An MRI Deep Learning Model Predicts Outcome in Rectal Cancer.

Background Deep learning (DL) models can potentially improve prognostication of rectal cancer but have not been systematically assessed. Purpose To develop and validate an MRI DL model for predicting survival in patients with rectal cancer based on segmented tumor volumes from pretreatment T2-weighted MRI scans. Materials and Methods DL models were trained and validated on retrospectively collected MRI scans of patients with rectal cancer diagnosed between August 2003 and April 2021 at two centers. Patients were excluded from the study if there were concurrent malignant neoplasms, prior anticancer treatment, incomplete course of neoadjuvant therapy, or no radical surgery performed. The Harrell C-index was used to determine the best model, which was applied to internal and external test sets. Patients were stratified into high- and low-risk groups based on a fixed cutoff calculated in the training set. A multimodal model was also assessed, which used DL model-computed risk score and pretreatment carcinoembryonic antigen level as input. Results The training set included 507 patients (median age, 56 years [IQR, 46-64 years]; 355 men). In the validation set (n = 218; median age, 55 years [IQR, 47-63 years]; 144 men), the best algorithm reached a C-index of 0.82 for overall survival. The best model reached hazard ratios of 3.0 (95% CI: 1.0, 9.0) in the high-risk group in the internal test set (n = 112; median age, 60 years [IQR, 52-70 years]; 76 men) and 2.3 (95% CI: 1.0, 5.4) in the external test set (n = 58; median age, 57 years [IQR, 50-67 years]; 38 men). The multimodal model further improved the performance, with a C-index of 0.86 and 0.67 for the validation and external test set, respectively. Conclusion A DL model based on preoperative MRI was able to predict survival of patients with rectal cancer. The model could be used as a preoperative risk stratification tool. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Langs in this issue.

Prevalent Pseudoprogression and Pseudoresidue in Patients With Rectal Cancer Treated With Neoadjuvant Immune Checkpoint Inhibitors.

BACKGROUND: Immune checkpoint inhibitor (ICI) treatment in patients with microsatellite instability-high/mismatch repair deficient (MSI-H/dMMR) tumors holds promise in reshaping organ preservation in rectal cancer. However, the benefits are accompanied by distinctive patterns of response, introducing a dilemma in the response evaluation for clinical decision-making. PATIENTS AND METHODS: Patients with locally advanced rectal cancer with MSI-H/dMMR tumors receiving neoadjuvant ICI (nICI) treatment (n=13) and matched patients receiving neoadjuvant chemoradiotherapy (nCRT; n=13) were included to compare clinical response and histopathologic features. RESULTS: Among the 13 patients receiving nICI treatment, in the final radiologic evaluation prior to surgery (at a median of 103 days after initiation of therapy), progressive disease (n=3), stable disease (n=1), partial response (n=7), and complete response (n=2) were observed. However, these patients were later confirmed as having pathologic complete response, resulting in pseudoprogression and pseudoresidue with incidences of 23.1% (n=3) and 76.9% (n=10), respectively, whereas no pseudoprogression was found in the 13 patients receiving nCRT. We further revealed the histopathologic basis underlying the pseudoprogression and pseudoresidue by discovering the distinctive immune-related regression features after nICI treatment, including fibrogenesis, dense lymphocytes, and plasma cell infiltration. CONCLUSIONS: Pseudoprogression and pseudoresidue were unique and prevalent response patterns in MSI-H/dMMR rectal cancer after nICI treatment. Our findings highlight the importance of developing specific strategies for response evaluation in neoadjuvant immunotherapy to identify patients with a good response in whom sphincter/organ-preserving or watch-and-wait strategies may be considered.

A Longitudinal MRI-Based Artificial Intelligence System to Predict Pathological Complete Response After Neoadjuvant Therapy in Rectal Cancer: A Multicenter Validation Study.

BACKGROUND: Accurate prediction of response to neoadjuvant chemoradiotherapy is critical for subsequent treatment decisions for patients with locally advanced rectal cancer. OBJECTIVE: To develop and validate a deep learning model based on the comparison of paired MRI before and after neoadjuvant chemoradiotherapy to predict pathological complete response. DESIGN: By capturing the changes from MRI before and after neoadjuvant chemoradiotherapy in 638 patients, we trained a multitask deep learning model for response prediction (DeepRP-RC) that also allowed simultaneous segmentation. Its performance was independently tested in an internal and 3 external validation sets, and its prognostic value was also evaluated. SETTINGS: Multicenter study. PATIENTS: We retrospectively enrolled 1201 patients diagnosed with locally advanced rectal cancer who underwent neoadjuvant chemoradiotherapy before total mesorectal excision. Patients had been treated at 1 of 4 hospitals in China between January 2013 and December 2020. MAIN OUTCOME MEASURES: The main outcome was the accuracy of predicting pathological complete response, measured as the area under receiver operating curve for the training and validation data sets. RESULTS: DeepRP-RC achieved high performance in predicting pathological complete response after neoadjuvant chemoradiotherapy, with area under the curve values of 0.969 (0.942-0.996), 0.946 (0.915-0.977), 0.943 (0.888-0.998), and 0.919 (0.840-0.997) for the internal and 3 external validation sets, respectively. DeepRP-RC performed similarly well in the subgroups defined by receipt of radiotherapy, tumor location, T/N stages before and after neoadjuvant chemoradiotherapy, and age. Compared with experienced radiologists, the model showed substantially higher performance in pathological complete response prediction. The model was also highly accurate in identifying the patients with poor response. Furthermore, the model was significantly associated with disease-free survival independent of clinicopathological variables. LIMITATIONS: This study was limited by its retrospective design and absence of multiethnic data. CONCLUSIONS: DeepRP-RC could be an accurate preoperative tool for pathological complete response prediction in rectal cancer after neoadjuvant chemoradiotherapy. UN SISTEMA DE IA BASADO EN RESONANCIA MAGNTICA LONGITUDINAL PARA PREDECIR LA RESPUESTA PATOLGICA COMPLETA DESPUS DE LA TERAPIA NEOADYUVANTE EN EL CNCER DE RECTO UN ESTUDIO DE VALIDACIN MULTICNTRICO: ANTECEDENTES:La predicción precisa de la respuesta a la quimiorradioterapia neoadyuvante es fundamental para las decisiones de tratamiento posteriores para los pacientes con cáncer de recto localmente avanzado.OBJETIVO:Desarrollar y validar un modelo de aprendizaje profundo basado en la comparación de resonancias magnéticas pareadas antes y después de la quimiorradioterapia neoadyuvante para predecir la respuesta patológica completa.DISEÑO:Al capturar los cambios de las imágenes de resonancia magnética antes y después de la quimiorradioterapia neoadyuvante en 638 pacientes, entrenamos un modelo de aprendizaje profundo multitarea para la predicción de respuesta (DeepRP-RC) que también permitió la segmentación simultánea. Su rendimiento se probó de forma independiente en un conjunto de validación interna y tres externas, y también se evaluó su valor pronóstico.ESCENARIO:Estudio multicéntrico.PACIENTES:Volvimos a incluir retrospectivamente a 1201 pacientes diagnosticados con cáncer de recto localmente avanzado y sometidos a quimiorradioterapia neoadyuvante antes de la escisión total del mesorrecto. Eran de cuatro hospitales en China en el período entre enero de 2013 y diciembre de 2020.PRINCIPALES MEDIDAS DE RESULTADO:Los principales resultados fueron la precisión de la predicción de la respuesta patológica completa, medida como el área bajo la curva operativa del receptor para los conjuntos de datos de entrenamiento y validación.RESULTADOS:DeepRP-RC logró un alto rendimiento en la predicción de la respuesta patológica completa después de la quimiorradioterapia neoadyuvante, con valores de área bajo la curva de 0,969 (0,942-0,996), 0,946 (0,915-0,977), 0,943 (0,888-0,998), y 0,919 (0,840-0,997) para los conjuntos de validación interna y las tres externas, respectivamente. DeepRP-RC se desempeñó de manera similar en los subgrupos definidos por la recepción de radioterapia, la ubicación del tumor, los estadios T/N antes y después de la quimiorradioterapia neoadyuvante y la edad. En comparación con los radiólogos experimentados, el modelo mostró un rendimiento sustancialmente mayor en la predicción de la respuesta patológica completa. El modelo también fue muy preciso en la identificación de los pacientes con mala respuesta. Además, el modelo se asoció significativamente con la supervivencia libre de enfermedad independientemente de las variables clinicopatológicas.LIMITACIONES:Este estudio estuvo limitado por el diseño retrospectivo y la ausencia de datos multiétnicos.CONCLUSIONES:DeepRP-RC podría servir como una herramienta preoperatoria precisa para la predicción de la respuesta patológica completa en el cáncer de recto después de la quimiorradioterapia neoadyuvante. (Traducción-Dr. Felipe Bellolio ).

A new magnetic resonance imaging tumour response grading scheme for locally advanced rectal cancer.

BACKGROUND: The potential of using magnetic resonance image tumour-regression grading (MRI-TRG) system to predict pathological TRG is debatable for locally advanced rectal cancer treated by neoadjuvant radiochemotherapy. METHODS: Referring to the American Joint Committee on Cancer/College of American Pathologists (AJCC/CAP) TRG classification scheme, a new four-category MRI-TRG system based on the volumetric analysis of the residual tumour and radiochemotherapy induced anorectal fibrosis was established. The agreement between them was evaluated by Kendall's tau-b test, while Kaplan-Meier analysis was used to calculate survival outcomes. RESULTS: In total, 1033 patients were included. Good agreement between MRI-TRG and AJCC/CAP TRG classifications was observed (k = 0.671). Particularly, as compared with other pairs, MRI-TRG 0 displayed the highest sensitivity [90.1% (95% CI: 84.3-93.9)] and specificity [92.8% (95% CI: 90.4-94.7)] in identifying AJCC/CAP TRG 0 category patients. Except for the survival ratios that were comparable between the MRI-TRG 0 and MRI-TRG 1 categories, any two of the four categories had distinguished 3-year prognosis (all P < 0.05). Cox regression analysis further proved that the MRI-TRG system was an independent prognostic factor (all P < 0.05). CONCLUSION: The new MRI-TRG system might be a surrogate for AJCC/CAP TRG classification scheme. Importantly, the system is a reliable and non-invasive way to identify patients with complete pathological responses.

GSH-Responsive Metal-Organic Framework for Intratumoral Release of NO and IDO Inhibitor to Enhance Antitumor Immunotherapy.

Immunotherapy brings great benefits for tumor therapy in clinical treatments but encounters the severe challenge of low response rate mainly because of the immunosuppressive tumor microenvironment. Multifunctional nanoplatforms integrating effective drug delivery and medical imaging offer tremendous potential for cancer treatment, which may play a critical role in combinational immunotherapy to overcome the immunosuppressive microenvironment for efficient tumor therapy. Here, a nanodrug (BMS-SNAP-MOF) is prepared using glutathione (GSH)-sensitive metal-organic framework (MOF) to encapsulate an immunosuppressive enzyme indoleamine 2,3-dioxygenase (IDO) inhibitor BMS-986205, and the nitric oxide (NO) donor s-nitrosothiol groups. The high T1 relaxivity allows magnetic resonance imaging to monitor nanodrug distribution in vivo. After the nanodrug accumulation in tumor tissue via the EPR effect and subsequent internalization into tumor cells, the enriched GSH therein triggers cascade reactions with MOF, which disassembles the nanodrug to rapidly release the IDO-inhibitory BMS-986205 and produces abundant NO. Consequently, the IDO inhibitor and NO synergistically modulate the immunosuppressive tumor microenvironment with increase CD8+ T cells and reduce Treg cells to result in highly effective immunotherapy. In an animal study, treatment using this theranostic nanodrug achieves obvious regressions of both primary and distant 4T1 tumors, highlighting its application potential in advanced tumor immunotherapy.

Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologists.

OBJECTIVES: Accurate evaluation of bowel fibrosis in patients with Crohn's disease (CD) remains challenging. Computed tomography enterography (CTE)-based radiomics enables the assessment of bowel fibrosis; however, it has some deficiencies. We aimed to develop and validate a CTE-based deep learning model (DLM) for characterizing bowel fibrosis more efficiently. METHODS: We enrolled 312 bowel segments of 235 CD patients (median age, 33 years old) from three hospitals in this retrospective study. A training cohort and test cohort 1 were recruited from center 1, while test cohort 2 from centers 2 and 3. All patients performed CTE within 3 months before surgery. The histological fibrosis was semi-quantitatively assessed. A DLM was constructed in the training cohort based on a 3D deep convolutional neural network with 10-fold cross-validation, and external independent validation was conducted on the test cohorts. The radiomics model (RM) was developed with 4 selected radiomics features extracted from CTE images by using logistic regression. The evaluation of CTE images was performed by two radiologists. DeLong's test and a non-inferiority test were used to compare the models' performance. RESULTS: DLM distinguished none-mild from moderate-severe bowel fibrosis with an area under the receiver operator characteristic curve (AUC) of 0.828 in the training cohort and 0.811, 0.808, and 0.839 in the total test cohort, test cohorts 1 and 2, respectively. In the total test cohort, DLM achieved better performance than two radiologists (*1 AUC = 0.579, *2 AUC = 0.646; both p < 0.05) and was not inferior to RM (AUC = 0.813, p < 0.05). The total processing time for DLM was much shorter than that of RM (p < 0.001). CONCLUSION: DLM is better than radiologists in diagnosing intestinal fibrosis on CTE in patients with CD and not inferior to RM; furthermore, it is more time-saving compared to RM. KEY POINTS: • Question Could computed tomography enterography (CTE)-based deep learning model (DLM) accurately distinguish intestinal fibrosis severity in patients with Crohn's disease (CD)? • Findings In this cross-sectional study that included 235 patients with CD, DLM achieved better performance than that of two radiologists' interpretation and was not inferior to RM with significant differences and much shorter processing time. • Meaning This DLM may accurately distinguish the degree of intestinal fibrosis in patients with CD and guide gastroenterologists to formulate individualized treatment strategies for those with bowel strictures.

Anatomical variations of the branches from left colic artery and middle colic artery at splenic flexure.

BACKGROUND: Variations of the vasculature at splenic flexure by left colic artery (LCA) and middle colic artery (MCA) remain ambiguous. OBJECTIVES: This study aim to investigate the anatomical variations of the branches from LCA and MCA at splenic flexure area. METHODS: Using ultra-thin CT images (0.5-mm thickness), we traced LCA and MCA till their merging site with paracolic marginal arteries through maximum intensity projection (MIP) reconstruction and computed tomography angiography (3D-CTA). RESULTS: A total of 229 cases were retrospectively enrolled. LCA ascending branch approached upwards till the distal third of the transverse colon in 37.6%, reached the splenic flexure in 37.6%, and reached the lower descending colon in 23.1%, and absent in 1.7% of the cases. Areas supplied by MCA left branch and aMCA were 33.2%, 44.5% and 22.3% in the proximal, middle and distal third of transverse colon of the cases, respectively. The accessory MCA separately originated from the superior mesenteric artery was found in 17.9% of the cases. Mutual correlation was found that, when the LCA ascending branch supplied the distal transverse colon, MCA left branch tended to feed the proximal transverse colon; when the LCA ascending branch supplied the lower part of descending colon, MCA left branch was more likely to feed the distal third of transverse colon. CONCLUSIONS: Vasculature at splenic flexure by LCA and MCA varied at specific pattern. This study could add more anatomical details for vessel management in surgeries for left-sided colon cancer.

Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer.

BACKGROUND: We aimed to develop a radiomic model based on pre-treatment computed tomography (CT) to predict the pathological complete response (pCR) in patients with rectal cancer after neoadjuvant treatment and tried to integrate our model with magnetic resonance imaging (MRI)-based radiomic signature. METHODS: This was a secondary analysis of the FOWARC randomized controlled trial. Radiomic features were extracted from pre-treatment portal venous-phase contrast-enhanced CT images of 177 patients with rectal cancer. Patients were randomly allocated to the primary and validation cohort. The least absolute shrinkage and selection operator regression was applied to select predictive features to build a radiomic signature for pCR prediction (rad-score). This CT-based rad-score was integrated with clinicopathological variables using gradient boosting machine (GBM) or MRI-based rad-score to construct comprehensive models for pCR prediction. The performance of CT-based model was evaluated and compared by receiver operator characteristic (ROC) curve analysis. The LR (likelihood ratio) test and AIC (Akaike information criterion) were applied to compare CT-based rad-score, MRI-based rad-score and the combined rad-score. RESULTS: We developed a CT-based rad-score for pCR prediction and a gradient boosting machine (GBM) model was built after clinicopathological variables were incorporated, with improved AUCs of 0.997 [95% CI 0.990-1.000] and 0.822 [95% CI 0.649-0.995] in the primary and validation cohort, respectively. Moreover, we constructed a combined model of CT- and MRI-based radiomic signatures that achieve better AIC (75.49 vs. 81.34 vs.82.39) than CT-based rad-score (P = 0.005) and MRI-based rad-score (P = 0.003) alone did. CONCLUSIONS: The CT-based radiomic models we constructed may provide a useful and reliable tool to predict pCR after neoadjuvant treatment, identify patients that are appropriate for a 'watch and wait' approach, and thus avoid overtreatment. Moreover, the CT-based radiomic signature may add predictive value to the MRI-based models for clinical decision making.

Tumor response as defined by iRECIST in gastrointestinal malignancies treated with PD-1 and PD-L1 inhibitors and correlation with survival.

BACKGROUND: Atypical tumor response patterns during immune checkpoint inhibitor therapy pose a challenge to clinicians and investigators in immuno-oncology practice. This study evaluated tumor burden dynamics to identify imaging biomarkers for treatment response and overall survival (OS) in advanced gastrointestinal malignancies treated with PD-1/PD-L1 inhibitors. METHODS: This retrospective study enrolled a total of 198 target lesions in 75 patients with advanced gastrointestinal malignancies treated with PD-1/PD-L1 inhibitors between January 2017 and March 2021. Tumor diameter changes as defined by immunotherapy Response Evaluation Criteria in Solid Tumors (iRECIST) were studied to determine treatment response and association with OS. RESULTS: Based on the best overall response, the tumor diameter ranged from - 100 to + 135.3% (median: - 9.6%). The overall response rate was 32.0% (24/75), and the rate of durable disease control for at least 6 months was 30.7% (23/75, one (iCR, immune complete response) or 20 iPR (immune partial response), or 2iSD (immune stable disease). Using univariate analysis, patients with a tumor diameter maintaining a < 20% increase (48/75, 64.0%) from baseline had longer OS than those with ≥20% increase (27/75, 36.0%) and, a reduced risk of death (median OS: 80 months vs. 48 months, HR = 0.22, P = 0.034). The differences in age (HR = 1.09, P = 0.01), combined surgery (HR = 0.15, P = 0.01) and cancer type (HR = 0.23, P = 0.001) were significant. In multivariable analysis, patients with a tumor diameter with a < 20% increase had notably reduced hazards of death (HR = 0.15, P = 0.01) after adjusting for age, combined surgery, KRAS status, cancer type, mismatch repair (MMR) status, treatment course and cancer differentiation. Two patients (2.7%) showed pseudoprogression. CONCLUSIONS: Tumor diameter with a < 20% increase from baseline during therapy in gastrointestinal malignancies was associated with therapeutic benefit and longer OS and may serve as a practical imaging marker for treatment response, clinical outcome and treatment decision making.

Preoperative radiomic signature based on multiparametric magnetic resonance imaging for noninvasive evaluation of biological characteristics in rectal cancer.

OBJECTIVES: To develop and validate radiomic models in evaluating biological characteristics of rectal cancer based on multiparametric magnetic resonance imaging (MP-MRI). METHODS: This study consisted of 345 patients with rectal cancer who underwent MP-MRI. We focused on evaluating five postoperative confirmed characteristics: lymph node (LN) metastasis, tumor differentiation, fraction of Ki-67-positive tumor cells, human epidermal growth factor receptor 2 (HER-2), and KRAS-2 gene mutation status. Data from 197 patients were used to develop the biological characteristics evaluation models. Radiomic features were extracted from MP-MRI and then refined for reproducibility and redundancy. The refined features were investigated for usefulness in building radiomic signatures by using two feature-ranking methods (MRMR and WLCX) and three classifiers (RF, SVM, and LASSO). Multivariable logistic regression was used to build an integrated evaluation model combining radiomic signatures and clinical characteristics. The performance was evaluated using an independent validation dataset comprising 148 patients. RESULTS: The MRMR and LASSO regression produced the best-performing radiomic signatures for evaluating HER-2, LN metastasis, tumor differentiation, and KRAS-2 gene status, with AUC values of 0.696 (95% CI, 0.610-0.782), 0.677 (95% CI, 0.591-0.763), 0.720 (95% CI, 0.621-0.819), and 0.651 (95% CI, 0.539-0.763), respectively. The best-performing signatures for evaluating Ki-67 produced an AUC value of 0.699 (95% CI, 0.611-0.786), and it was developed by WLCX and RF algorithm. The integrated evaluation model incorporating radiomic signature and MRI-reported LN status had improved AUC of 0.697 (95% CI, 0.612-0.781). CONCLUSION: Radiomic signatures based on MP-MRI have potential to noninvasively evaluate the biological characteristics of rectal cancer. KEY POINTS: • Radiomic features were extracted from MP-MRI images of the rectal tumor. • The proposed radiomic signatures demonstrated discrimination ability in identifying the histopathological, immunohistochemical, and genetic characteristics of rectal cancer. • All MRI sequences were important and could provide complementary information in radiomic analysis.

Clinical Anastomotic Leakage After Rectal Cancer Resection Can Be Predicted by Pelvic Anatomic Features on Preoperative MRI Scans: A Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: We demonstrated previously that radiation proctitis induced by preoperative radiotherapy is a predisposing factor for clinical anastomotic leakage in patients undergoing rectal cancer resection. Quantitative measurement of radiation proctitis is needed. OBJECTIVE: This study aimed to quantitate the changes of anatomic features caused by preoperative radiotherapy for rectal cancer and evaluate its ability to predict leakage. DESIGN: It was a secondary analysis of a randomized controlled trial (NCT01211210). MRI variables were retrospectively assessed. SETTINGS: The study was conducted in the leading center of the trial, which is a tertiary GI hospital. PATIENTS: Patients undergoing preoperative chemoradiation with sphincter-preserving surgery were included. MAIN OUTCOME MEASURES: Anatomic features were measured by preradiotherapy and postradiotherapy MRI. Univariate analyses were used to identify prognostic factors. Receiver operating characteristic curves were constructed to determine the cutoff value of the changes of MRI variables in predicting leakage. RESULTS: Eighteen (14.4%) of the 125 included patients developed clinical anastomotic leakage. Baseline characteristics were comparable between leakage group and nonleakage group. Relative increments of width of presacral space, thickness of rectal wall, and distal end of sigmoid colon discriminate between the 2 groups better than random chance. Relative increments of width of presacral space was the best performing predictor, with area under the curve of 0.722, sensitivity of 66.7%, specificity of 72.0%, and positive and negative predictive value of 28.6% and 92.8%. LIMITATIONS: The study was limited by its small sample size and retrospective design. CONCLUSIONS: Increments of the width of the presacral space, thickness of rectal wall, and distal part of the sigmoid colon helps to identify individuals not at risk for clinical anastomotic leakage after rectal cancer resection. The first variable is the strongest predictor. Changes of these variables should be taken into consideration when evaluating the application of defunctioning stoma. See Video Abstract at http://links.lww.com/DCR/B23. CLINICAL TRIALS IDENTIFIER: NCT1211210. LAS FUGAS ANASTOMÓTICAS CLÍNICAS DESPUÉS DE LA RESECCIÓN DEL CÁNCER DEL RECTO PUEDEN PREDECIRSE POR LAS CARACTERÍSTICAS ANATÓMICAS PÉLVICAS EN LAS IMAGENES DE RESONANCIA MAGNÉTICA PREOPERATORIA: UN ANÁLISIS SECUNDARIO DE UN ESTUDIO CONTROLADO ALEATORIZADO:: Anteriormente demostramos que la proctitis inducida por la radiación de radioterapia preoperatoria es un factor predisponente para la fuga anastomótica clínica en pacientes sometidos a resección de cáncer rectal. Es necesaria la medición cuantitativa de la proctitis por radiación.Este estudio tuvo como objetivo cuantificar los cambios en las características anatómicas causados por la radioterapia preoperatoria para el cáncer de recto y evaluar su capacidad para predecir las fugas anastomoticas.Fue un análisis secundario de un estudio controlado aleatorio (NCT01211210). Los variables de imagines de resonancia magnetica se evaluaron retrospectivamente.Se llevó a cabo en el centro principal del estudio, que es un hospital gastrointestinal terciario.Se incluyeron pacientes sometidos a quimiorradiación preoperatoria con cirugía conservadora del esfínter.Las características anatómicas se midieron mediante imagines de resonancia magnetica previa y posterior a la radioterapia. Se utilizaron análisis univariados para identificar los factores pronósticos. Las curvas de características operativas del receptor se construyeron para determinar el valor de corte de los cambios de los variables de resonancia magnetica en la predicción de fugas.Dieciocho (14.4%) de los 125 pacientes incluidos desarrollaron fugas anastomóticas clínicas. Las características basales fueron comparables entre el grupo de fugas y el grupo de no fugas. Los incrementos relativos del ancho del espacio presacro, el grosor de la pared rectal y distal del colon sigmoide discriminan entre los dos grupos mejor que la posibilidad aleatoria. Los incrementos relativos del ancho del espacio presacro fueron el mejor pronóstico con un AUC de 0.722, sensibilidad del 66.7%, especificidad del 72.0%, valor predictivo positivo y negativo del 28.6% y 92.8%.Estaba limitado por el tamaño de muestra pequeño y el diseño retrospectivo.Los incrementos en el ancho del espacio presacro, el grosor de la pared rectal y la parte distal del colon sigmoide ayudan a identificar a las personas que no tienen riesgo de fuga anastomótica clínica después de la resección del cáncer rectal. La primera variable es el predictor más fuerte. Los cambios de estos variables deben tenerse en cuenta al evaluar la aplicación del estoma para desvio. Vea el Resumen del Video en http://links.lww.com/DCR/B23.

Generation of functional hepatocyte-like cells from human bone marrow mesenchymal stem cells by overexpression of transcription factor HNF4α and FOXA2.

BACKGROUND: Our previous study showed that overexpression of hepatocyte nuclear factor 4α (HNF4α) could directly promote mesenchymal stem cells (MSCs) to differentiate into hepatocyte-like cells. However, the efficiency of hepatic differentiation remains low. The purpose of our study was to establish an MSC cell line that overexpressed HNF4α and FOXA2 genes to obtain an increased hepatic differentiation efficiency and hepatocyte-like cells with more mature hepatocyte functions. METHODS: Successful establishment of high-level HNF4α and FOXA2 co-overexpression in human induced hepatocyte-like cells (hiHep cells) was verified by flow cytometry, immunofluorescence and RT-PCR. Measurements of albumin (ALB), urea, glucose, indocyanine green (ICG) uptake and release, cytochrome P450 (CYP) activity and gene expression were used to analyze mature hepatic functions of hiHep cells. RESULTS: hiHep cells efficiently express HNF4α and FOXA2 genes and proteins, exhibit typical epithelial morphology and acquire mature hepatocyte-like cell functions, including ALB secretion, urea production, ICG uptake and release, and glycogen storage. hiHep cells can be activated by CYP inducers. The percentage of both ALB and α-1-antitrypsin (AAT)-positive cells was approximately 72.6%. The expression levels of hepatocyte-specific genes (ALB, AAT, and CYP1A1) and liver drug transport-related genes (ABCB1, ABCG2, and SLC22A18) in hiHep cells were significantly higher than those in MSCs-Vector cells. The hiHep cells did not form tumors after subcutaneous xenograft in BALB/c nude mice after 2 months. CONCLUSION: This study provides an accessible, feasible and efficient strategy to generate hiHep cells from MSCs.

Improvement of ablative margins by the intraoperative use of CEUS-CT/MR image fusion in hepatocellular carcinoma.

BACKGROUND: To assess whether intraoperative use of contrast-enhanced ultrasound (CEUS)-CT/MR image fusion can accurately evaluate ablative margin (AM) and guide supplementary ablation to improve AM after hepatocellular carcinoma (HCC) ablation. METHODS: Ninety-eight patients with 126 HCCs designated to undergo thermal ablation treatment were enrolled in this prospective study. CEUS-CT/MR image fusion was performed intraoperatively to evaluate whether 5-mm AM was covered by the ablative area. If possible, supplementary ablation was applied at the site of inadequate AM. The CEUS image quality, the time used for CEUS-CT/MR image fusion and the success rate of image fusion were recorded. Local tumor progression (LTP) was observed during follow-up. Clinical factors including AM were examined to identify risk factors for LTP. RESULTS: The success rate of image fusion was 96.2% (126/131), and the duration required for image fusion was 4.9 ± 2.0 (3-13) min. The CEUS image quality was good in 36.1% (53/147) and medium in 63.9% (94/147) of the cases. By supplementary ablation, 21.8% (12/55) of lesions with inadequate AMs became adequate AMs. During follow-up, there were 5 LTPs in lesions with inadequate AMs and 1 LTP in lesions with adequate AMs. Multivariate analysis showed that AM was the only independent risk factor for LTP (hazard ratio, 9.167; 95% confidence interval, 1.070-78.571; p = 0.043). CONCLUSION: CEUS-CT/MR image fusion is feasible for intraoperative use and can serve as an accurate method to evaluate AMs and guide supplementary ablation to lower inadequate AMs.

Contrast-Enhanced Sonography for Diagnosing Collateral Transformation of the Hepatic Artery After Liver Transplantation.

OBJECTIVES: To determine the contrast-enhanced sonographic features of hepatic artery collateral transformation in patients with hepatic artery complications after liver transplantation. METHODS: Ninety-nine liver transplant recipients who underwent contrast-enhanced sonography were recruited from April 2004 to May 2014. The reference standards were conventional angiography and computed tomographic angiography. The contrast-enhanced sonographic features of the hepatic artery in patients with and without collateral arteries were retrospectively analyzed. RESULTS: All 15 patients with hepatic artery collateral transformation had hepatic artery thrombosis (10 of 15) or hepatic artery stenosis (5 of 15). The collateral artery detection rate on contrast-enhanced sonography was 100%. The peripheral hepatic artery could not be visualized by contrast-enhanced sonography in most of the patients with hepatic artery collateral transformation (14 of 15). Additionally, many small tortuous collateral arteries in the porta hepatis region were visualized during the arterial and early portal phases, showing reticulated/patchy (15 of 15) and striped (3 of 15) enhancement patterns on contrast-enhanced sonography. CONCLUSIONS: Collateral transformation of the hepatic artery in patients with hepatic artery complications after liver transplantation appears to have characteristic features on contrast-enhanced sonography, especially a reticulated or patchy enhancement pattern in the porta hepatis region during the arterial and early portal phases combined with the absence of the peripheral hepatic artery. Contrast-enhanced sonography may be a novel method for diagnosing hepatic artery collateral transformation, which may be a highly specific sign of hepatic artery thrombosis or stenosis.

Hepatocellular carcinoma with portal vein tumor thrombus: treatment with transarterial chemoembolization combined with sorafenib--a retrospective controlled study.

PURPOSE: To determine the safety and efficacy of transarterial chemoembolization (TACE) combined with sorafenib (hereafter, TACE-sorafenib) in patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT). MATERIALS AND METHODS: This study was approved by the institutional review board, and the requirement for informed consent was waived. The medical records of consecutive patients with HCC and PVTT who underwent TACE-sorafenib or TACE alone from January 2010 to December 2012 were retrospectively evaluated. Sorafenib (400 mg) was administered twice daily. Outcomes of patients who underwent TACE-sorafenib were compared with outcomes of patients who underwent TACE by using the Kaplan-Meier method according to types of PVTT: PVTT in the main portal vein (type A), PVTT in the first-order portal vein branch (type B), and PVTT in second- or lower-order portal vein branches (type C). RESULTS: Ninety-one patients were included in the analysis; 46 patients underwent TACE-sorafenib and 45 underwent TACE. TACE-sorafenib showed significant survival benefits compared with TACE in patients with type B (median survival, 13 months vs 6 months; P = .002) or type C (median survival, 15 months vs 10 months; P = .003) PVTT. TACE-sorafenib and main PVTT were the independent prognostic factors for survival at uni- and multivariate analysis. Liver function after TACE-sorafenib worsened only in patients with main PVTT. Sorafenib-related adverse events of grade 3 or higher occurred in 16 patients (35%). CONCLUSION: TACE-sorafenib side effects were acceptable, and this treatment may improve overall survival in patients with HCC with first-order or lower-branch PVTT when compared with patients who underwent TACE alone.

[Multifunctional nano-vector for gene delivery into human adipose derived mesenchymal stem cells and in vitro cellular magnetic resonance imaging].

OBJECTIVE: To examine the feasibility and efficacy of using superparamagnetic iron oxide nanoparticles coated with polyethylene glycol-grafted polyethylenimine (PEG-g-PEI-SPION) as a carrier for gene delivery into human adipose derived mesenchymal stem cells (hADMSCs) and in vitro cellular magnetic resonance imaging (MRI). METHODS: PEG-g-PEI-SPION was synthesized as previously reported. Gel electrophoresis was performed to assess the pDNA condensation capacity of PEG-g-PEI-SPION. The particle size and zeta potential of PEG-g-PEI-SPION/pDNA complexes were determined by dynamic light scattering. Cytotoxicity of PEG-g-PEI-SPION was evaluated by CCK-8 assay with hADMSCs. Gene transfection efficiency of PEG-g-PEI-SPION in hADMSCs was quantified by flow cytometry. The cellular internalization of PEG-g-PEI-SPION/pDNA nanocomplexes was studied by confocal laser scanning microscopy and Prussian blue staining. MRI function of PEG-g-PEI-SPION was studied by in vitro cellular MRI scanning. RESULTS: PEG-g-PEI-SPION condensed pDNA to form stable complexes of 80-100 nm in diameter and showed low cytotoxicity in hADMSCs. At the optimal N/P ratio of 20, PEG-g-PEI-SPION/pDNA obtained the highest transfection efficiency of 22.8% ± 3.6% in hADMSCs. And it was higher than that obtained with lipofectamine 11.2% ± 2.6% (P < 0.05). Furthermore, hADMSCs labeled with PEG-g-PEI-SPION showed sensitive low signal intensity on MRI T2-weighted images in vitro. CONCLUSION: PEG-g-PEI-SPION is an efficient and MRI-visible nano-vector for gene delivery into hADMSCs.

Residual abnormalities on CTE predict adverse outcomes in Crohn's disease with endoscopic healing.

BACKGROUND: Residual abnormalities on computed tomography enterography (CTE) in Crohn's disease (CD) with endoscopic healing (EH) may have prognostic implications and affect therapeutic strategy. METHODS: CD patients with EH who underwent CTE between March 2015 and June 2022 were enrolled. CTE findings of the terminal ileum and the most severe segment of colon at the time of EH were assessed respectively for each patient. Cox regression analysis and Kaplan-Meier curves were used to evaluate the association between residual abnormalities and adverse outcomes. RESULTS: A total of 140 patients (217 digestive segments) were included. Mesenteric edema (hazard ratio [HR] = 3.61, 95% CI = 1.81-7.20, P<0.001), fibrofatty proliferation (HR = 3.40, 95% CI = 1.97-5.85, P<0.001) and active small bowel inflammation (HR = 2.74, 95% CI = 1.59-4.71, P<0.001) were risk factors for clinical relapse. Furthermore, we built a scoring system using the three parameters. Radiologic score ≥ 1 was the best threshold to predict clinical relapse (HR = 4.56, 95% CI = 2.54-8.19, P<0.001) and it was validated in different outcomes. CONCLUSION: The scoring system based on three residual abnormalities on CTE can predict adverse outcomes in CD patients with EH.

A computed tomography-based multitask deep learning model for predicting tumour stroma ratio and treatment outcomes in patients with colorectal cancer: a multicentre cohort study.

BACKGROUND: Tumour-stroma interactions, as indicated by tumour-stroma ratio (TSR), offer valuable prognostic stratification information. Current histological assessment of TSR is limited by tissue accessibility and spatial heterogeneity. The authors aimed to develop a multitask deep learning (MDL) model to noninvasively predict TSR and prognosis in colorectal cancer (CRC). MATERIALS AND METHODS: In this retrospective study including 2268 patients with resected CRC recruited from four centres, the authors developed an MDL model using preoperative computed tomography (CT) images for the simultaneous prediction of TSR and overall survival. Patients in the training cohort ( n =956) and internal validation cohort (IVC, n =240) were randomly selected from centre I. Patients in the external validation cohort 1 (EVC1, n =509), EVC2 ( n =203), and EVC3 ( n =360) were recruited from other three centres. Model performance was evaluated with respect to discrimination and calibration. Furthermore, the authors evaluated whether the model could predict the benefit from adjuvant chemotherapy. RESULTS: The MDL model demonstrated strong TSR discrimination, yielding areas under the receiver operating curves (AUCs) of 0.855 (95% CI, 0.800-0.910), 0.838 (95% CI, 0.802-0.874), and 0.857 (95% CI, 0.804-0.909) in the three validation cohorts, respectively. The MDL model was also able to predict overall survival and disease-free survival across all cohorts. In multivariable Cox analysis, the MDL score (MDLS) remained an independent prognostic factor after adjusting for clinicopathological variables (all P <0.05). For stage II and stage III disease, patients with a high MDLS benefited from adjuvant chemotherapy [hazard ratio (HR) 0.391 (95% CI, 0.230-0.666), P =0.0003; HR=0.467 (95% CI, 0.331-0.659), P <0.0001, respectively], whereas those with a low MDLS did not. CONCLUSION: The multitask DL model based on preoperative CT images effectively predicted TSR status and survival in CRC patients, offering valuable guidance for personalized treatment. Prospective studies are needed to confirm its potential to select patients who might benefit from chemotherapy.

miR-122 targets NOD2 to decrease intestinal epithelial cell injury in Crohn's disease.

Crohn's disease (CD) is one of the two major types of inflammatory bowel disease (IBD) thought to be caused by genetic and environmental factors. Recently, miR-122 was found to be deregulated in association with CD progression. However, the underlying molecular mechanisms remain unclear. In the present study, the gene nucleotide-binding oligomerization domain 2 (NOD2/CARD15), which is strongly associated with susceptibility to CD, was identified as a functional target of miR-122. MiR-122 inhibited LPS-induced apoptosis by suppressing NOD2 in HT-29 cells. NOD2 interaction with LPS initiates signal transduction mechanisms resulting in the activation of nuclear factor κB (NF-κB) and the stimulation of downstream pro-inflammatory events. The activation of NF-κB was inhibited in LPS-stimulated HT-29 cells pretreated with miR-122 precursor or NOD2 shRNA. The expression of the pro-inflammatory cytokines TNF-α and IFN-γ was significantly decreased, whereas therelease of the anti-inflammatory cytokines IL-4 and IL-10 was increased in LPS-stimulated HT-29 cells pretreated with miR-122 precursor, NOD2 shRNA or the NF-κB inhibitor QNZ. Taken together, these results indicate that miR-122 and its target gene NOD2 may play an important role in the injury of intestinal epithelial cells induced by LPS.

Percutaneous transsplenic portal vein catheterization: technical procedures, safety, and clinical applications.

PURPOSE: To evaluate the safety and feasibility of percutaneous transsplenic portal vein catheterization (PTSPC) by retrospective review of its use in patients with portal vein (PV) occlusion. MATERIALS AND METHODS: From July 2004 to December 2010, 46 patients with a history of uncontrolled gastroesophageal variceal bleeding secondary to portal hypertension underwent endovascular PV interventions via a percutaneous transsplenic approach. All patients had occlusion of the main PV or central intrahepatic PV branches, which prevented the performance of a transhepatic approach. A vein within the splenic parenchyma was punctured under fluoroscopic guidance by referencing preoperative computed tomography images. PTSPC-related complications and clinical applications were analyzed. RESULTS: PTSPC was successfully performed in 44 of 46 patients (96%); two failures were caused by inaccessible small intrasplenic veins. PTSPC-related major bleeding complications occurred in three patients (6.5%), including large intraperitoneal hemorrhage in one patient and large splenic subcapsular hemorrhage in two patients. Two of the three patients developed hypotension, and one developed severe anemia. All three of the patients required blood transfusions. PTSPC-related minor bleeding complications occurred in six patients (13%) as a result of a small splenic subcapsular hemorrhage. In addition, three patients exhibited mild left pleural effusion, which subsided spontaneously 1 week later. All 44 patients successfully treated via PTSPC received gastroesophageal variceal embolization. Eight patients received PV stents, five for treatment of PV occlusion and three during transjugular intrahepatic portosystemic shunt placement. CONCLUSIONS: PTSPC is a safe and effective access for endovascular PV interventions in patients without a transhepatic window.