/OL]. Front Immunol, 2022, 13: 795972 [2023-01-10]. DOI: 10.3389/fimmu.2022.795972.
BANDO H, TSUKADA Y, INAMORI K, et al. Preoperative chemoradiotherapy plus nivolumab before surgery in patients with microsatellite stable and microsatellite instability-high locally advanced rectal cancer[J]. Clin Cancer Res, 2022, 28(6): 1136-1146. DOI: 10.1158/1078-0432.CCR-21-3213.
SWETS M, GRAHAM MARTINEZ C, VAN VLIET S, et al. Microsatellite instability in rectal cancer: what does it mean? A study of two randomized trials and a systematic review of the literature[J]. Histopathology, 2022, 81(3): 352-362. DOI: 10.1111/his.14710.
MATSUBAYASHI H, OISHI T, SASAKI K, et al. Discordance of microsatellite instability and mismatch repair immunochemistry occurs depending on the cancer type[J]. Hum Pathol, 2023, 135: 54-64. DOI: 10.1016/j.humpath.2022.12.016.
MAHMOUD N N. Colorectal cancer: preoperative evaluation and staging[J]. Surg Oncol Clin N Am, 2022, 31(2): 127-141. DOI: 10.1016/j.soc.2021.12.001.
ZHANG Y, ZHANG F, ZHAO L D, et al. Long-term survival of a patient with microsatellite-stable refractory colorectal cancer with regorafenib and PD-1 inhibitor sintilimab: a case report and review of literature[J/OL]. BMC Gastroenterol, 2021, 21(1): 399 [2022-12-09]. DOI: 10.1186/s12876-021-01950-y.
OH C R, KIM J E, KANG J, et al. Prognostic value of the microsatellite instability status in patients with stage Ⅱ/Ⅲ rectal cancer following upfront surgery[J/OL]. Clin Colorectal Cancer, 2018, 17(4): e679-e685 [2022-12-10]. DOI: 10.1016/j.clcc.2018.07.003.
RATOVOMANANA T, COHEN R, SVRCEK M, et al. Performance of next-generation sequencing for the detection of microsatellite instability in colorectal cancer with deficient DNA mismatch repair[J/OL]. Gastroenterology, 2021, 161(3): 814-826.e7 [2022-12-08]. DOI: 10.1053/j.gastro.2021.05.007.
SAMAISON L, UGUEN A. Idylla MSI test combined with immunohistochemistry is a valuable and cost effective strategy to search for microsatellite instable tumors of noncolorectal origin[J]. Pathol Int, 2022, 72(4): 234-241. DOI: 10.1111/pin.13208.
SHIA J R. The diversity of tumours with microsatellite instability: molecular mechanisms and impact upon microsatellite instability testing and mismatch repair protein immunohistochemistry[J]. Histopathology, 2021, 78(4): 485-497. DOI: 10.1111/his.14271.
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/OL]. Abdom Radiol, 2023, 48(3): 844-854 [2023-01-10]. DOI: 10.1007/s00261-022-03782-0.
WANG L L, LI S H, HUANG G, et al. Study on biological characteristics of rectal cancer based on magnetic resonance diffusion kurtosis imaging[J]. Chin J Magn Reson Imag, 2020, 11(1): 35-39. DOI: 10.12015/issn.1674-8034.2020.01.008.
HU S, PENG Y, WANG Q S, et al. T2*-weighted imaging and diffusion kurtosis imaging (DKI) of rectal cancer: correlation with clinical histopathologic prognostic factors[J]. Abdom Radiol, 2022, 47(2): 517-529. DOI: 10.1007/s00261-021-03369-1.
DING X, SUN D Q, GUO Q C, et al. The value of diffusion kurtosis imaging and intravoxel incoherent motion quantitative parameters in predicting synchronous distant metastasis of rectal cancer[J/OL]. BMC Cancer, 2022, 22(1): 920 [2023-02-05]. DOI: 10.1186/s12885-022-10022-7.
SUNG H, FERLAY J, SIEGEL R L, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
SCHLECHTER B L. Management of rectal cancer[J]. Hematol Oncol Clin North Am, 2022, 36(3): 521-537. DOI: 10.1016/j.hoc.2022.03.002.
ZHOU L, YANG X Q, ZHAO G Y, et al. Meta-analysis of neoadjuvant immunotherapy for non-metastatic colorectal cancer[J/OL]. Front Immunol, 2023, 14: 1044353 [2023-06-09]. DOI: 10.3389/fimmu.2023.1044353.
SU A L, PEDRAZA R, KENNECKE H. Developments in checkpoint inhibitor therapy for the management of deficient mismatch repair (dMMR) rectal cancer[J]. Curr Oncol, 2023, 30(4): 3672-3683. DOI: 10.3390/curroncol30040279.
MIYAMOTO Y, OGAWA K, OHUCHI M, et al. Emerging evidence of immunotherapy for colorectal cancer[J]. Ann Gastroenterol Surg, 2023, 7(2): 216-224. DOI: 10.1002/ags3.12633.
SAHIN I H, ZHANG J, SARIDOGAN T, et al. Neoadjuvant immune checkpoint inhibitor therapy for patients with microsatellite instability-high colorectal cancer: shedding light on the future[J]. JCO Oncol Pract, 2023, 19(5): 251-259. DOI: 10.1200/OP.22.00762.
SAKATA S, LARSON D W. Targeted therapy for colorectal cancer[J]. Surg Oncol Clin N Am, 2022, 31(2): 255-264. DOI: 10.1016/j.soc.2021.11.006.
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.
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 [2022-12-05]. DOI: 10.3389/fonc.2019.01250.
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.
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.
HUANG Z X, ZHANG W, HE D, et al. Development and validation of a radiomics model based on T2WI images for preoperative prediction of microsatellite instability status in rectal cancer: study Protocol Clinical Trial (SPIRIT Compliant)[J/OL]. Medicine, 2020, 99(10): e19428 [2022-12-08]. DOI: 10.1097/MD.0000000000019428.
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.
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 [2023-06-10]. DOI: 10.3390/diagnostics13020269.

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