수술 전 선행보조치료를 받은 직장암 환자의 직장 자기공명영상의 해석 Interpretation of Rectal MRI after Neoadjuvant Treatment in Patients with Rectal Cancer
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PROVIDER: S-EPMC10265231 | biostudies-literature | 2023 May
REPOSITORIES: biostudies-literature
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Project description:In recent years, several key advances in the management of locally advanced rectal cancer have been made, including the implementation of total mesorectal excision as the standard surgical approach; use of neoadjuvant chemoradiotherapy in selected patients with a high risk of local recurrence, and finally, adoption of organ preservation strategies, through either local excision or nonoperative management in selected patients with clinical complete response following neoadjuvant chemoradiotherapy. This review aims to shed light on the role of rectal MRI in the assessment of treatment response after neoadjuvant therapy, which is especially important given the growing feasibility of nonoperative management. First, an overview of current neoadjuvant therapies and response assessment based on digital rectal examination, endoscopy, and MRI will be provided. Second, the use of a high-quality restaging rectal MRI protocol will be presented. Third, a step-by-step approach to assessing treatment response on restaging rectal MRI following neoadjuvant treatment will be outlined, acknowledging challenges faced by radiologists during MRI interpretation. Finally, research related to response assessment will be discussed. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.
| S-EPMC9851947 | biostudies-literature
Project description:BackgroundTo validate and compare various MRI-based radiomics models to evaluate treatment response to neoadjuvant chemoradiotherapy (nCRT) of rectal cancer.MethodsA total of 80 patients with locally advanced rectal cancer (LARC) who underwent surgical resection after nCRT were enrolled retrospectively. Rectal MR images were scanned pre- and post-nCRT. The radiomics features were extracted from T2-weighted images, then reduced separately by least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA). Four classifiers of Logistic Regression, Random Forest (RF), Decision Tree and K-nearest neighbor (KNN) models were constructed to assess the tumor regression grade (TRG) and pathologic complete response (pCR), respectively. The diagnostic performances of models were determined with leave-one-out cross-validation by generating receiver operating characteristic curves and decision curve analysis.ResultsThree features related to the TRG and 11 features related to the pCR were obtained by LASSO. Top five principal components representing a cumulative contribution of 80% to overall features were selected by PCA. For TRG, the area under the curve (AUC) of RF model was 0.943 for LASSO and 0.930 for PCA, higher than other models (P < 0.05 for both). As for pCR, the AUCs of KNN for LASSO and PCA were 0.945 and 0.712, higher than other models (P < 0.05 for both). The DCA showed that LASSO algorithm was clinically superior to PCA.ConclusionMRI-based radiomics models demonstrated good performance for evaluating the treatment response of LARC after nCRT and LASSO algorithm yielded more clinical benefit.
| S-EPMC7885409 | biostudies-literature
Project description:BackgroundTo analyse the performance of multicentre pre-treatment MRI-based radiomics (MBR) signatures combined with clinical baseline characteristics and neoadjuvant treatment modalities to predict complete response to neoadjuvant (chemo)radiotherapy in locally advanced rectal cancer (LARC).MethodsBaseline MRI and clinical characteristics with neoadjuvant treatment modalities at four centres were collected. Decision tree, support vector machine and five-fold cross-validation were applied for two non-imaging and three radiomics-based models' development and validation.ResultsWe finally included 674 patients. Pre-treatment CEA, T stage, and histologic grade were selected to generate two non-imaging models: C model (clinical baseline characteristics alone) and CT model (clinical baseline characteristics combining neoadjuvant treatment modalities). The prediction performance of both non-imaging models were poor. The MBR signatures comprising 30 selected radiomics features, the MBR signatures combining clinical baseline characteristics (CMBR), and the CMBR incorporating neoadjuvant treatment modalities (CTMBR) all showed good discrimination with mean AUCs of 0.7835, 0.7871 and 0.7916 in validation sets, respectively. The three radiomics-based models had insignificant discrimination in performance.ConclusionsThe performance of the radiomics-based models were superior to the non-imaging models. MBR signatures seemed to reflect LARC's true nature more accurately than clinical parameters and helped identify patients who can undergo organ preservation strategies.
| S-EPMC9296479 | biostudies-literature
Project description:Rectal cancer remains a significant problem worldwide. Outcomes vary significantly according to the stage of disease and prognostic factors, including the distance of the tumor from the circumferential resection margin. Accurate staging, including high-resolution magnetic resonance imaging, allows stratification of patients into low-, moderate-, and high-risk disease; this information can be used to inform multidisciplinary team decisions regarding the role of neoadjuvant therapy. Both neoadjuvant short-course radiotherapy and long-course chemoradiation reduce the risk of local recurrence compared with surgery alone, but they have little impact on survival. Although there remains a need to reduce overtreatment of those patients at moderate risk, evaluation of intensified regimens for those with high-risk disease is still required to reduce distant failure rates and improve survival in these patients with an otherwise poor prognosis.
| S-EPMC3720638 | biostudies-literature
Project description:PurposeNeoadjuvant chemoradiotherapy for rectal cancer is associated with improved local control and may result in complete tumor response. Associations between tumor response and disease control following radical resection should be established before tumor response is used to evaluate treatment strategies. The purpose of this study was to assess and compare oncologic outcomes associated with the degree of pathologic response after chemoradiotherapy.Patients and methodsAll patients with locally advanced (cT3-4 or cN+ by endorectal ultrasonography, computed tomography, or magnetic resonance imaging) rectal carcinoma diagnosed from 1993 to 2008 at our institution and treated with preoperative chemoradiotherapy and radical resection were identified, and their records were retrospectively reviewed. The median radiation dose was 50.4 Gy with concurrent chemotherapy. Recurrence-free survival (RFS), distant metastasis (DM), and local recurrence (LR) rates were compared among patients with complete (ypT0N0), intermediate (ypT1-2N0), or poor (ypT3-4 or N+) response by using Kaplan-Meier survival analysis and multivariate Cox proportional hazards regression.ResultsIn all, 725 patients were classified by tumor response: complete (131; 18.1%), intermediate (210; 29.0%), and poor (384; 53.0%). Age, sex, cN stage, and tumor location were not related to tumor response. Tumor response (complete v intermediate v poor) was associated with 5-year RFS (90.5% v 78.7% v 58.5%; P < .001), 5-year DM rates (7.0% v 10.1% v 26.5%; P < .001), and 5-year LR only rates (0% v 1.4% v 4.4%; P = .002).ConclusionTreatment response to neoadjuvant chemoradiotherapy among patients with locally advanced rectal cancer undergoing radical resection is an early surrogate marker and correlate to oncologic outcomes. These data provide guidance with response-stratified oncologic benchmarks for comparisons of novel treatment strategies.
| S-EPMC3383178 | biostudies-literature
Project description:BackgroundIn rectal cancer, prediction of tumor response and pathological complete response (pCR) to neoadjuvant treatment could contribute to refine selection of patients who might benefit from a delayed- or no-surgery approach. The aim of this study was to explore the association of clinical and molecular characteristics of rectal cancer with response to neoadjuvant treatment and to compare patient survival according to level of response.MethodsResected rectal cancer patients were selected from a population-based cohort study. Molecular tumor markers were determined from the surgical specimen. Tumor response and pCR were defined as downstaging in T or N stage and absence of tumor cells upon pathological examination, respectively. The associations of patient and tumor characteristics with tumor response and pCR were explored, and patient survival was determined by degree of response to neoadjuvant treatment.ResultsAmong 1536 patients with rectal cancer, 602 (39%) received neoadjuvant treatment. Fifty-five (9%) patients presented pCR, and 239 (49%) and 250 (53%) patients showed downstaging of the T and N stages, respectively. No statistically significant associations were observed between patient or tumor characteristics and tumor response or pCR. Patients who presented any type of response to neoadjuvant treatment had significantly better cancer-specific and overall survival compared with non-responders.ConclusionIn this study, patient characteristics were not associated with response to neoadjuvant treatment, and molecular characteristics determined after surgical resection of the tumor were not predictive of pCR or tumor downstaging. Future studies should include molecular biomarkers from biopsy samples before neoadjuvant treatment.
| S-EPMC7782441 | biostudies-literature
Project description:ObjectivesA watch and wait strategy with the goal of organ preservation is an emerging treatment paradigm for rectal cancer following neoadjuvant treatment. However, the selection of appropriate patients remains a challenge. Most previous efforts to measure the accuracy of MRI in assessing rectal cancer response used a small number of radiologists and did not report variability among them.MethodsTwelve radiologists from 8 institutions assessed baseline and restaging MRI scans of 39 patients. The participating radiologists were asked to assess MRI features and to categorize the overall response as complete or incomplete. The reference standard was pathological complete response or a sustained clinical response for > 2 years.ResultsWe measured the accuracy and described the interobserver variability of interpretation of rectal cancer response between radiologists at different medical centers. Overall accuracy was 64%, with a sensitivity of 65% for detecting complete response and specificity of 63% for detecting residual tumor. Interpretation of the overall response was more accurate than the interpretation of any individual feature. Variability of interpretation was dependent on the patient and imaging feature investigated. In general, variability and accuracy were inversely correlated.ConclusionsMRI-based evaluation of response at restaging is insufficiently accurate and has substantial variability of interpretation. Although some patients' response to neoadjuvant treatment on MRI may be easily recognizable, as seen by high accuracy and low variability, that is not the case for most patients.Key points• The overall accuracy of MRI-based response assessment is low and radiologists differed in their interpretation of key imaging features. • Some patients' scans were interpreted with high accuracy and low variability, suggesting that these patients' pattern of response is easier to interpret. • The most accurate assessments were those of the overall response, which took into consideration both T2W and DWI sequences and the assessment of both the primary tumor and the lymph nodes.
| S-EPMC10394731 | biostudies-literature
Project description:BackgroundThe purpose of this study was to investigate and validate multiparametric magnetic resonance imaging (MRI)-based machine learning classifiers for early identification of poor responders after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).MethodsPatients with LARC who underwent nCRT were included in this retrospective study (207 patients). After preprocessing of multiparametric MRI, radiomics features were extracted and four feature selection methods were used to select robust features. The selected features were used to build five machine learning classifiers, and 20 (four feature selection methods × five machine learning classifiers) predictive models for the screening of poor responders were constructed. The predictive models were evaluated according to the area under the curve (AUC), F1 score, accuracy, sensitivity, and specificity.ResultsEighty percent of all predictive models constructed achieved an AUC of more than 0.70. A predictive model using a support vector machine classifier with the minimum redundancy maximum relevance (mRMR) selection method followed by the least absolute shrinkage and selection operator (LASSO) selection method showed superior prediction performance, with an AUC of 0.923, an F1 score of 88.14%, and accuracy of 91.03%. The predictive performance of the constructed models was not improved by ComBat compensation.ConclusionsIn rectal cancer patients who underwent neoadjuvant chemoradiotherapy, machine learning classifiers with radiomics features extracted from multiparametric MRI were able to accurately discriminate poor responders from good responders. The techniques should provide additional information to guide patient-tailored treatment.
| S-EPMC9017030 | biostudies-literature
Project description:To determine the imaging details and diagnostic information of the treatment response to neoadjuvant chemoradiotherapy (nCRT) of rectal adenocarcinoma at 9.4T magnetic resonance imaging (MRI) by ex vivo. Fifteen cases with locally advanced rectal cancer (LARC) followed by radical surgery after nCRT between September 2022 and February 2023 were recruited. Resected specimens were fixed in a perfluoropolyether-filled test tube and scanned with a 3.0T and 9.4T MRI system ex vivo. The residual tumor depth and MRI-based tumor regression grade (TRG) were subjectively assessed and then compared with the pathological findings. The ex vivo 9.4T T2WI without fat suppression clearly differentiated tumor tissue, fibrosis and normal rectal wall, which clearly corresponded to the pathologic tissues of the rectal specimens. The TRG could be accurately assessed on ex vivo 9.4T images in 13/15 specimens (86.7%), while in 11/15 specimens (73.3%) on ex vivo 3.0T images. Ex vivo 9.4T MR imaging clearly displayed the components of rectal wall and proved excellent diagnostic performance for evaluating the treatment response to nCRT, which allow radiologists to understand and then assess more accurately the TRG of LARC after nCRT.
| S-EPMC11293138 | biostudies-literature
Project description:BackgroundStandardized assessments of clinical complete response (cCR) to neoadjuvant chemoradiotherapy (nCRT) for rectal cancer have been established, but their utility and accuracy remain unclear. This study aimed to evaluate the clinical diagnostic value of rectal magnetic resonance imaging (MRI) and endorectal ultrasonography (ERUS) for the determination of cCRs after neoadjuvant immunotherapy and to investigate the concordance between cCR and pathological complete response (pCR).MethodsNinety-four patients with rectal cancer treated with neoadjuvant radiotherapy with or without immunotherapy were included. The sensitivity, specificity, and accuracy of each evaluation method were calculated.ResultsCombined MRI and ERUS assessments found cCR in seven of the 94 patients in our cohort. In the non-immunotherapy group, the sensitivity, specificity, and accuracy of MRI for diagnosing cCR were 50.0%, 85.2%, and 77.1%, respectively, whereas those of ERUS were 50.0%, 92.6%, and 82.9%, respectively; those of combined MRI and ERUS were 25.0%, 96.3%, and 87.5%, respectively. In the immunotherapy group, the sensitivity, specificity, and accuracy with which MRI identified CR were 51.7%, 76.7%, and 64.4%, respectively; those of ERUS were 13.8%, 90.0%, and 52.5%, respectively, and those of combined MRI and ERUS were 10.3%, 96.7%, and 54.2%, respectively. We also found that 32 of 37 patients with pCR did not meet the cCR evaluation criteria. Of these pCR patients, 78.4% (29/37) received immunotherapy. In the entire cohort, there were five pCRs among the seven cCRs. Of the four cCRs that occurred in the immunotherapy group, three were pCRs.ConclusionsRectal MRI and/or ERUS did not provide sufficiently accurate assessments of cCR in patients with rectal cancer receiving neoadjuvant therapy, especially immunotherapy, and cCR did not predict pCR.
| S-EPMC11001488 | biostudies-literature