Diffusion-weighted MR volume and apparent diffusion coefficient for discriminating lymph node metastases and good response after chemoradiation therapy in locally advanced rectal cancer

Yuan, Yi; Pu, Hong; Chen, Guangwen; Chen, Xiaoli; Liu, Yi-Sha; Liu, Hao; Wang, Kang; Li, Hang

doi:10.1007/s00330-020-07101-3

Cited by 8 publications

(3 citation statements)

References 26 publications

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“…A recent study revealed that the ADC values before treatment could predict patients with good response, and the AUCs, sensitivity, and speci city were 0.801, 80.36%, and 74.29%, respectively [10]. However, our result showed that no difference was found in pretreatment ADC values between the pCR group and the non-pCR group, which was in line with Yuan, Y. et al's study [34]. These con ict results about ADC values in treatment evaluation may be partly because of its inability to discriminate tissue from true diffusion of water molecules [35][36][37].…”

Section: Model Developmentsupporting

confidence: 91%

Combination of intravoxel incoherent motion histogram parameters and clinical characteristics for predicting response to neoadjuvant chemoradiation in Rectal Cancer

Yang,

Lin,

et al. 2024

Preprint

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Objective To explore the value of histogram parameters derived from intravoxel incoherent motion (IVIM) for predicting response to neoadjuvant chemoradiation (nCRT) in patients with rectal cancer. Methods 112 patients diagnosed with rectal cancer who underwent IVIM-DWI before nCRT were enrolled in this study, and true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and microvascular volume fraction (f) calculated from IVIM, together with the histogram parameters were recorded. The patients were divided into the pathological complete response (pCR) group and the non-pCR group according to the tumor regression grade (TRG) system. We also divided the patients into low T stage (yp T0-2) and high T stage (ypT3-4) according to the pathologic T stage (ypT stage). Univariate logistic regression analysis was implemented to select independent risk factors, including clinical characteristics and IVIM histogram parameters, and the models for Clinical, Histogram, and Combined Clinical and Histogram were generated respectively by using multivariable binary logistic regression analysis for predicting pCR. The area under the Receiver operating characteristic (ROC) curve (AUCs) were used to compare the diagnostic performance among the three models. Results The values of D_ kurtosis, f_mean, and f_ median were significantly higher in the pCR group (n = 24) compared with the non-pCR group. The value of D*_ entropy was significantly lower in the pCR group compared with the non-pCR group. The values of D_ kurtosis, f_mean, and f_ median were significantly higher in the low T stage group (n=37) compared with the high T stage group. The value of D*_ entropy was significantly lower in the low T stage group compared with the high T stage group (all p < 0.05). ROC curves demonstrated that the Combined Clinical and Histogram model had the best diagnostic performance in predicting the pCR patients with optimal AUCs, sensitivity, specificity, and accuracy (0.916, 83.33%, 85.23%, and 84.82%, respectively). Conclusions IVIM histogram parameters which combined with clinical characteristics showed promising prospects in predicting the pCR patients before surgery.

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Section: Model Developmentsupporting

confidence: 91%

Combination of intravoxel incoherent motion histogram parameters and clinical characteristics for predicting response to neoadjuvant chemoradiation in Rectal Cancer

Yang,

Lin,

et al. 2024

Preprint

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“…In contrast, ADC value is significantly increased in non-metastatic and benign tissue. DWI has been more and more applied in determining tumor status and evaluating therapeutic response after treatment [ 16 , 17 ]. Yet, to date, there is still a lack of studies using functional MRI parameters to determine the status of HLN.…”

Section: Introductionmentioning

confidence: 99%

Prediction of hepatic lymph node metastases based on magnetic resonance imaging before and after preoperative chemotherapy in patients with colorectal liver metastases underwent surgical resection

Zhu

Sun

et al. 2023

Cancer Imaging

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Background Patients with colorectal liver metastases (CRLM) combined with hepatic lymph node (HLN) metastases have a poor prognosis. In this study, we developed and validated a model using clinical and magnetic resonance imaging (MRI) parameters to predict HLN status before surgery. Methods A total of 104 CRLM patients undergoing hepatic lymphonodectomy with pathologically confirmed HLN status after preoperative chemotherapy were enrolled in this study. The patients were further divided into a training group (n = 52) and a validation group (n = 52). The apparent diffusion coefficient (ADC) values, including ADCmean and ADCmin of the largest HLN before and after treatment, were measured. rADC was calculated referring to the target liver metastases, spleen, and psoas major muscle (rADC-LM, rADC-SP, rADC-m). In addition, ADC change rate (Δ% ADC) was quantitatively calculated. A multivariate logistic regression model for predicting HLN status in CRLM patients was constructed using the training group and further tested in the validation group. Results In the training cohort, post-ADCmean (P = 0.018) and the short diameter of the largest lymph node after treatment (P = 0.001) were independent predictors for metastatic HLN in CRLM patients. The model’s AUC was 0.859 (95% CI, 0.757-0.961) and 0.767 (95% CI 0.634-0.900) in the training and validation cohorts, respectively. Patients with metastatic HLN showed significantly worse overall survival (p = 0.035) and recurrence-free survival (p = 0.015) than patients with negative HLN. Conclusions The developed model using MRI parameters could accurately predict HLN metastases in CRLM patients and could be used to preoperatively assess the HLN status and facilitate surgical treatment decisions in patients with CRLM.

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“…In the past, clinicians often used the size of the lymph nodes to estimate which lymph nodes could have metastases and which could be free of metastatic foci (74), to assess the volume reduction rate prior to and following treatment to evaluate lymph node metastasis (75), or to predict the status of the lymph nodes using clinicopathological factors (76); however, precise prediction accuracy has not been achieved. In recent years, with the development of artificial intelligence and big data, radiomics studies have become increasingly popular in the clinic.…”

Section: Mri-based Radiomics To Predict Lymph Node Statusmentioning

confidence: 99%

Role of MRI‑based radiomics in locally advanced rectal cancer (Review)

Zhang

Chen

et al. 2021

Oncol Rep

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Colorectal cancer is the third most common type of cancer, with high morbidity and mortality rates. In particular, locally advanced rectal cancer (LARC) is difficult to treat and has a high recurrence rate. Neoadjuvant chemoradiotherapy (NCRT) is one of the standard treatment programs of LARC. If the response to treatment and prognosis in patients with LARC can be predicted, it will guide clinical decision-making. Radiomics is characterized by the extraction of high-dimensional quantitative features from medical imaging data, followed by data analysis and model construction, which can be used for tumor diagnosis, staging, prediction of treatment response and prognosis. In recent years, a number of studies have assessed the role of radiomics in NCRT for LARC. MRI-based radiomics provides valuable data and is expected to become an imaging biomarker for predicting treatment response and prognosis. The potential of radiomics to guide personalized medicine is widely recognized; however, current limitations and challenges prevent its application to clinical decision-making. The present review summarizes the applications, limitations and prospects of MRI-based radiomics in LARC.

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Diffusion-weighted MR volume and apparent diffusion coefficient for discriminating lymph node metastases and good response after chemoradiation therapy in locally advanced rectal cancer

Cited by 8 publications

References 26 publications

Combination of intravoxel incoherent motion histogram parameters and clinical characteristics for predicting response to neoadjuvant chemoradiation in Rectal Cancer

Combination of intravoxel incoherent motion histogram parameters and clinical characteristics for predicting response to neoadjuvant chemoradiation in Rectal Cancer

Prediction of hepatic lymph node metastases based on magnetic resonance imaging before and after preoperative chemotherapy in patients with colorectal liver metastases underwent surgical resection

Role of MRI‑based radiomics in locally advanced rectal cancer (Review)

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