Improved detection of a tumorous involvement of the mesorectal fascia and locoregional lymph nodes in locally advanced rectal cancer using DCE-MRI

Armbruster, Marco; D’Anastasi, Melvin; Holzner, Veronika; Kreis, Martin E.; Dietrich, Olaf; Brandlhuber, Bernhard; Graser, Anno; Brandlhuber, Martina

doi:10.1007/s00384-018-3083-x

Cited by 18 publications

(10 citation statements)

References 37 publications

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“…36 T1+C sequences, which can be used to indicate tumor blood supply, can be better evaluate tumor invasiveness because the growth, development and metastasis of tumors depend on complex microvessels for nutrition. 37 Both T2WI and T1+C sequences showed high predictive value for treatment response in the present study, which is important for predicting the outcome of treatment. Secondly, our study differed from earlier studies limited to radiomics in that clinical data were also incorporated into the model as important factors.…”

Section: Discussionsupporting

confidence: 57%

Development of a Joint Prediction Model Based on Both the Radiomics and Clinical Factors for Predicting the Tumor Response to Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer

Liu

Zhang

Zhao

et al. 2021

CMAR

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Purpose Neoadjuvant chemoradiotherapy (nCRT) has become the standard treatment for locally advanced rectal cancer (LARC). However, the accuracy of traditional clinical indicators in predicting tumor response is poor. Recently, radiomics based on magnetic resonance imaging (MRI) has been regarded as a promising noninvasive assessment method. The present study was conducted to develop a model to predict the pathological response by analyzing the quantitative features of MRI and clinical risk factors, which might predict the therapeutic effects in patients with LARC as accurately as possible before treatment. Patients and Methods A total of 82 patients with LARC were enrolled as the training cohort and internal validation cohort. The pre-CRT MRI after pretreatment was acquired to extract texture features, which was finally selected through the minimum redundancy maximum relevance (mRMR) algorithm. A support vector machine (SVM) was used as a classifier to classify different tumor responses. A joint radiomics model combined with clinical risk factors was then developed and evaluated by receiver operating characteristic (ROC) curves. External validation was performed with 107 patients from another center to evaluate the applicability of the model. Results Twenty top image texture features were extracted from 6192 extracted-radiomic features. The radiomics model based on high-spatial-resolution T2-weighted imaging (HR-T2WI) and contrast-enhanced T1-weighted imaging (T1+C) demonstrated an area under the curve (AUC) of 0.8910 (0.8114–0.9706) and 0.8938 (0.8084–0.9792), respectively. The AUC value rose to 0.9371 (0.8751–0.9997) and 0.9113 (0.8449–0.9776), respectively, when the circumferential resection margin (CRM) and carbohydrate antigen 19-9 (CA19-9) levels were incorporated. Clinical usefulness was confirmed in an external validation cohort as well (AUC, 0.6413 and 0.6818). Conclusion Our study indicated that the joint radiomics prediction model combined with clinical risk factors showed good predictive ability regarding the treatment response of tumors as accurately as possible before treatment.

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Section: Discussionsupporting

confidence: 57%

Development of a Joint Prediction Model Based on Both the Radiomics and Clinical Factors for Predicting the Tumor Response to Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer

Liu

Zhang

Zhao

et al. 2021

CMAR

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“…Grovik et al showed that a low K trans of the primary tumor can predict the presence of nodal metastasis (63), which can be achieved by dynamic contrastenhanced MRI (DCE-MRI) (64,65). In addition to DCE-MRI, special diffusion-weighted MRI parameters are helpful in differentiating metastatic lymph nodes (45,66).…”

Section: Discussionmentioning

confidence: 99%

“…The characteristics of the studies are presented in Table 1. The reference standards were divided into the following five categories according to different morphological criteria: (A) a short-axis diameter of 5 mm (22-34), (B) morphological standard, including an irregular border and mixed-signal intensity within the lymph node (35)(36)(37)(38)(39)(40), (C) a short-axis diameter of 5 mm with the morphological standard (11,(41)(42)(43)(44)(45)(46)(47)(48), (D) a short-axis diameter of 8 mm with the morphological standard (49)(50)(51)(52), and (E) a short-axis diameter of 10 mm with the morphological standard (11,45,53,54). In all of the included articles, 36 indirectly evaluated the lymph node stage of patients through histopathology and 5 (9,41,42,55,56) identified the node-by-node correspondence between lymph node MRI scans and histopathologic results.…”

Section: Description Of Included Studiesmentioning

confidence: 99%

Magnetic Resonance Imaging Evaluation of the Accuracy of Various Lymph Node Staging Criteria in Rectal Cancer: A Systematic Review and Meta-Analysis

et al. 2021

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BackgroundMagnetic resonance imaging (MRI)-based lymph node staging remains a significant challenge in the treatment of rectal cancer. Pretreatment evaluation of lymph node metastasis guides the formulation of treatment plans. This systematic review aimed to evaluate the diagnostic performance of MRI in lymph node staging using various morphological criteria.MethodsA systematic search of the EMBASE, Medline, and Cochrane databases was performed. Original articles published between 2000 and January 2021 that used MRI for lymph node staging in rectal cancer were eligible. The included studies were assessed using the QUADAS-2 tool. A bivariate random-effects model was used to conduct a meta-analysis of diagnostic test accuracy.ResultsThirty-seven studies were eligible for this meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratio of preoperative MRI for the lymph node stage were 0.73 (95% confidence interval [CI], 0.68–0.77), 0.74 (95% CI, 0.68–0.80), and 7.85 (95% CI, 5.78–10.66), respectively. Criteria for positive mesorectal lymph node metastasis included (A) a short-axis diameter of 5 mm, (B) morphological standard, including an irregular border and mixed-signal intensity within the lymph node, (C) a short-axis diameter of 5 mm with the morphological standard, (D) a short-axis diameter of 8 mm with the morphological standard, and (E) a short-axis diameter of 10 mm with the morphological standard. The pooled sensitivity/specificity for these criteria were 75%/64%, 81%/67%, 74%/79%, 72%/66%, and 62%/91%, respectively. There was no significant difference among the criteria in sensitivity/specificity. The area under the receiver operating characteristic (ROC) curve values of the fitted summary ROC indicated a diagnostic accuracy rate of 0.75–0.81.ConclusionMRI scans have minimal accuracy as a reference index for pretreatment staging of various lymph node staging criteria in rectal cancer. Multiple types of evidence should be used in clinical decision-making.

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“…18 Semi-quantitative maps for plasma flow and mean transit time were calculated by deconvolution of tissue concentrations with the arterial input function. 17,19…”

Section: Mri and Dce-mri Postprocessingmentioning

confidence: 99%

Impact of Dynamic Contrast Enhanced and Diffusion‐Weighted MR Imaging on Detection of Early Local Recurrence of Soft Tissue Sarcoma

Erber

Reidler

Goller

et al. 2022

Magnetic Resonance Imaging

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Background Diagnosis of residual or recurrent tumor in soft‐tissue sarcomas (STS) is a differential diagnostic challenge since post‐therapeutic changes impede diagnosis. Purpose To evaluate the diagnostic accuracy of quantitative dynamic contrast enhanced (DCE)‐MRI and diffusion‐weighted imaging (DWI) to detect local recurrence of STS of the limb. Study Type Prospective. Population A totalof 64 consecutive patients with primary STS of the limbs were prospectively included 3–6 months after surgery between January 2016 and July 2021. Field Strength/Sequence A 1.5 T; axial DWI echo‐planar imaging sequences and DCE‐MRI using a 3D T1‐weighted spoiled gradient‐echo sequence. Assessment The quantitative DCE‐MRI parameters relative plasma flow (rPF) and relative mean transit time (rMTT) were calculated and ADC mapping was used to quantify diffusion restriction. Regions of interest of tumor growth and postoperative changes were drawn in consensus by two experts for diffusion and perfusion analysis. An additional morphological assessment was done by three independent and blinded radiologists. Statistical Test Unpaired t‐test, ROC‐analysis, and a logistic regression model were applied. Interobserver reliability was calculated using Fleiss kappa statistics. A P value of 0.05 was considered statistically significant. Results A total of 11 patients turned out to have local recurrence. rPF was significantly higher in cases of local recurrence when compared to cases without local recurrence (61.1–4.5) while rMTT was slightly and significantly lower in local recurrence. ROC‐analysis showed an area under the curve (AUC) of 0.95 (SEM ± 0.05) for rPF while a three‐factor multivariate logistic regression model showed a high diagnostic accuracy of rPF (R2 = 0.71). Compared with morphological assessment, rPF had a distinct higher specificity and true positive value in detection of LR. Data Conclusion DCE‐MRI is a promising additional method to differentiate local recurrence from benign postoperative changes in STS of the limb. Especially specificity in detection of LR is increased compared to morphological assessment. Evidence Level 1 Technical Efficacy Stage 2

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Improved detection of a tumorous involvement of the mesorectal fascia and locoregional lymph nodes in locally advanced rectal cancer using DCE-MRI

Abstract: DCE-MRI considerably increases both sensitivity and specificity for the detection of small mesorectal lymph node metastases (≥ 5 mm but < 10 mm) and sufficiently improves specificity of a suspected MRF infiltration in patients with locally advanced rectal cancer.

Cited by 18 publications

References 37 publications

Development of a Joint Prediction Model Based on Both the Radiomics and Clinical Factors for Predicting the Tumor Response to Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer

Development of a Joint Prediction Model Based on Both the Radiomics and Clinical Factors for Predicting the Tumor Response to Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer

Magnetic Resonance Imaging Evaluation of the Accuracy of Various Lymph Node Staging Criteria in Rectal Cancer: A Systematic Review and Meta-Analysis

Impact of Dynamic Contrast Enhanced and Diffusion‐Weighted MR Imaging on Detection of Early Local Recurrence of Soft Tissue Sarcoma

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