MR Imaging of Rectal Cancer

MRI-based radiomics features for prediction of pathological deterioration upgrading in rectal tumor

PURPOSE

Our aim is to develop and validate an MRI-based diagnostic model for predicting pathological deterioration upgrading in rectal tumor.

METHODS

This retrospective study included 158 eligible patients from January 2017 to November 2023. The patients were divided into a training group (n = 110) and a validation group (n = 48). Radiomics features were extracted from T2-weighted images to create a radiomics score model. Significant factors identified through multifactor analysis were used to develop the final clinical feature model. By combining these two models, an combined radiomics-clinical model was established. The model's performance was evaluated using Receiver Operating Characteristic (ROC) analysis and the Area Under the ROC Curve (AUC).

RESULTS

A total of 1197 features were extracted, with 11 features selected for calculating the radiomics score to establish the radiomics model. This model demonstrated good predictive performance for pathological upgrading in both the training and validation groups (AUC of 0.863 and 0.861, respectively). Clinical factors such as chief complaint and differential carcinoembryonic antigen levels showed statistical significance (P < 0.05). The clinical model, incorporating these factors, yielded AUC values of 0.669 and 0.651 for the training and validation groups, respectively. Furthermore, the radiomics-clinical combined model outperformed the individual models in predicting preoperative pathological upgrading in both the training and validation groups (AUC of 0.932 and 0.907, respectively).

CONCLUSIONS

A radiomics-clinical model, which combines clinical features with radiomics features based on MRI, can predict pathological deterioration upgrading in patients with rectal tumor and provide valuable insights for personalized treatment strategies.

Preoperative Noninvasive Evaluation of Tumor Budding in Rectal Cancer Using Multiparameter MRI Radiomics

RATIONALE AND OBJECTIVES

To assess the value of a multiparametric magnetic resonance imaging (MRI)-based model integrating radiomics features with clinical and MRI semantic features for preoperative evaluation of tumor budding (TB) in rectal cancer.

MATERIALS AND METHODS

A total of 120 patients with pathologically confirmed rectal cancer were retrospectively analyzed. The patients were randomized into training and validation cohorts in a 6:4 ratio. Radiomics features were extracted and selected from preoperative T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging (T1CE) sequences, after which the corresponding radiomics score (RS) was calculated, and the radiomics models (T2WI model, DWI model, and T1CE model) were constructed. Logistic regression analysis was selected to develop a combined model integrated RST2WI, RSDWI, RST1CE, and clinical and MRI semantic features. The efficacy of each model in diagnosing TB grade was observed by the receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was used to assess the clinical benefits of the models.

RESULTS

Seven features were extracted and selected from each T2WI, DWI, and T1CE sequence to calculate the corresponding RS and construct the corresponding radiomics model. MRI reported N stage was an independent risk factor for TB. The area under the ROC curve of the combined model was 0.961 and 0.891 in the training and validation cohorts, respectively. The combined model showed better performance than the other models. DCA showed that the net benefit of the combined model was better than that of the other models in the vast majority of threshold probabilities.

CONCLUSION

A combined model integrating radiomics features and MRI semantic features allows for noninvasive preoperative evaluation of TB grading in patients with rectal cancer.

Association Analysis Between Intratumoral and Peritumoral MRI Radiomics Features and Overall Survival of Neoadjuvant Therapy in Rectal Cancer

BACKGROUND

The use of peritumoral features to determine the survival time of patients with rectal cancer (RC) is still imprecise.

PURPOSE

To explore the correlation between intratumoral, peritumoral and combined features, and overall survival (OS).

STUDY TYPE

Retrospective.

POPULATION

One hundred sixty-six RC patients (53 women, 113 men; average age: 55 ± 12 years) who underwent radical resection after neoadjuvant therapy.

FIELD STRENGTH/SEQUENCE

3 T; T2WI sagittal, T1WI axial, T2WI axial with fat suppression, and high-resolution T2WI axial sequences, enhanced T1WI axial and sagittal sequences with fat suppression.

ASSESSMENT

Radiologist A segmented 166 patients, and radiologist B randomly segmented 30 patients. Intratumoral and peritumoral features were extracted, and features with good stability (ICC ≥0.75) were retained through intra-observer analysis. Seven classifiers, including Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest (RF), Extremely randomized trees (ET), eXtreme Gradient Boosting (XGBoost), and LightGBM (LGBM), were applied to select the classifier with the best performance. Next, the Rad-score of best classifier and the clinical features were selected to establish the models, thus, nomogram was built to identify the association with 1-, 3-, and 5-year OS.

STATISTICAL TESTS

LASSO, regression analysis, ROC, DeLong method, Kaplan-Meier curve. P < 0.05 indicated a significant difference.

RESULTS

Only Node (irregular tumor nodules in the surrounding mesentery) and ExtraMRF (lymph nodes outside the perirectal mesentery) were significantly different in 20 clinical features. Twelve intratumoral, 3 peritumoral, and 14 combined features related to OS were selected. LR, SVM, and RF classier showed the best efficacy in the intratumoral, peritumoral, and combined model, respectively. The combined model (AUC = 0.954 and 0.821) had better survival association than the intratumoral model (AUC = 0.833 and 0.813) and the peritumoral model (AUC = 0.824 and 0.687).

DATA CONCLUSION

The proposed peritumoral model with radiomics features may serve as a tool to improve estimated survival time.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 4.

Convolutional network denoising for acceleration of multi-shot diffusion MRI

Multi-shot echo planar imaging is a promising technique to reduce geometric distortions and increase spatial resolution in diffusion-weighted MRI (DWI), at the expense of increased scan time. Moreover, performing DWI in the body requires multiple repetitions to obtain sufficient signal-to-noise ratio, which further increases the scan time. This work proposes to reduce the number of repetitions and perform denoising of high b-value images using a convolutional network denoising trained on single-shot DWI to accelerate the acquisition of multi-shot DWI. Convolutional network denoising is demonstrated to accelerate the acquisition of 2-shot DWI by a factor of 4 compared to the clinical standard on patients with rectal cancer. Image quality was evaluated using qualitative scores from expert body radiologists between accelerated and non-accelerated acquisition. Additionally, the effect of convolutional network denoising on each image quality score was analyzed using a Wilcoxon signed-rank test. Convolutional network denoising would enable to increase the number of shots without increasing scan time for significant geometric artifact reduction and spatial resolution increase.

Biparametric versus Multiparametric Magnetic Resonance Imaging for Assessing Muscle Invasion in Bladder Urothelial Carcinoma with Variant Histology Using the Vesical Imaging-Reporting and Data System

BACKGROUND

The diagnostic performance of contrast medium-free biparametric magnetic resonance imaging (bpMRI; combining T2-weighted imaging [T2WI] and diffusion-weighted imaging [DWI]) for evaluating variant-histology urothelial carcinoma (VUC) remains unknown.

OBJECTIVE

To compare the diagnostic performance of bpMRI and multiparametric MRI (mpMRI; combining T2WI, DWI, and dynamic contrast-enhanced MRI]) for assessing muscle invasion of VUC.

DESIGN, SETTING, AND PARTICIPANTS

This multi-institution retrospective analysis included 118 patients with pathologically verified VUC who underwent bladder mpMRI before transurethral bladder tumor resection between 2010 and 2019.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Three board-certified radiologists separately evaluated two sets of images, set 1 (bpMRI) and set 2 (mpMRI), in accordance with the Vesical Imaging Reporting and Data System (VI-RADS). The histopathology results were utilized as a reference standard. Receiver operating characteristic curve analysis, Z test, and Wald test were used to assess diagnostic abilities.

RESULTS AND LIMITATIONS

Sixty-six (55.9%) and 52 (44.1%) of the 118 patients with VUC included in the analysis (mean age, 71 ± 10 yr; 88 men) had muscle-invasive bladder cancer (MIBC) and non-MIBC, respectively. For the diagnosis of MIBC, the areas under the curve for bpMRI were significantly smaller than those for mpMRI (0.870-0.884 vs 0.902-0.923, p < 0.05). The sensitivity of bpMRI was significantly lower than that of mpMRI for all readers with a VI-RADS cutoff score of 4 (65.2-66.7% vs 77.3-80.3%, p < 0.05). The specificity of bpMRI and mpMRI did not differ significantly for all readers (88.5-90.4 vs 88.5-92.3, p > 0.05). A limitation of the study is the limited sample size because of the rarity of VUC.

CONCLUSIONS

In patients with VUC, on applying VI-RADS, the diagnostic results of bpMRI were inferior to those of mpMRI for evaluating muscle invasion. Therefore, mpMRI-based methods are recommended for evaluating muscle invasiveness of VUC.

PATIENT SUMMARY

Contrast medium-free biparametric magnetic resonance imaging (bpMRI)-based Vesical Imaging Reporting and Data System (VI-RADS) can accurately diagnose pure urothelial carcinomas, similar to conventional multiparametric magnetic resonance imaging-based VI-RADS. However, bpMRI-based VI-RADS may misdiagnose muscle invasiveness of urothelial carcinoma with variant histology, particularly when its cutoff score is 4.

Biparametric magnetic resonance imaging-based radiomics features for prediction of lymphovascular invasion in rectal cancer

BACKGROUND

Preoperative assessment of lymphovascular invasion(LVI) of rectal cancer has very important clinical significance. However, accurate preoperative imaging evaluation of LVI is highly challenging because the resolution of MRI is still limited. Relatively few studies have focused on prediction of LVI of rectal cancer with the tool of radiomics, especially in patients with negative statue of MRI-based extramural vascular invasion (mrEMVI).The purpose of this study was to explore the preoperative predictive value of biparametric MRI-based radiomics features for LVI of rectal cancer in patients with the negative statue of mrEMVI.

METHODS

The data of 146 cases of rectal adenocarcinoma confirmed by postoperative pathology were retrospectively collected. In the cases, 38 had positive status of LVI. All patients were examined by MRI before the operation. The biparametric MRI protocols included T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI). We used whole-volume three-dimensional method and two feature selection methods, minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO), to extract and select the features. Logistics regression was used to construct models. The area under the receiver operating characteristic curve (AUC) and DeLong's test were used to evaluate the diagnostic performance of the radiomics based on T2WI and DWI and the combined models.

RESULTS

Radiomics models based on T2WI and DWI had good predictive performance for LVI of rectal cancer in both the training cohort and the validation cohort. The AUCs of the T2WI model were 0.87 and 0.87, and the AUCs of the DWI model were 0.94 and 0.92. The combined model was better than the T2WI model, with AUCs of 0.97 and 0.95. The predictive performance of the DWI model was comparable to that of the combined model.

CONCLUSIONS

The radiomics model based on biparametric MRI, especially DWI, had good predictive value for LVI of rectal cancer. This model has the potential to facilitate the clinical recognition of LVI in rectal cancer preoperatively.

A Dual-Energy CT Radiomics of the Regional Largest Short-Axis Lymph Node Can Improve the Prediction of Lymph Node Metastasis in Patients With Rectal Cancer

Objective

To explore the value of dual-energy computed tomography (DECT) radiomics of the regional largest short-axis lymph nodes for evaluating lymph node metastasis in patients with rectal cancer.

Materials and Methods

One hundred forty-one patients with rectal cancer (58 in LNM+ group, 83 in LNM- group) who underwent preoperative total abdominal DECT were divided into a training group and testing group (7:3 ratio). After post-processing DECT venous phase images, 120kVp-like images and iodine (water) images were obtained. The highest-risk lymph nodes were identified, and their long-axis and short-axis diameter and DECT quantitative parameters were measured manually by two experienced radiologists who were blind to the postoperative pathological results. Four DECT parameters were analyzed: arterial phase (AP) normalized iodine concentration, AP normalized effective atomic number, the venous phase (VP) normalized iodine concentration, and the venous phase normalized effective atomic number. The carcinoembryonic antigen (CEA) levels were recorded one week before surgery. Radiomics features of the largest lymph nodes were extracted, standardized, and reduced before modeling. Radomics signatures of 120kVp-like images (Rad-signature120kVp) and iodine map (Rad-signatureImap) were built based on Logistic Regression via Least Absolute Shrinkage and Selection Operator (LASSO).

Results

Eight hundred thirty-three features were extracted from 120kVp-like and iodine images, respectively. In testing group, the radiomics features based on 120kVp-like images showed the best diagnostic performance (AUC=0.922) compared to other predictors [CT morphological indicators (short-axis diameter (AUC=0.779, IDI=0.262) and long-axis diameter alone (AUC=0.714, IDI=0.329)), CEA alone (AUC=0.540, IDI=0.414), and normalized DECT parameters alone (AUC=0.504-0.718, IDI=0.290-0.476)](P&lt;0.05 in Delong test). Contrary, DECT iodine map-based radiomic signatures showed similar performance in predicting lymph node metastasis (AUC=0.866). The decision curve showed that the 120kVp-like-based radiomics signature has the highest net income.

Conclusion

Predictive model based on DECT and the largest short-axis diameter lymph nodes has the highest diagnostic value in predicting lymph node metastasis in patients with rectal cancer.

Is rectal filling optimal for MRI-based radiomics in preoperative T staging of rectal cancer?

PURPOSE

To determine whether rectal filling with ultrasound gel is clinically more beneficial in preoperative T staging of patients with rectal cancer (RC) using radiomics model based on magnetic resonance imaging (MRI).

METHODS

A total of 94 RC patients were assigned to cohort 1 (leave-one-out cross-validation [LOO-CV] set) and 230 RC patients were assigned to cohort 2 (test set). Patients were grouped according to different pathological T stages. The radiomics features were extracted through high-resolution T2-weighted imaging for all volume of interests in the two cohorts. Optimal features were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Model 1 (without rectal filling) and model 2 (with rectal filling) were constructed. LOO-CV was adopted for radiomics model building in cohort 1. Thereafter, the cohort 2 was used to test and verify the effectiveness of the two models.

RESULTS

Totally, 204 patients were enrolled, including 60 cases in cohort 1 and 144 cases in cohort 2. Finally, seven optimal features with LASSO were selected to build model 1 and nine optimal features were used for model 2. The ROC curves showed an AUC of 0.806 and 0.946 for model 1 and model 2 in cohort 1, respectively, and an AUC of 0.783 and 0.920 for model 1 and model 2 in cohort 2, respectively (p = 0.021).

CONCLUSION

The radiomics model with rectal filling showed an advantage for differentiating T1 + 2 from T3 and had less inaccurate categories in the test cohort, suggesting that this model may be useful for T-stage evaluation.

MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer

OBJECTIVE

To interrogate the mesorectal fat using MRI radiomics feature analysis in order to predict clinical outcomes in patients with locally advanced rectal cancer.

METHODS

This retrospective study included patients who underwent neoadjuvant chemoradiotherapy for locally advanced rectal cancer from 2009 to 2015. Three radiologists independently segmented mesorectal fat on baseline T2-weighted axial MRI. Radiomics features were extracted from segmented volumes and calculated using CERR software, with adaptive synthetic sampling being employed to combat large class imbalances. Outcome variables included pathologic complete response (pCR), local recurrence, distant recurrence, clinical T-category (cT), post-treatment T category (ypT), and post-treatment N category (ypN). A maximum of eight most important features were selected for model development using support vector machines and fivefold cross-validation to predict each outcome parameter via elastic net regularization. Diagnostic metrics of the final models were calculated, including sensitivity, specificity, PPV, NPV, accuracy, and AUC.

RESULTS

The study included 236 patients (54 ± 12 years, 135 men). The AUC, sensitivity, specificity, PPV, NPV, and accuracy for each clinical outcome were as follows: for pCR, 0.89, 78.0%, 85.1%, 52.5%, 94.9%, 83.9%; for local recurrence, 0.79, 68.3%, 80.7%, 46.7%, 91.2%, 78.3%; for distant recurrence, 0.87, 80.0%, 88.4%, 58.3%, 95.6%, 87.0%; for cT, 0.80, 85.8%, 56.5%, 89.1%, 49.1%, 80.1%; for ypN, 0.74, 65.0%, 80.1%, 52.7%, 87.0%, 76.3%; and for ypT, 0.86, 81.3%, 84.2%, 96.4%, 46.4%, 81.8%.

CONCLUSION

Radiomics features of mesorectal fat can predict pathological complete response and local and distant recurrence, as well as post-treatment T and N categories.

KEY POINTS

• Mesorectal fat contains important prognostic information in patients with locally advanced rectal cancer (LARC). • Radiomics features of mesorectal fat were significantly different between those who achieved complete vs incomplete pathologic response (accuracy 83.9%, 95% CI: 78.6-88.4%). • Radiomics features of mesorectal fat were significantly different between those who did vs did not develop local or distant recurrence (accuracy 78.3%, 95% CI: 72.0-83.7% and 87.0%, 95% CI: 81.6-91.2% respectively).

Abdominal and pelvic 18F-FDG PET/MR: a review of current and emerging oncologic applications

Positron emission tomography (PET) using fluorodeoxyglucose (¹⁸F-FDG) combined with magnetic resonance imaging (MR) is an emerging hybrid modality that has shown utility in evaluating abdominal and pelvic disease entities. Together, the high soft tissue contrast and metabolic/functional imaging capabilities make this modality ideal for oncologic imaging in many organ systems. Its clinical utility continues to evolve and future research will help solidify its role in oncologic imaging. In this manuscript, we aim to (1) provide an overview of the various PET/MR systems, describing the strengths and weaknesses of each system, and (2) review the oncologic applications for ¹⁸F-FDG PET/MR in the abdomen and pelvis.

Pretreatment MR-based radiomics nomogram as potential imaging biomarker for individualized assessment of perineural invasion status in rectal cancer

PURPOSE

To investigate whether pretreatment magnetic resonance (MR)-based radiomics nomogram can individualize prediction of perineural invasion (PNI) status in rectal cancer (RC).

MATERIAL AND METHODS

A total of 122 RC patients with pathologically confirmed were classified as training cohort (n = 87) and test cohort (n = 35). 180 radiomics features were extracted from all lesions based on oblique axial T₂WI TSE images. The dimensionality reduction and feature selection in training cohort were realized by the maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression model. A predictive model combining radiomics features and clinical risk factors (pathological N stage, pathological LVI status) was established by multivariate logistic regression analysis. The performance of the model was assessed based on its receiver operating characteristic (ROC) curve, nomogram, and calibration.

RESULTS

The developed radiomics nomogram that integrated the radiomics signature and clinical risk factors could provide discrimination in the training and test cohorts. The accuracy and the area under the curve (AUC) for assessing PNI status were 0.82, 0.86, respectively, in the training cohort, while they were 0.71 and 0.85 in the test cohort. The goodness-of-fit of the nomogram was evaluated using the Hosmer-Lemeshow test (p = 0.52 in training cohort and p = 0.24 in test cohort). Decision curve analysis (DCA) showed that the radiomics nomogram was clinically useful.

CONCLUSION

The developed radiomics nomogram might be helpful in the individualized assessment PNI status in patients with RC. This stratification of RC patients according to their PNI status may provide the basis for individualized adjuvant therapy, especially for stage II patients.

Hybrid imaging of the abdomen and pelvis

Accurate imaging is crucial for lesion detection in abdominal organs, for the noninvasive characterization of focal and diffuse abnormalities, and for surgical planning. To accomplish these tasks, several imaging modalities such as multidetector computer tomography (MDCT), magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) are used for abdominal imaging, providing important morphological, functional or metabolic information. More recently, PET/MRI has been gaining attention due to the possibility of combining high-resolution imaging with metabolic imaging. PET/MRI is a novel hybrid imaging technology that in the near future might play a pivotal role in the clinical management of oncologic and inflammatory abdominopelvic diseases. Despite the still limited number of published clinical studies, PET/MRI has been proven to be at least equivalent to PET/CT and to standalone MRI in a variety of oncologic disease. Moreover, in selected and focused clinical studies, it has been proven to outperform current standard of care imaging, for example, in evaluating cholangiocarcinomas, liver metastases, untreated and treated rectal cancer. This has also had an impact on therapeuticmanagement in some studies. Therefore in some institutions, including those of the authors, PET/MRI is becoming the new standard imaging modality in staging treatment-naïve intrahepatic massforming cholangiocarcinomas and prior to complicated hepatic surgery.

The value of intravoxel incoherent motion and diffusion kurtosis imaging in the assessment of tumor regression grade and T stages after neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer

PURPOSE

To evaluate the role of IVIM and diffusion kurtosis imaging (DKI) in identifying pathologic complete response (pCR) and T stages after neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC).

METHOD

Forty-two patients with biopsy-proven rectal adenocarcinoma, who underwent both pre-and post-CRT MRI with IVIM and DKI sequences on a 3 T scanner, were enrolled prospectively. According to the pathologic ypTNM stages and tumor regression grade (TRG), patients were grouped into pCR (TRG0) and non-pCR (TRG1-3) groups and low T stage (ypT0-2) and high T stage (ypT3-4) groups. IVIM parameters (the slow diffusion coefficient [D], fast diffusion coefficient [D*], perfusion fraction [f]), DKI parameters (mean diffusivity [MD] and mean kurtosis [MK]), and mono-exponential ADC were calculated and analyzed between groups.

RESULTS

The pCR group had significantly higher post-CRT ADC, D*, f, and MD values than non-pCR group, and higher percent changes in the ADC, f, and MD values (all P < 0.05). The post-CRT MD values yielded the highest AUC (0.788) with higher sensitivity than post-ADC values (82.9 % vs. 77.1 %, respectively). Post-CRT ADC and MD values and the percent changes in the ADC and MD values were also negatively correlated with TRG (all P < 0.05). Besides, negative correlations were found among the pre-CRT MD, post-CRT ADC, D, f, and MD values and the ypT stages (all P < 0.05).

CONCLUSIONS

Both IVIM and DKI parameters could provide more information when evaluating pCR and T stages after nCRT. In particular, the diagnostic performance of the MD values was more valuable than ADC values in being able to determine pCR.

Submucosal Enhancing Stripe as a Contrast Material-enhanced MRI-based Imaging Feature for the Differentiation of Stage T0-T1 from Early T2 Rectal Cancers

Background Accurate differentiation of stage T0-T1 rectal tumors from stage T2 rectal tumors facilitates the selection of appropriate surgical treatment. MRI is a recommended technique for local staging, but its ability to distinguish T1 from T2 tumors is poor. Purpose To explore the value of a submucosal enhancing stripe (SES), an uninterrupted enhancing band between the rectal tumor and the muscular layer on contrast material-enhanced T1-weighted images, as a potential imaging feature to differentiate T0-T1 from T2 rectal tumors. Materials and Methods This retrospective study included patients with pT0-T1 and pT2 rectal tumors who underwent pretreatment MRI and rectal tumor resection between January 2012 and November 2019. Two radiologists independently evaluated tumor characteristics (SES; status of muscularis propria [SMP]; and tumor shape, location, and size) at MRI. The associations of clinical and imaging characteristics with stage T0-T1 or T2 tumors were assessed, β values were calculated, and predictive models were built. The diagnostic accuracies for the differentiation of T0-T1 tumors from T2 tumors with SES and SMP were compared. Results Data from 431 patients (mean age, 60 years ± 10 [standard deviation]; 261 men) were evaluated. SES (β = 3.9; 95% CI: 3.1, 4.7; P < .001), SMP (β = 1.3; 95% CI: 0.7, 1.9; P < .001), and carpetlike shape (β = 1.6; 95% CI: 0.5, 2.8; P = .01) were independent factors distinguishing T0-T1 tumors from T2 tumors. The diagnostic accuracy was 87% (95% CI: 84, 90; 376 of 431) for SES and 67% (95% CI: 63, 72; 290 of 431) for SMP (P < .001). Conclusion Submucosal enhancing stripe (SES) at contrasted-enhanced MRI, status of muscularis propria (SMP) on T2-weighted images, and tumor shape can serve as independent imaging features to differentiate stage T0-T1 rectal tumors from stage T2 rectal tumors. Moreover, SES is a more accurate feature than is SMP. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Clinical value of high-resolution dynamic contrast-enhanced (DCE) MRI in diagnosis of cutaneous squamous cell carcinoma

BACKGROUND

While uncomplicated cases of skin squamous cell carcinoma (cSCC) can be treated with surgery topical therapy alone, more objective and non-invasive examination methods are needed to guide clinicians to make more detailed biopsy and surgical plans for lesions with atypical or subcutaneous growth. High-resolution magnetic resonance imaging (HR-MRI) is a novel skin imaging method.

MATERIALS AND METHODS

Prospective collection of 19 patients with clinically suspected cSCC. All patients underwent high-resolution DCE-MRI using a 70-mm microscopy coil before operation. The imaging features and results of surgical pathology were recorded. K^trans , K_ep , V_e values, and the time-signal curve (TIC) types were determined using DCE images.

RESULTS

16 cases of cSCC, 3 cases of acanthoma. The subcutaneous invasion of all lesions was clearly displayed, of which 8 lesions invaded the subcutaneous fat layer, 5 invaded the muscle layer, 1 invaded the periosteum, 2 invaded the cap fascia, and the layer of all lesions invasion judged by HR-MR imaging was consistent with the postoperative pathology. The main manifestations of cSCC were ill-defined margin, obvious inhomogeneous enhancement, higher perfusion parameters value and type-III TIC, while acanthoma showed well-defined and type-I TIC. Some imaging findings (such as boundary, enhancement) and DCE perfusion parameters of the two groups overlap.

CONCLUSION

High-resolution DCE-MRI can fully and directly display the subcutaneous invasion of cSCC, and more work needs to be done to prove its value. Next, we will expand the sample size, and further explore its value in the differential diagnosis and prognosis evaluation of cSCC from acanthoma or other skin tumors.

PET/MRI Radiomics in Rectal Cancer: a Pilot Study on the Correlation Between PET- and MRI-Derived Image Features with a Clinical Interpretation

PURPOSE

The aim of this study was to explore possible correlations among different imaging features from 2-deoxy-2-[¹⁸F]fluoro-D-Glucose positron emission tomography/magnetic resonance imaging (PET/MRI) in rectal cancer (RC).

PROCEDURES

RC patients who underwent PET/MRI were enrolled. A region of interest (ROI) was drawn around each primary RC on PET/MRI images (PET, pelvic axial T2w, and apparent diffusion coefficient maps (ADC)). Multiple imaging features were assessed, and Pearson's correlation was used to explore possible correlations among them.

RESULTS

A total of 13 patients were included, mean age 56.1 years old, 6 females. A strong inverse correlation was observed between SUVpeak and ADCmean values, MTV and T2 sphericity, MTV and ADC sphericity, MTV and T2 entropy, and TLG and ADC sphericity. There was also strong direct correlation between PET entropy and ADC sphericity.

CONCLUSIONS

In conclusion, several clinically relevant correlations were observed between PET and MRI imaging features. These findings show how the use of both modalities provides complementary information.

[Hybrid imaging of the abdomen and pelvis. German version]

Accurate imaging is crucial for lesion detection in abdominal organs, for the noninvasive characterization of focal and diffuse abnormalities, and for surgical planning. To accomplish these tasks, several imaging modalities such as multidetector computer tomography (MDCT), magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) are used for abdominal imaging, providing important morphological, functional or metabolic information. More recently, PET/MRI has been gaining attention due to the possibility of combining high-resolution imaging with metabolic imaging. PET/MRI is a novel hybrid imaging technology that in the near future might play a pivotal role in the clinical management of oncologic and inflammatory abdominopelvic diseases. Despite the still limited number of published clinical studies, PET/MRI has been proven to be at least equivalent to PET/CT and to stand-alone MRI in a variety of oncologic disease. Moreover, in selected and focused clinical studies, it has been proven to outperform current standard of care imaging, for example, in evaluating cholangiocarcinomas, liver metastases, untreated and treated rectal cancer. This has also had an impact on therapeutic management in some studies. Therefore in some institutions, including those of the authors, PET/MRI is becoming the new standard imaging modality in staging treatment-naïve intrahepatic mass-forming cholangiocarcinomas and prior to complicated hepatic surgery.

Imaging and Management of Rectal Cancer

High-resolution phased array external magnetic resonance imaging (MRI) is the first investigation of choice in rectal cancer for local staging, both in the primary and restaging situations. Use of MRI helps differentiate between those with good prognosis, which can be offered upfront surgery and the poor prognostic cases where treatment intensification is needed. MRI identified poor prognostic factors are threatened or involved mesorectal fascia, T3 tumors with >5 mm extramural spread, those with extramural vascular invasion, pelvic sidewall nodes and mucinous tumors. At restaging, use of MRI helps evaluate response and an MR tumor regression grading system is being evaluated. Complete response seen on clinical examination and endoscopy, needs confirmation on MRI using both T2-weighted and diffusion-weighted sequences to justify a "watch and wait" approach. In this subset of patients, MRI also plays a role in monitoring and detecting early regrowth. In those with partial response, MRI helps define surgical margins and can be used as a roadmap to decide between sphincter preserving surgeries and radical sphincter sacrificing surgeries; pelvic exenteration and pelvic sidewall lymph node dissection. Poor responders on MRI may benefit from adjuvant chemotherapy. Use of MRI thus helps in individualizing treatment in rectal cancer.

Pretreatment MR-Based Radiomics Signature as Potential Imaging Biomarker for Assessing the Expression of Topoisomerase II alpha (TOPO-IIα) in Rectal Cancer

BACKGROUND

Rectal cancer (RC) is one of the most common cancers throughout the world. Chemotherapy or neoadjuvant chemotherapy play an important role in the treatment of advanced RC. Whether to add topoisomerase inhibitor to individualized chemotherapy is a puzzling question for clinicians.

PURPOSE

To investigate whether pretreatment MR-based radiomics signature can assess the expression of topoisomerase II alpha (TOPO-IIα) in RC.

STUDY TYPE

Retrospective.

POPULATION

In all, 122 patients with RC. Field Strength/Sequence: Pretreatment 3.0T; T₂ WI turbo spin echo (TSE) sequence.

ASSESSMENT

A training group (n = 85) and a test group (n = 37) with pathologically confirmed RC. Patients underwent TOPO-IIα expression. A total of 180 radiomics features were extracted from oblique axial T₂ WI TSE images of the entire primary tumor. The least absolute shrinkage and selection operator (LASSO) regression model was used to reduce the dimension of the data and select the features.

STATISTICAL TESTS

The assessment models were established by multivariable logistic regression analysis. The performance of the model was assessed by the receiver operating characteristic (ROC) curve, nomogram, and calibration.

RESULTS

The radiomics signature, which consisted of 10 selected optimal features, was significantly associated with TOPO-IIα expression (P < 0.01 for both training and test groups). The area under the curve (AUC), the sensitivity, and the specificity for assessing TOPO-IIα expression, were 0.859, 0.872, and 0.739, respectively, in the training group, while they were 0.762, 0.941, and 0.600 in the test group. The nomogram model of the radiomics signature (Rad-score) had good calibration. Calibration curves were plotted to assess the calibration of the radiomics nomogram that was accompanied with the Hosmer-Lemeshow test (P = 0.52).

DATA CONCLUSION

The proposed pretreatment MR-based radiomics signature was associated with TOPO-IIα expression. A radiomics nomogram might be helpful in the individualized assessment of TOPO-IIα expression in patients with RC.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:1881-1889.

Rectal cancer MR staging: pearls and pitfalls at baseline examination

In recent years, rectal MRI has become a central diagnostic tool in rectal cancer staging. Indeed, rectal MR has the ability to accurately evaluate a number of important findings that may impact patient management, including distance of the tumor to the mesorectal fascia, presence of extramural vascular invasion (EMVI), presence of lymph nodes, and involvement of the peritoneum/anterior peritoneal reflection. Many of these findings are difficult to assess in nonexpert hands. In this review, we present a practical approach for radiologists to provide high-quality interpretations at initial baseline exams, based on recent guidelines from the Society of Abdominal Radiology, Rectal and Anal Cancer Disease Focused Panel. Practical pearls and pitfalls are discussed, focusing on optimization of technique including, patient preparation and protocol recommendations, interpretation, and essentials of reporting.

Rectal cancer lexicon: consensus statement from the society of abdominal radiology rectal & anal cancer disease-focused panel

Standardized terminology is critical to providing consistent reports to referring clinicians. This lexicon aims to provide a reference for terminology frequently used in rectal cancer and reflects the consensus of the Society of Abdominal Radiology Disease Focused Panel in Rectal cancer. This lexicon divided the terms into the following categories: primary tumor staging, nodal staging, treatment response, anal canal anatomy, general anatomy, and treatments.

Current controversy, confusion, and imprecision in the use and interpretation of rectal MRI

There has been a rapid increase in the utilization of MRI in rectal cancer staging in the USA essentially replacing endorectal ultrasound and mimicking the trend in Europe seen in the 1990s and 2000s. Accompanying this trend, there is a demand, and recognized need, for greater precision and clarification of confusing, misunderstood and poorly understood concepts, facts, statements and nomenclature regarding rectal cancer and the use of pelvic MRI for diagnosis. As such, this Review, part evidence-based and part expert opinion, will attempt to elucidate and clarify several concepts the authors have encountered in 25 years of imaging rectal cancer, focusing on MRI.

Diagnostic performance of magnetic resonance to assess treatment response after neoadjuvant therapy in patients with locally advanced rectal cancer

PURPOSE

Our study aimed to evaluate the diagnostic performance of rectal magnetic resonance imaging (MRI) for local restaging in patients with non-metastatic locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (CRT) using surgical histopathology of total mesorectal excision as the reference standard.

METHODS

Ninety-five patients with LARC who underwent rectal MRI after CRT between January 2014 and December 2016 were included. Accuracy, sensitivity, specificity, positive, and negative predictive value for local staging regarding T-stage, N-stage, circumferential resection margin, and MRI tumor regression grade (ymriTRG) were calculated, and inter-test agreements were assessed.

RESULTS

22/95 (23.2%) patients had radiological complete response (rCR), whereas 20/95 (21.1%) had pathological complete response (pCR). Among the patients with pCR, 11/20 (55%) had rCR. Fair agreement was demonstrated between ymriTRG and pathological TRG (ypTRG) (κ = 0.255). The sensitivity and specificity for detection of pCR were 61.1% (95% CI 35.7-82.7) and 89.6% (95% CI 80.6-95.4). For the detection of ypTRG grades 1 and 2, the corresponding values were 67.2% (95% CI 54.3-78.4) and 51.6 (95% CI 33.1-69.8). The accuracy of ymriTRG was 24.2% (95% CI 15.6-32.8). Inter-test agreement in TRG between MRI and pathology was overall fair (κ = 0.255) and slight (κ = 0.179), if TRG 1 + 2.

CONCLUSION

Qualitative assessment on MRI for diagnosing pCR showed moderate sensitivity and high specificity, whereas the diagnosis of TRG had moderate sensitivity and low specificity with slight to fair inter-test agreement when compared with pathological specimens.