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• Clinical Articles •
Evaluation of peritumoral and intratumoral apparent diffusion coefficient parameters for the diagnosis of pathological factors in resectable rectal cancer
SUN Yancong  XIE Beichen  NIU Jin  DUAN Jinhui  ZHANG Jian  YAN Ruifang 

Cite this article as: SUN Y C, XIE B C, NIU J, et al. Evaluation of peritumoral and intratumoral apparent diffusion coefficient parameters for the diagnosis of pathological factors in resectable rectal cancer[J]. Chin J Magn Reson Imaging, 2023, 14(7): 53-60. DOI:10.12015/issn.1674-8034.2023.07.010.


[Abstract] Objective To investigate the diagnostic value of peritumoral and intratumoral apparent diffusion coefficient (ADC) in the pathological prognostic factors of resectable rectal cancer.Materials and Methods Sixty-eight patients with rectal cancer who received preoperative MRI were retrospectively analyzed. Two radiologists independently placed three circular regions of interest (ROIs) with an area of about 20 mm2 in the largest cross section of the tumor, and three oval ROIs with an area of about 22 mm2 in the peritumoral region adjacent to the tumor contour. The maximum of tumor ADC (ADCtmax), minimum of tumor ADC (ADCtmin), mean of tumor ADC (ADCtmean), maximum of peritumoral ADC (ADCpmax), mean of peritumoral ADC (ADCpmean) and ADCpmean/ADCtmean (ADC ratio) were obtained, and the differences between groups with different prognostic factors were compared. Independent sample t test, Mann-Whitney U test and χ² test were used to compare whether the difference was statistically significant. The variables with statistically significant differences in univariate analysis were included in multivariate logistic regression analysis to screen out independent risk factors and establish a joint prediction model. Receiver operating characteristic (ROC) curve was used to calculate the area under the curve (AUC), and the diagnostic efficacy of each parameter and the combined prediction model for pathological prognostic factors was analyzed. DeLong test was used to compare whether the AUC of different parameters and a joint prediction model was statistically different.Results The inter-observer agreement of the parameters was good [intraclass correlation coefficient (ICC)＞0.75]. The ADC ratio of T3 group was higher than that of T1-T2 group, poorly differentiated group was higher than that of moderately well differentiated group, lymph node metastasis (LNM) positive group was higher than that of LNM negative group, tumor deposition (TD) positive group was higher than TD negative group, lymphovascular infiltration (LVI) positive group was higher than LVI negative group, ADCtmean in T1-T2 group was higher than T3 group, LNM negative group was higher than LNM positive group. ADCpmean in T1-T2 group was lower than that in T3 group, TD positive group was higher than that in TD negative group, and LVI positive group was higher than that in LVI negative group, and the differences were statistically significant (P＜0.05). The ROC curve analysis showed that the AUCs of ADC ratio in predicting T3, LNM-positive, high differentiation, TD-positive, and LVI-positive were 0.803 [95% (confidence interval, CI): 0.694-0.911], 0.737 (95% CI: 0.614-0.859), 0.787 (95% CI: 0.628-0.945), 0.706 (95% CI: 0.572-0.841), and 0.802 (95% CI: 0.685-0.919); the AUCs of ADCtmean in predicting T3 and LNM-positive were 0.737 (95% CI: 0.617-0.858) and 0.683 (95% CI: 0.548-0.818); the AUCs of ADCpmean in predicting T3, TD-positive, and LVI-positive were 0.691 (95% CI: 0.566-0.816), 0.702 (95% CI: 0.566-0.838), and 0.763 (95% CI: 0.647-0.880).Conclusions Peritumoral and intratumoral ADC parameters are important for the diagnosis of pathological factors in resectable rectal cancer, the AUC values of ADC ratio in T stage, LNM, TD and LVI of rectal cancer were higher than those of ADCtmean and ADCpmean.
[Keywords] rectal cancer；peritumoral tissue；within the tumor tissue；diffusion weighted imaging；apparent dispersion coefficient；magnetic resonance imaging；diagnosis；prognosis

SUN Yancong   XIE Beichen   NIU Jin   DUAN Jinhui   ZHANG Jian   YAN Ruifang*  

Department of Magnetic Resonance, the First Affiliated Hospital of Xinxiang Medical College, Xinxiang 453100, China

Corresponding author: Yan RF, E-mail: yrf718@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Medical Science and Technology Research Program of Henan Province (No. LHGJ20200519).
Received  2022-11-23
Accepted  2023-06-25
DOI: 10.12015/issn.1674-8034.2023.07.010
Cite this article as: SUN Y C, XIE B C, NIU J, et al. Evaluation of peritumoral and intratumoral apparent diffusion coefficient parameters for the diagnosis of pathological factors in resectable rectal cancer[J]. Chin J Magn Reson Imaging, 2023, 14(7): 53-60. DOI:10.12015/issn.1674-8034.2023.07.010.

[1]
SIEGEL R L, MILLER K D, GODING SAUER A, et al. Colorectal cancer statistics, 2020[J]. CA Cancer J Clin, 2020, 70(3): 145-164. DOI: 10.3322/caac.21601.
[2]
WONG M C S, HUANG J, LOK V, et al. Differences in incidence and mortality trends of colorectal cancer worldwide based on sex, age, and anatomic location[J/OL]. Clin Gastroenterol Hepatol, 2021, 19(5): 955-966.e61 [2022-05-01]. https://doi.org/10.1016/j.cgh.2020.02.026. DOI: 10.1016/j.cgh.2020.02.026.
[3]
SAHIN A A, GILLIGAN T D, CAUDELL J J. Challenges with the 8th edition of the AJCC cancer staging manual for breast, testicular, and head and neck cancers[J]. J Natl Compr Cancer Netw, 2019, 17(5.5): 560-564. DOI: 10.6004/jnccn.2019.5015.
[4]
GLYNNE-JONES R, WYRWICZ L, TIRET E, et al. Rectal cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up[J/OL]. Ann Oncol, 2017, 28(suppl_4): iv22-iv40 [2022-05-03]. https://doi.org/10.1093/annonc/mdx224. DOI: 10.1093/annonc/mdx224.
[5]
Chinese Society of Clinical Oncology (CSCO) diagnosis and treatment guidelines for colorectal cancer working group. Chinese Society of Clinical Oncology (CSCO) diagnosis and treatment guidelines for colorectal cancer 2018 (English version)[J]. Chin J Cancer Res, 2019, 31(1): 117-134. DOI: 10.21147/j.issn.1000-9604.2019.01.07.
[6]
MIRKIN K A, KULAYLAT A S, HOLLENBEAK C S, et al. Prognostic significance of tumor deposits in stage Ⅲ colon cancer[J]. Ann Surg Oncol, 2018, 25(11): 3179-3184. DOI: 10.1245/s10434-018-6661-9.
[7]
GAO Z Y, CAO H H, XU X, et al. Prognostic value of lymphovascular invasion in stage Ⅱ colorectal cancer patients with an inadequate examination of lymph nodes[J/OL]. World J Surg Oncol, 2021, 19(1): 125 [2022-05-03]. https://wjso.biomedcentral.com/articles/10.1186/s12957-021-02224-3. DOI: 10.1186/s12957-021-02224-3.
[8]
CHANDRAMOHAN A, SIDDIQI U M, MITTAL R, et al. Diffusion weighted imaging improves diagnostic ability of MRI for determining complete response to neoadjuvant therapy in locally advanced rectal cancer[J/OL]. Eur J Radiol Open, 2020, 7: 100223 [2022-04-05]. https://doi.org/10.1016/j.ejro.2020.100223. DOI: 10.1016/j.ejro.2020.100223.
[9]
FLIEDNER F P, ENGEL T B, EL-ALI H H, et al. Diffusion weighted magnetic resonance imaging (DW-MRI) as a non-invasive, tissue cellularity marker to monitor cancer treatment response[J/OL]. BMC Cancer, 2020, 20(1): 134 [2022-03-06]. https://doi.org/10.1186/s12885-020-6617-x. DOI: 10.1186/s12885-020-6617-x.
[10]
NELSON D A, TAN T T, RABSON A B, et al. Hypoxia and defective apoptosis drive genomic instability and tumorigenesis[J]. Genes Dev, 2004, 18(17): 2095-2107. DOI: 10.1101/gad.1204904.
[11]
SOYSAL S D, TZANKOV A, MUENST S E. Role of the tumor microenvironment in breast cancer[J]. Pathobiology, 2015, 82(3/4): 142-152. DOI: 10.1159/000430499.
[12]
TAMMI M I, OIKARI S, PASONEN-SEPPÄNEN S, et al. Activated hyaluronan metabolism in the tumor matrix—causes and consequences[J]. Matrix Biol, 2019, 78/79: 147-164. DOI: 10.1016/j.matbio.2018.04.012.
[13]
MORI N, MUGIKURA S, TAKASAWA C, et al. Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer[J].Eur Radiol, 2016, 26(2): 331-339. DOI: 10.1007/s00330-015-3847-4.
[14]
OKUMA H, SUDAH M, KETTUNEN T, et al. Peritumor to tumor apparent diffusion coefficient ratio is associated with biologically more aggressive breast cancer features and correlates with the prognostication tools[J/OL]. PLoS One, 2020, 15(6): e0235278 [2022-03-26]. https://doi.org/10.1371/journal.pone.0235278. DOI: 10.1371/journal.pone.0235278.
[15]
HU Y H, XIE C Y, YANG H, et al. Assessment of intratumoral and peritumoral computed tomography radiomics for predicting pathological complete response to neoadjuvant chemoradiation in patients with esophageal squamous cell carcinoma[J/OL]. JAMA Netw Open, 2020, 3(9): e2015927 [2022-03-26]. https://doi.org/10.1001/jamanetworkopen.2020.15927. DOI: 10.1001/jamanetworkopen.2020.15927.
[16]
DENG L, WANG Q P, YAN R, et al. The utility of measuring the apparent diffusion coefficient for peritumoral zone in assessing infiltration depth of endometrial cancer[J].Cancer Imaging, 2018, 18(1): 1-8. DOI: 10.1186/s40644-018-0156-6.
[17]
BAE H, YOSHIDA S, MATSUOKA Y, et al. Apparent diffusion coefficient value as a biomarker reflecting morphological and biological features of prostate cancer[J].Int Urol Nephrol, 2014, 46(3): 555-561. DOI: 10.1007/s11255-013-0557-1.
[18]
YILDIZ S, ARALASMAK A, YETIS H, et al. MRI findings and utility of DWI in the evaluation of solid parathyroid lesions[J].La Radiol Med, 2019, 124(5): 360-367. DOI: 10.1007/s11547-018-0970-8.
[19]
REYES-PÉREZ J A, VILLASEÑOR-NAVARRO Y, DE LOS SANTOS M E J, et al. The apparent diffusion coefficient (ADC) on 3-T MRI differentiates myometrial invasion depth and histological grade in patients with endometrial cancer[J]. Acta Radiol Stock Swed, 2020, 61(9): 1277-1286. DOI: 10.1177/0284185119898658.
[20]
CHOI B B. Effectiveness of ADC difference value on pre-neoadjuvant chemotherapy MRI for response evaluation of breast cancer[J/OL]. Technol Cancer Res Treat, 2021, 20: 153303382110391 [2022-06-06]. https://doi.org/10.1177/15330338211039129. DOI: 10.1177/15330338211039129.
[21]
MAFFAZZIOLI L, ZILIO M B, KLAMT A L, et al. ADC as a predictor of pathologic response to neoadjuvant therapy in esophageal cancer: a systematic review and meta-analysis[J].Eur Radiol, 2020, 30(7): 3934-3942. DOI: 10.1007/s00330-020-06723-x.
[22]
WANG Y, CHEN X, PU H, et al. Roles of DWI and T2-weighted MRI volumetry in the evaluation of lymph node metastasis and lymphovascular invasion of stage IB-IIA cervical cancer[J]. Clin Radiol, 2022, 77(3): 224-230. DOI: 10.1016/j.crad.2021.12.011.
[23]
LIU J K, LI Q Y, TANG L L, et al. Correlations of mean and mimimum apparent diffusion coefficient values with the clinicopathological features in rectal cancer[J]. Acad Radiol, 2021, 28: S105-S111. DOI: 10.1016/j.acra.2020.10.018.
[24]
LI H, CHEN G W, LIU Y S, et al. Assessment of histologic prognostic factors of resectable rectal cancer: comparison of diagnostic performance using various apparent diffusion coefficient parameters[J/OL]. Sci Rep, 2020, 10: 11554 [2022-06-05]. https://doi.org/10.1038/s41598-020-68328-0. DOI: 10.1038/s41598-020-68328-0.
[25]
SUN Y Q, TONG T, CAI S J, et al. Apparent Diffusion Coefficient (ADC) value: a potential imaging biomarker that reflects the biological features of rectal cancer[J/OL]. PLoS One, 2014, 9(10): e109371 [2022-06-04]. https://doi.org/10.1371/journal.pone.0109371. DOI: 10.1371/journal.pone.0109371.
[26]
SHIN H J, KIM S H, LEE H J, et al. Tumor apparent diffusion coefficient as an imaging biomarker to predict tumor aggressiveness in patients with estrogen-receptor-positive breast cancer[J]. NMR Biomed, 2016, 29(8): 1070-1078. DOI: 10.1002/nbm.3571.
[27]
CURVO-SEMEDO L, LAMBREGTS D M J, MAAS M, et al. Diffusion-weighted MRI in rectal cancer: apparent diffusion coefficient as a potential noninvasive marker of tumor aggressiveness[J]. J Magn Reson Imaging, 2012, 35(6): 1365-1371. DOI: 10.1002/jmri.23589.
[28]
YUAN Y, CHEN X L, LI Z L, et al. The application of apparent diffusion coefficients derived from intratumoral and peritumoral zones for assessing pathologic prognostic factors in rectal cancer[J].Eur Radiol, 2022, 32(8): 5106-5118. DOI: 10.1007/s00330-022-08717-3.
[29]
ZHOU J J, ZHANG Y, CHANG K T, et al. Diagnosis of benign and malignant breast lesions on DCE-MRI by using radiomics and deep learning with consideration of peritumor tissue[J]. J Magn Reson Imaging, 2020, 51(3): 798-809. DOI: 10.1002/jmri.26981.
[30]
LIU C L, DING J, SPUHLER K, et al. Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast-enhanced MRI[J]. J Magn Reson Imaging, 2019, 49(1): 131-140. DOI: 10.1002/jmri.26224.
[31]
BRAITHWAITE A C, DALE B M, BOLL D T, et al. Short- and midterm reproducibility of apparent diffusion coefficient measurements at 3.0-T diffusion-weighted imaging of the abdomen[J]. Radiology, 2009, 250(2): 459-465. DOI: 10.1148/radiol.2502080849.
[32]
BLAZIC I M, LILIC G B, GAJIC M M. Quantitative assessment of rectal cancer response to neoadjuvant combined chemotherapy and radiation therapy: comparison of three methods of positioning region of interest for ADC measurements at diffusion-weighted MR imaging[J]. Radiology, 2017, 282(2): 418-428. DOI: 10.1148/radiol.2016151908.
[33]
LAMBREGTS D M J, BEETS G L, MAAS M, et al. Tumour ADC measurements in rectal cancer: effect of ROI methods on ADC values and interobserver variability[J].Eur Radiol, 2011, 21(12): 2567-2574. DOI: 10.1007/s00330-011-2220-5.
[34]
KETTUNEN T, OKUMA H, AUVINEN P, et al. Peritumoral ADC values in breast cancer: region of interest selection, associations with hyaluronan intensity, and prognostic significance[J].Eur Radiol, 2020, 30(1): 38-46. DOI: 10.1007/s00330-019-06361-y.

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