Rectal Magnetic Resonance Imaging Research Articles

Added value of DCER-features to clinicopathologic model for predicting metachronous metastases in rectal cancer patients.

The study aimed to investigate whether dynamic contrast-enhanced MRI parameters and preoperative radiological features (DCER-Features) add value to the clinicopathologic model for predicting metachronous metastases in rectal cancer patients. From January 2014 to December 2020, 859 patients in the PACS system were retrospectively screened. Of the initial 722 patients with surgically confirmed rectal cancer and no synchronous metastases, 579 patients were excluded for various reasons such as lack of clinicopathological or radiological information. 143 patients were finally included in this study. And 73 Patients of them developed metachronous metastasis within five years. After stepwise multiple regression analyses, we constructed three distinct models. Model 1 was developed solely based on clinicopathological factors, and model 2 incorporated clinicopathological characteristics along with DCE-MRI parameters. Finally, model 3 was built on all available factors, including clinicopathological characteristics, DCE-MRI parameters, and radiological features based on rectal magnetic resonance imaging. The radiological features assessed in this study encompass tumor imaging staging, location, and circumferential resection margin (CRM) for primary tumors, as well as the number of visible lymph nodes and suspected metastatic lymph nodes. Receiver operating characteristic (ROC) and decision curve analysis (DCA) were conducted to evaluate whether the diagnostic efficiency was improved. The performance of model 3 (including clinicopathologic characteristics and DCER-Features) was the best (AUC: 0.856, 95% CI 0.778-0.886), whereas it was 0.796 (95% CI 0.720-0.828) for model 2 and 0.709 (95% CI 0.612-0.778) for model 1 (DeLong test: model 1 vs model 2, p = 0.004; model 2 vs model 3, p = 0.037; model 1 vs model 3, p < 0.001). The decision curves indicated that the net benefit of model 3 was higher than the other two models at each referral threshold. The calibration plot of the three models revealed an excellent predictive accuracy. This study suggests that DCER-Features have added value for the clinicopathological model to predict metachronous metastasis in patients with rectal cancers.

Can rectal MRI and endorectal ultrasound accurately predict the complete response to neoadjuvant immunotherapy for rectal cancer?

Standardized 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). Ninety-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. Combined 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. Rectal 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.

Incidental findings on staging rectal MRI: clinical significance and outcomes.

Incidental findings (IFs) are commonly seen in staging rectal magnetic resonance imaging (MRI) scans. Their prevalence and clinical significance have not been previously documented. To assess the prevalence, clinical significance, and outcomes of incidental findings in MRI scans performed for the staging of rectal cancer. A retrospective study was performed at a tertiary colorectal imaging institution. Consecutive MRI rectal staging scans with correlative pathology confirmed primary rectal cancer between March 2014 and March 2021 were identified. The respective imaging reports were reviewed for IFs, which were classified as high, moderate, and low, according to their clinical significance. Medical records were reviewed to assess the outcomes of the highly significant IFs. There were 266 eligible patients (97 women; mean age = 64.2 years) during the study period. A total of 120 (45%) patients did not have any IFs. A total of 238 IFs in 146 (55%) patients were found. There were 21 (9%) IFs of high clinical significance, 122 (51%) of moderate clinical significance, and 95 (40%) of low clinical significance. The prostate and uterus had the most IFs of high clinical significance, two of which were subsequently pathology confirmed as prostate adenocarcinomas. IFs were seen in more than half of the staging MRI scans in rectal cancer but less than 10% of these were of high clinical significance. The results of this study highlight the range of potential IFs and can guide future research assessing the potential impact of these IFs on patients and the healthcare system.

Survey of rectal cancer MRI technique and reporting tumour descriptors in the UK: a multi-centre British Society of Gastrointestinal and Abdominal Radiology (BSGAR) audit

To evaluate variation in magnetic resonance imaging (MRI) technique and reporting of rectal cancer staging examinations across the UK. A retrospective, multi-centre audit was undertaken of imaging protocols and information documented within consecutive MRI rectal cancer reports between March 2020 and August 2021, which were compared against American and European guidelines. Inclusion criteria included histologically proven rectal adenocarcinoma and baseline staging MRI rectum only. Fully anonymised data from 924 MRI reports by 78 radiologists at 24 centres were evaluated. Thirty-two per cent of radiologists used template reporting, but these reports offered superior documentation of 13 out of 18 key tumour features compared to free-text reports including T-stage, relation to peritoneal reflection and mesorectal fascia (MRF), nodal status, and presence of extramural venous invasion (EMVI; p<0.027 in each). There was no significant differences in the remaining five features. Across all tumour locations, the tumour relationship to the MRF, the presence of EMVI, and the presence of tumour deposits were reported in 79.5%, 85.6%, and 44% of cases, respectively, and tumour, nodal, and distant metastatic stage documented in 94.4%, 97.7%, and 78.3%. In low rectal tumours, the relationship to the anal sphincter complex was reported in only 54.6%. Considerable variation exists in rectal cancer MRI acquisition and reporting in this sample of UK centres. Inclusion of key radiological features in reports must be improved for risk stratification and treatment decisions. Template reporting is superior to free-text reporting. Routine adoption of standardised radiology practices should now be considered to improve standards to facilitate personalised precision treatment for patients to improve outcomes.

Split scar sign to predict complete response in rectal cancer after neoadjuvant chemoradiotherapy: systematic review and meta-analysis.

Magnetic resonance imaging (MRI) is the modality of choice for rectal cancer initial staging and restaging after neoadjuvant chemoradiation. Our objective was to perform a meta-analysis of the diagnostic performance of the split scar sign (SSS) on rectal MRI in predicting complete response after neoadjuvant therapy. MEDLINE, EMBASE, and Cochrane databases were searched for relevant published studies through June 2023. Primary studies met eligibility criteria if they evaluated the diagnostic performance of the SSS to predict complete response on pathology or clinical follow-up in patients undergoing neoadjuvant chemoradiation. A meta-analysis with a random-effects model was used to estimate pooled sensitivity and specificity, area under the curve (AUC), and diagnostic odds ratio (DOR) of the SSS. A total of 4 studies comprising 377 patients met the inclusion criteria. The prevalence of complete response in the studies was 21.7-52.5%. The pooled sensitivity and specificity of the SSS to predict complete response were 62.0% (95% CI, 43.5-78.5%) and 91.9% (95% CI, 78.9-97.2%), respectively. The estimated AUC for SSS was 0.83 (95% CI, 0.56-0.94) with a DOR of 18.8 (95% CI, 3.65-96.5). The presence of SSS on rectal MRI demonstrated high specificity for complete response in patients with rectal cancer after neoadjuvant chemoradiation. This imaging pattern can be a valuable tool to identify potential candidates for organ-sparing treatment and surveillance. SSS presents high specificity for complete response post-neoadjuvant. This MRI finding enhances rectal cancer treatment assessment and aids clinicians and patients in choosing watch-and-wait over immediate surgery, which can potentially reduce costs and associated morbidity. •Fifteen to 50% of rectal cancer patients achieve complete response after neoadjuvant chemoradiation and may be eligible for a watch-and-wait strategy. •The split scar sign has high specificity for a complete response. •This imaging finding is valuable to select candidates for organ-sparing management.

Application of natural language processing to post-structuring of rectal cancer MRI reports

To evaluate a natural language processing (NLP) system for extracting structured information from the free-form text of rectal cancer magnetic resonance imaging (MRI) reports written in Chinese. A rule-based NLP model that could extract 11 key image features of rectal cancer was constructed using 358 MRI reports of rectal cancer written between 2015 and 2021. Fifty reports written before 2015 and 50 written after 2021 were used as test datasets, and the reference standard was determined by manual extraction of information by two radiologists. The length and reporting rate of image features in pre-2015 and post-2021 datasets, as well as the accuracy, precision, recall, and F1 score of feature extraction by the NLP system, were compared. The time required for the NLP to extract data was compared with that required by the radiologists. Reports written after 2021 had longer diagnostic impression sections than reports written before 2015. The reporting rate of key imaging features of rectal cancer was 36.55% before 2015 and 79.82% after 2021. The accuracy, precision, recall, and F1 score of NLP for correct extraction of values from reports were 93.82%, 95.63%, 87.06%, and 91.15%, respectively, for pre-2015 reports, and 92.55%, 98.53%, 94.15%, and 96.29%, respectively, for post-2021 reports. NLP generated all the structured information in <1 second. The NLP system with rule-based pattern matching achieved rapid and accurate structured processing of rectal cancer MRI reports. MRI reports with structured templates are more suitable for NLP-based extraction of information.

Preoperative prediction of tumor budding in rectal cancer using multiple machine learning algorithms based on MRI T2WI radiomics.

This study aimed to explore the radiomics model based on magnetic resonance imaging (MRI) T2WI and compare the value of different machine algorithms in preoperatively predicting tumor budding (TB) grading in rectal cancer. A retrospective study was conducted on 266 patients with preoperative rectal MRI examinations, who underwent complete surgical resection and confirmed pathological diagnosis of rectal cancer. Among them, patients from Qingdao West Coast Hospital were assigned as the training group (n=172), while patients from other hospitals were assigned as the external validation group (n=94). Regions of interest (ROIs) were delineated, and image features were extracted and dimensionally reduced using the Least Absolute Shrinkage and Selection Operator (LASSO). Eight machine algorithms were used to construct the models, and the diagnostic performance of the models was evaluated and compared using receiver operating characteristic (ROC) curves and the area under the curve (AUC), as well as clinical utility assessment using decision curve analysis (DCA). A total of 1197 features were extracted, and after feature selection and dimension reduction, 11 image features related to TB grading were obtained. Among the eight algorithm models, the support vector machine (SVM) algorithm achieved the best diagnostic performance, with accuracy, sensitivity, and specificity of 0.826, 0.949, and 0.723 in the training group, and 0.713, 0.579, and 0.804 in the validation group, respectively. DCA demonstrated the clinical utility of this radiomics model. The radiomics model based on MR T2WI can provide an effective and noninvasive method for preoperative TB grading assessment in patients with rectal cancer.

MRI in rectal cancer: An institutional real life analysis of technical parameters

MRI plays a key role in the preoperative staging of rectal cancers and choice of neoadjuvant radiochemotherapy. Yet, the acquisition and interpretation of rectum magnetic resonance imaging (MRI) turn out to be unequal, impacting patients'care. The present study aims at evaluating the quality of the acquisition of technical parameters of the rectal MRI performed by comparing them according to the various guidelines. The medical MRI reports of all consecutive patients with locally advanced rectal cancer treated in a curative intent, by preoperative RCT and completion surgery were retrospectively reviewed over two periods (January 2010-December 2014 and January 2018 and December 2020) according to international 2012 and 2016 ESGAR and 2017 SAR MRI recommendation reports. During the first period (69 MRI performed), 58% of these MRI abided by the recommendations and 75% of essential criteria could be found in 25.5% of MRI reportings. During the second period (73 MRI performed), the protocol used by 6.8% of MR images abided by the 2016 Society of Gastrointestinal and Abdominal Radiology(ESGAR) recommendations and 39.7% abided by the Society of Abdominal Radiology (SAR) recommendations. 75% of essential criteria could be found in 52.3% of MRI reportings and 90% of essential criteria could be found in 6.2% of MRI reportings. In an era of increasing individualized patient care and conservative treatment focused on tumour response and prognostic factors, the present study showed that compliance to MRI protocols and reporting guidelines needs improving to upgrade patient care.

Mesorectal reconstruction with pedicled greater omental transplantation to relieve low anterior resection syndrome following total intersphincteric resection in patients with ultra-low rectal cancer

BackgroundTotal intersphincteric resection (ISR) is the ultimate anus-preserving surgery for patients with ultra-low rectal cancer (ULRC), which can result in various degrees of anorectal dysfunction. Known as low anterior resection syndrome (LARS), it seriously affects the postoperative quality of life of patients. The aim of this study was to discuss the value of mesorectal reconstruction with pedicled greater omental transplantation (PGOT) to relieve LARS following total ISR in patients with ULRC, hoping to provide new ideas and strategies for the prevention and improvement of LARS.MethodsWe retrospectively analyzed hospitalization data and postoperative anorectal function of 26 ULRC patients, who were met inclusion and exclusion criteria in our center from January 2015 to February 2022. And combined with the results of anorectal manometry and rectal magnetic resonance imaging (MRI) defecography of some patients, we assessed comprehensively anorectal physiological and morphological changes of the patients after surgery, and their correlation with LARS.ResultsIn this study, 26 patients with ULRC were enrolled and divided into observation group (n = 15) and control group (n = 11) according to whether PGOT was performed. There were no significant differences in surgical results such as operative time, intraoperative blood loss and postoperative complications between the two groups (P > 0.05). Postoperative follow-up showed that patients in both groups showed severe LARS within 3 months after surgery, but from the 3rd month after surgery, LARS in both groups gradually began to decrease, especially in the observation group, which showed faster recovery and better recovery, with statistically significant difference (P < 0.001). Through anorectal manometry, the mean rectal resting pressure in the observation group was significantly lower than that in the control group (P = 0.010). In addition, the postoperative thickness of the posterior rectal mesenterium in the observation group was significantly higher than that in the control group (P = 0.001), and also higher than the preoperative level (P = 0.018). Moreover, rectal MRI defecography showed that the neo-rectum had good compliance under the matting of greater omentum, and its intestinal peristalsis was coordinated.ConclusionsULRC patients, with the help of greater omentum, coordinated their neo-rectum peristalsis after total ISR and recovery of LARS was faster and better. PGOT is expected to be an effective strategy for LARS prevention and treatment of ULRC patients after surgery and is worthy of clinical promotion.

The significance of mucin on rectal MRI in patients with locally advanced rectal cancer being considered for watch-and-wait after neoadjuvant therapy.

3614 Background: Neoadjuvant therapy (NAT) leads to a clinical complete response (cCR) in a significant proportion of patients with locally advanced rectal cancer (LARC) allowing for possible non-operative management. Along with physical exam and proctoscopy, magnetic resonance imaging (MRI) is used to evaluate for residual tumor following NAT. The presence of mucin on MRI leads to uncertainty about residual disease and appropriateness of watch-and-wait strategy (WW) in patients with no evidence of disease on proctoscopy (endoscopic cCR). We set out to determine the impact of radiographic mucin in patients with LARC after NAT. Methods: MRI reports between July 2016 to January 2020 at Memorial Sloan Kettering Cancer Center were queried for the presence of mucin in the tumor bed on post-treatment rectal MRI in patients with LARC following NAT. The clinicodemographic, pathologic, and outcomes data from these patients were compiled and analyzed. Results: Seventy-one patients were included in the final analysis who fit the pre-specified inclusion criteria (Table). Of the 71 patients with mucin present on post-treatment MRI, 19 patients (27%) entered a watch-and-wait (WW) strategy and 52 patients (73%) were planned for surgery (non-WW). Comparing the WW and non-WW cohorts, there was no difference in age, sex, clinical nodal status, or neoadjuvant regimen. Patients entering a WW protocol had a higher proportion of cT1-T2 tumors (32%) compared to non-WW (4%) (P &lt; 0.01). All WW patients had endoscopic cCR, while only one non-WW patient achieved endoscopic cCR. Of 52 non-WW patients, 49 underwent resection and 3 did not have surgery due to disease progression. The pathologic complete response (pCR) rate in the non-WW patients who underwent surgery was 10%. Of 19 WW patients, 4 experienced regrowth (21%), while 15 (79%) have no local regrowth, with a median follow up of 4.2 years (range 2.4-6.3 yrs). Two patients (11%) experienced distant failure. Conclusions: The presence of mucin after NAT for LARC should not necessarily preclude a WW strategy in otherwise appropriate candidates who achieve an endoscopic cCR. [Table: see text]

Rectal cancer update: postneoadjuvant staging

Over the last two decades, magnetic resonance imaging (MRI) has continuously been gaining influence in modern management of rectal cancer. Bringing morphological and functional features together improves the differentiation of responders from nonresponders, provides for accurate surgical planning, intensified radiation therapy regimes, and watch-and-wait strategies. Ashift from TNM staging towards risk stratification of rectal cancer patients, patient selection to increasingly individualized therapies, and intensified surveillance has contributed to the transformation of rectal MRI into atrue gamechanger.

MRI-based radiomic score increased mrTRG accuracy in predicting rectal cancer response to neoadjuvant therapy.

To develop a magnetic resonance imaging (MRI)-based radiomics score, i.e., "rad-score," and to investigate the performance of rad-score alone and combined with mrTRG in predicting pathologic complete response (pCR) in patients with locally advanced rectal cancer following neoadjuvant chemoradiation therapy. This retrospective study included consecutive patients with LARC who underwent neoadjuvant chemoradiotherapy followed by surgery from between July 2011 to November 2015. Volumes of interest of the entire tumor on baseline rectal MRI and of the tumor bed on restaging rectal MRI were manually segmented on T2-weighted images. The radiologist also provided the ymrTRG score on the restaging MRI. Radiomic score (rad-score) was calculated and optimal cut-off points for both mrTRG and rad-score to predict pCR were selected using Youden's J statistic. Of 180 patients (mean age = 63years; 60% men), 33/180 (18%) achieved pCR. High rad-score (> - 1.49) yielded an area under the curve (AUC) of 0.758, comparable to ymrTRG 1-2 which yielded an AUC of 0.759. The combination of high rad-score and ymrTRG 1-2 yielded a significantly higher AUC of 0.836 compared with ymrTRG 1-2 and high rad-score alone (p < 0.001). A logistic regression model incorporating both high rad-score and mrTRG 1-2 was built to calculate adjusted odds ratios for pCR, which was 4.85 (p < 0.001). Our study demonstrates that a rectal restaging MRI-based rad-score had comparable diagnostic performance to ymrTRG. Moreover, the combined rad-score and ymrTRG model yielded a significant better diagnostic performance for predicting pCR.

Magnifying endoscopy with narrow-band imaging and salvage endoscopic submucosal dissection of a locally advanced rectal adenocarcinoma after neoadjuvant chemoradiotherapy.

A 61-year-old man underwent colonoscopy because of bloody stools. Colonoscopy showed an elevated lesion of 25 × 15 mm about 3 cm from the anus ([Fig. 1 a]). Histological examination of the biopsy indicated that this was an adenocarcinoma. Endoscopic ultrasound (EUS) showed that the lesion was involving the muscularis propria. Computed tomography (CT) and rectal magnetic resonance imaging (MRI) resulted in a staging classification of T2N0M0.

Quantitative assessment of the microstructure of the mesorectum with different prognostic statuses by intravoxel incoherent motion diffusion-weighed magnetic resonance imaging

BackgroundThe mesorectum surrounding the rectum provides an ideal substrate for tumour spread. However, preoperative risk assessment is still an issue. This study aimed to investigate the microstructural features of mesorectum with different prognostic statuses by intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI).MethodsPatients with pathologically proven rectal adenocarcinoma underwent routine high-resolution rectal magnetic resonance imaging (MRI) and IVIM DWI sequences were acquired. The MRI-detected circumferential resection margin (mrCRM) and extramural vascular invasion (mrEMVI) were evaluated. IVIM parameters of the mesorectum adjacent to (MAT) and distant from (MDT) the tumour were measured and compared between and within the prognostic factor groups.ResultsThe positive mrCRM (pMAT < 0.001; pMDT = 0.013) and mrEMVI (pMAT = 0.001; pMDT < 0.001) groups demonstrated higher D values in the MAT and MDT than the corresponding negative groups. Conversely, the positive mrCRM (p = 0.001) and mrEMVI (p < 0.001) groups both demonstrated lower f values in the MAT. Similarly, in the self-comparison between the MAT and MDT in the above subgroups, D showed a significant difference in all subgroups (p < 0.001 for all), and f showed a significant difference in the positive mrCRM (p = 0.001) and mrEMVI (p = 0.002) groups. Moreover, the MAT displayed a higher D* in the positive mrCRM (p = 0.014), negative mrCRM (p = 0.009) and negative mrEMVI groups (p < 0.001).ConclusionThe microstructure of the mesorectum in patients with rectal cancer with poor prognostic status shows changes based on IVIM parameters. IVIM parameters might be promising imaging biomarkers for risk assessment of tumour spread in mesorectum preoperatively.

Deep Learning Model to Assist Pathological Complete Response Diagnosis in the Locally Advanced Rectal Cancer: A Prospective and Multicenter Study

<h3>Purpose/Objective(s)</h3> Previously, through extracting post-neoadjuvant treatment magnetic resonance imaging (MRI) features, we constructed a radiomics based deep learning model to identify pathological complete response (pCR) patients from non-pCR LARC patients. Here, we aim to investigate the power of this deep learning system in a prospective and multicenter clinical study (Clinical Trial. gov No. NCT04278274). <h3>Materials/Methods</h3> In this study, patients who are pathologically diagnosed rectal adenocarcinoma and MRI defined as locally advanced stage (II and III stages) will be enrolled. All patients will be treated with neoadjuvant chemoradiotherapy or chemotherapy, following TME surgery and adjuvant chemotherapy. The images of MRI will be collected after the neoadjuvant treatment. Further, based on the post-neoadjuvant treatment MRI, nine radiologists divided into three different levels will be employed to generate the predicted response ("predicted as pCR" vs. "predicted as non-pCR"). The diagnosis from radiologists was compared with a reference diagnosis from the deep learning system. If two diagnoses did not match, the radiologists could then choose to adhere to their own diagnosis or adopt the diagnosis from the deep learning system as the final diagnosis. Both the initial and final assisted diagnoses were recorded. Finally, the pathologic report of TME surgery specimen ("confirmed pCR" vs. "confirmed non-pCR") will be served as a standard. The prediction accuracy, specificity, sensitivity as well as the area under curve (AUC) of Receiver Operating Characteristic (ROC) curves of identifying the pCR candidates from non-pCR individuals of the radiologists will be calculated. <h3>Results</h3> From February 2020 to July 2021, 205 patients were recruited in the prospective study. The preliminary predictive performance in deep learning system yielded a maximum AUC (0.850), which was higher than that of the radiologists (0.750, <i>p</i> < 0.01). Furthermore, the deep learning system improved the pooled AUC of the radiologists from 0.750 when diagnosing without deep learning system to 0.830 after supporting by deep learning system (<i>p</i> < 0.05). <h3>Conclusion</h3> Promisingly, based on the present prospective, multicenter clinical study, our deep learning prediction system displayed a higher predictive power to identify pCR patient using post-neoadjuvant treatment MRI. Importantly, this deep learning system may function as a diagnosis supporter to radiologists, particularly to the junior physician. Hopefully, the final and detailed result could be shared at 2022 ASTRO meeting.

Predicting perineural invasion using histogram analysis of zoomed EPI diffusion-weighted imaging in rectal cancer.

To investigate the utility of histogram analysis of zoomed EPI diffusion-weighted imaging (DWI) for predicting the perineural invasion (PNI) status of rectal cancer (RC). This prospective study evaluated 94 patients diagnosed with histopathologically confirmed RC between July 2020 and July 2021. Patients underwent preoperative rectal magnetic resonance imaging (MRI) examinations, including the zoomed EPI DWI sequence. Ten whole-tumor histogram parameters of each patient were derived from zoomed EPI DWI. Reproducibility was evaluated according to the intra-class correlation coefficient (ICC). The association of the clinico-radiological and histogram features with PNI status was assessed using univariable analysis for trend and multivariable logistic regression analysis with β value calculation. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance. Forty-two patients exhibited positive PNI. The inter- and intraobserver agreements were excellent for the histogram parameters (all ICCs > 0.80). The maximum (p = 0.001), energy (p = 0.021), entropy (p = 0.021), kurtosis (p < 0.001), and skewness (p < 0.001) were significantly higher in the positive PNI group than in the negative PNI group. Multivariable analysis showed that higher MRI T stage [β = 2.154, 95% confidence interval (CI) 0.932-3.688; p = 0.002] and skewness (β = 0.779, 95% CI 0.255-1.382; p = 0.006) were associated with positive PNI. The model combining skewness and MRI T stage had an area under the ROC curve of 0.811 (95% CI 0.724-0.899) for predicting PNI status. Histogram parameters in zoomed EPI DWI can help predict the PNI status in RC.

Interobserver Reliability and the Sigmoid Takeoff-An Interobserver Study.

Simple SummaryColorectal cancer is the second most common cancer. The sigmoid takeoff is the landmark where the colon sigmoid curves toward the sacrum viewed from sagittal magnetic resonance imaging. We assessed the interobserver variability in the assessment of the anal verge and anorectal junction in patients diagnosed with rectal cancer using magnetic resonance imaging. Our data indicate that radiologists are excellent at pointing out if a colorectal tumour is above or beneath the takeoff landmark.Background: Colorectal cancer is the second most common cancer worldwide. The sigmoid takeoff is the landmark where the colon sigmoid curves toward the sacrum viewed from sagittal magnetic resonance imaging (MRI). The purpose of this study was to assess interobserver variability in the assessment of the anal verge and anorectal junction in patients diagnosed with rectal cancer on magnetic resonance imaging (MRI). Materials and Methods: The rectal MRI examinations were performed using a 1.5- or 3.0-tesla unit using an anterior coil and a standard scan protocol. Two senior radiologists assessed MRI scans from patients under investigation for rectal cancer. The two observers assessed the anal verge and takeoff in cm independently. Difference in agreement between the observers were evaluated using intraclass correlation (ICC) and graphically by Bland–Altman plots. Results: The study population (n = 122) included 68 (55.7%) female and 54 (44.3%) male subjects. The overall median age was 69.5 years (range 39–95 years). There was perfect agreement between the two observers when defining rectal tumor above or below the takeoff landmark. The reliability of measuring the distance from the anal verge to the sigmoid takeoff was 0.712. Conclusion: Overall, the study found a moderate reliability in assessing the location of the sigmoid takeoff, with a low difference in the distance measuring, as well as a good consensus concerning the determination of tumors in relation to the sigmoid takeoff. Routine implementation of this information within the report seems reasonable.

Pictorial essay on MRI local staging of rectal carcinoma: An easy approach.

Rectal cancer is common and accounts for more than one-third of colorectal tumors. It is associated with significant morbidity and mortality. Previously computed tomography scan is the key imaging modality in preoperative assessment to detect local invasion and distant metastasis. However, the advent of magnetic resonance imaging (MRI) has aided in local staging and prognosticates the outcome of rectal tumor. Here, the author briefly explains why rectal MRI has a comprehensive role and provides a simple and easy way in reporting an MRI rectal carcinoma, even for a non-radiologist.

An Unsupervised Learning Approach to 3D Rectal MRI Volume Registration

Accurate alignment of multi-session medical imaging is essential to the analysis of disease progression. By comparing the magnetic resonance imaging (MRI) data captured before and after a course of neoadjuvant chemoradiation (nCRT) treatment, physicians are able to evaluate the tumor response for further treatment of the disease. However, rectal MRI data captured in multi-session are often misaligned and not guaranteed to have one-to-one correspondence, making it challenging for physicians to observe the treatment response of tumor. To address this issue, we propose an unsupervised learning based volume registration framework, which enables accurate alignment even under a high degree of deformation between multi-session rectal data. Moreover, it works without the assumption of one-to-one correspondence between multi-session data, and hence is a general solution to rectal MRI volume registration. The experimental results show that the proposed registration framework accurately aligns rectal cancer images and outperforms other state-of-the-art methods in medical image registration. By providing accurate registration, it can potentially increase the efficiency and reduce the workload for physicians to evaluate the rectal tumor response to nCRT.

Histogram analysis based on multi-parameter MR imaging as a biomarker to predict lymph node metastasis in T3 stage rectal cancer

BackgroundPreoperative identification of rectal cancer lymph node status is crucial for patient prognosis and treatment decisions. Rectal magnetic resonance imaging (MRI) plays an essential role in the preoperative staging of rectal cancer, but its ability to predict lymph node metastasis (LNM) is insufficient. This study explored the value of histogram features of primary lesions on multi-parametric MRI for predicting LNM of stage T3 rectal carcinoma.MethodsWe retrospectively analyzed 175 patients with stage T3 rectal cancer who underwent preoperative MRI, including diffusion-weighted imaging (DWI) before surgery. 62 patients were included in the LNM group, and 113 patients were included in the non-LNM group. Texture features were calculated from histograms derived from T2 weighted imaging (T2WI), DWI, ADC, and T2 maps. Stepwise logistic regression analysis was used to screen independent predictors of LNM from clinical features, imaging features, and histogram features. Predictive performance was evaluated by receiver operating characteristic (ROC) curve analysis. Finally, a nomogram was established for predicting the risk of LNM.ResultsThe clinical, imaging and histogram features were analyzed by stepwise logistic regression. Preoperative carbohydrate antigen 199 level (p = 0.009), MRN stage (p < 0.001), T2WIKurtosis (p = 0.010), DWIMode (p = 0.038), DWICV (p = 0.038), and T2-mapP5 (p = 0.007) were independent predictors of LNM. These factors were combined to form the best predictive model. The model reached an area under the ROC curve (AUC) of 0.860, with a sensitivity of 72.8% and a specificity of 85.5%.ConclusionThe histogram features on multi-parametric MRI of the primary tumor in rectal cancer were related to LN status, which is helpful for improving the ability to predict LNM of stage T3 rectal cancer.