Total Neoadjuvant Therapy With PD-1 Blockade for High-Risk Proficient Mismatch Repair Rectal Cancer

Importance

Total neoadjuvant therapy (TNT) is the standard treatment for locally advanced rectal cancer, especially for patients with high-risk factors. However, the efficacy of TNT combined with immunotherapy for patients with proficient mismatch repair (pMMR) rectal cancer is unknown.

Objectives

To evaluate the safety and efficacy of TNT with induction chemoimmunotherapy followed by long-course chemoradiation in patients with high-risk, pMMR rectal cancer and to identify potential molecular biomarkers associated with treatment efficacy.

Design, Setting, and Participants

This cohort study was a single-arm phase 2 trial conducted at Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, from June 2020 to October 2021. Biopsies and plasma were collected before treatment for whole-exome sequencing and cell-free DNA sequencing, respectively. Data were analyzed from May 2022 to September 2022.

Interventions

Participants received 3 cycles of induction oxaliplatin and capecitabine combined with camrelizumab and radiotherapy (50.6 Gy in 22 fractions) with concurrent capecitabine. Patients without disease progression received 2 cycles of consolidation oxaliplatin/capecitabine.

Main Outcomes and Measures

The primary end point was pathologic complete response rate.

Results

Of 25 patients enrolled (19 men [76%]; 6 women [24%]; median [IQR] age, 58 [48-64] years), 22 patients (88%) completed the TNT schedule. The pathologic complete response rate was 33.3% (7/21). Twelve patients (48%) achieved clinical complete response, and 4 patients (16%) chose to watch and wait. R0 resection was achieved in 21 of 21 patients, and the major pathologic response rate was 38.1% (8/21). The most common adverse event was nausea (80%, 20/25); grade 3 toxic effects occurred in 9 of 25 patients (36%). Patients with tumor shrinkage of 50% or greater after induction oxaliplatin/capecitabine and camrelizumab or clinical complete response had higher percentages of LRP1B mutation. Mutation of LRP1B was associated with high tumor mutation burden and tumor neoantigen burden. Patients with high tumor mutation burden all benefited from therapy.

Conclusions and Relevance

This study found that TNT with induction chemoimmunotherapy followed by long-course chemoradiation was safe and effective for patients with high-risk rectal cancer with pMMR status. Longer follow-up and larger clinical studies are needed to validate this innovative regimen. There is also an urgent need to further validate the predictive value of LRP1B and discover other novel biomarkers with potential predictive value for rectal cancer.

A comparative study of mono-exponential and advanced diffusion-weighted imaging in differentiating stage IA endometrial carcinoma from benign endometrial lesions

PURPOSE

The purpose of the current investigation is to compare the efficacy of different diffusion models and diffusion kurtosis imaging (DKI) in differentiating stage IA endometrial carcinoma (IAEC) from benign endometrial lesions (BELs).

METHODS

Patients with IAEC, endometrial hyperplasia (EH), or a thickened endometrium confirmed between May 2016 and August 2022 were retrospectively enrolled. All of the patients underwent a preoperative pelvic magnetic resonance imaging (MRI) examination. The apparent diffusion coefficient (ADC) from the mono-exponential model, pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) from the bi-exponential model, distributed diffusion coefficient (DDC), water molecular diffusion heterogeneity index from the stretched-exponential model, diffusion coefficient (Dk) and diffusion kurtosis (K) from the DKI model were calculated. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic efficiency.

RESULTS

A total of 90 patients with IAEC and 91 patients with BELs were enrolled. The values of ADC, D, DDC and Dk were significantly lower and D* and K were significantly higher in cases of IAEC (p < 0.05). Multivariate analysis showed that K was the only predictor. The area under the ROC curve of K was 0.864, significantly higher compared with the ADC (0.601), D (0.811), D* (0.638), DDC (0.743) and Dk (0.675). The sensitivity, specificity and accuracy of K were 78.89%, 85.71% and 80.66%, respectively.

CONCLUSION

Advanced diffusion-weighted imaging models have good performance for differentiating IAEC from EH and endometrial thickening. Among all of the diffusion parameters, K showed the best performance and was the only independent predictor. Diffusion kurtosis imaging was defined as the most valuable model in the current context.

Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework

PURPOSE

Rectal tumor segmentation on post neoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) has great significance for tumor measurement, radiomics analysis, treatment planning, and operative strategy. In this study, we developed and evaluated segmentation potential exclusively on post-chemoradiation T2-weighted MRI using convolutional neural networks, with the aim of reducing the detection workload for radiologists and clinicians.

METHODS

A total of 372 consecutive patients with LARC were retrospectively enrolled from October 2015 to December 2017. The standard-of-care neoadjuvant process included 22-fraction intensity-modulated radiation therapy and oral capecitabine. Further, 243 patients (3061 slices) were grouped into training and validation datasets with a random 80:20 split, and 41 patients (408 slices) were used as the test dataset. A symmetric eight-layer deep network was developed using the nnU-Net Framework, which outputs the segmentation result with the same size. The trained deep learning (DL) network was examined using fivefold cross-validation and tumor lesions with different TRGs.

RESULTS

At the stage of testing, the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD) were applied to quantitatively evaluate the performance of generalization. Considering the test dataset (41 patients, 408 slices), the average DSC, HD95, and MSD were 0.700 (95% CI: 0.680-0.720), 17.73 mm (95% CI: 16.08-19.39), and 3.11 mm (95% CI: 2.67-3.56), respectively. Eighty-two percent of the MSD values were less than 5 mm, and fifty-five percent were less than 2 mm (median 1.62 mm, minimum 0.07 mm).

CONCLUSIONS

The experimental results indicated that the constructed pipeline could achieve relatively high accuracy. Future work will focus on assessing the performances with multicentre external validation.

Early Contrast-Enhanced MR for Diagnosing Complete Tumor Response of Locally Advanced Esophageal Squamous Cell Carcinoma After Neoadjuvant Therapy: A Retrospective Comparative Study

BACKGROUND

This study assessed the performance of early contrast-enhanced magnetic resonance (ECE-MR) in the detecting of complete tumor response (ypT0) in patients with esophageal squamous cell carcinoma following neoadjuvant therapy.

PATIENTS AND METHODS

Preoperative MR images of consecutive patients who underwent neoadjuvant therapy and surgical resection were reviewed retrospectively. The accuracy of ECE-MR and T2WI+DWI was evaluated by comparing the findings with pathological results. Receiver operating characteristic curve analysis was used to assess the diagnostic performance, and DeLong method was applied to compare the areas under the curves (AUC). Chi-squared analysis was conducted to explore the difference in pathological changes.

RESULTS

A total of 198 patients (mean age 62.6 ± 7.8 years, 166 men) with 201 lesions were included. The AUC of ECE-MR was 0.85 (95% CI 0.79-0.90) for diagnosing ypT1-4, which was significantly higher than that of T2WI+DWI (AUC 0.69, 95% CI 0.63-0.76, p < 0.001). The diagnostic performance of both T2WI+DWI and ECE-MR improved with increasing tumor stage. The AUCs of ECE-MRI were higher in ypT1 and ypT2 tumors than T2WI+DWI. Degree 2-3 tumor-infiltrating lymphocytes and neutrophils were commonly seen in ypT0 tumors misdiagnosed by ECE-MR.

CONCLUSIONS

Visual evaluation of ECE-MR is a promising diagnostic protocol for the detection of complete tumor response, especially for differentiation with early stage tumors. The accurate diagnosis of complete tumor response after neoadjuvant therapy using imaging modalities is of important significance for clinical decision-making for patients with esophageal squamous cell carcinoma. It is hoped that early contrast-enhanced MR will provide supportive advice for the development of individualized treatment options for patients.

Extranodal Extension at Pretreatment MRI and the Prognostic Value for Patients with Rectal Cancer

Background Detection of extranodal extension (ENE) at pathology is a poor prognostic indicator for rectal cancer, but whether ENE can be identified at pretreatment MRI is, to the knowledge of the authors, unknown. Purpose To evaluate the performance of pretreatment MRI in detecting ENE using a matched pathologic reference standard and to assess its prognostic value in patients with rectal cancer. Materials and Methods This single-center study included a prospective development data set consisting of participants with rectal adenocarcinoma who underwent pretreatment MRI and radical surgery (December 2021 to January 2023). MRI characteristics were identified by their association with ENE-positive nodes (χ2 test and multivariable logistic regression) and the performance of these MRI features was assessed (area under the receiver operating characteristic curve [AUC]). Interobserver agreement was assessed by Cohen κ coefficient. The prognostic value of ENE detected with MRI for predicting 3-year disease-free survival was assessed by Cox regression analysis in a retrospective independent validation cohort of patients with locally advanced rectal cancer (December 2019 to July 2020). Results The development data set included 147 participants (mean age, 62 years ± 11 [SD]; 87 male participants). The retrospective cohort included 110 patients (mean age, 60 years ± 9; 79 male participants). Presence of vessel interruption and fusion (both P < .001), heterogeneous internal structure, and the broken-ring and tail signs (odds ratio range, 4.10-23.20; P value range, <.001 to .002) were predictors of ENE at MRI, and together achieved an AUC of 0.91 (95% CI: 0.88, 0.93) in detecting ENE. Interobserver agreement was moderate for the presence of vessel interruption and fusion (κ = 0.46 for both) and substantial for others (κ = 0.61-0.67). The presence of ENE at pretreatment MRI was independently associated with worse 3-year disease-free survival (hazard ratio, 3.00; P = .02). Conclusion ENE can be detected at pretreatment MRI, and its presence was associated with worse prognosis for patients with rectal cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Eberhardt in this issue.

Resting state functional connectome in breast cancer patients with fear of cancer recurrence

This study aimed to investigate network-level brain functional changes in breast cancer patients and their relationship with fear of cancer recurrence (FCR). Resting-state functional MRI was collected from 43 patients with breast cancer and 40 healthy controls (HCs). Graph theory analyses, whole-brain voxel-wise functional connectivity strength (FCS) analyses and seed-based functional connectivity (FC) analyses were performed to identify connection alterations in breast cancer patients. Correlations between brain functional connections (i.e. FCS and FC) and FCR level were assessed to further reveal the neural mechanisms of FCR in breast cancer patients. Graph theory analyses indicated a decreased clustering coefficient in breast cancer patients compared to HCs (P = 0.04). Patients with breast cancer exhibited significantly higher FCS in both higher-order function networks (frontoparietal, default mode, and dorsal attention systems) and primary somatomotor networks. Among the hyperconnected regions in breast cancer, the left inferior frontal operculum demonstrated a significant positive correlation with FCR. Our findings suggest that breast cancer patients exhibit less segregation of brain function, and the left inferior frontal operculum is a key region associated with FCR. This study offers insights into the neural mechanisms of FCR in breast cancer patients at the level of brain connectome.

Peri-lesion regions in differentiating suspicious breast calcification-only lesions specifically on contrast enhanced mammography

PURPOSE

The explore the added value of peri-calcification regions on contrast-enhanced mammography (CEM) in the differential diagnosis of breast lesions presenting as only calcification on routine mammogram.

METHODS

Patients who underwent CEM because of suspicious calcification-only lesions were included. The test set included patients between March 2017 and March 2019, while the validation set was collected between April 2019 and October 2019. The calcifications were automatically detected and grouped by a machine learning-based computer-aided system. In addition to extracting radiomic features on both low-energy (LE) and recombined (RC) images from the calcification areas, the peri-calcification regions, which is generated by extending the annotation margin radially with gradients from 1 mm to 9 mm, were attempted. Machine learning (ML) models were built to classify calcifications into malignant and benign groups. The diagnostic matrices were also evaluated by combing ML models with subjective reading.

RESULTS

Models for LE (significant features: wavelet-LLL_glcm_Imc2_MLO; wavelet-HLL_firstorder_Entropy_MLO; wavelet-LHH_glcm_DifferenceVariance_CC; wavelet-HLL_glcm_SumEntropy_MLO;wavelet-HLH_glrlm_ShortRunLowGray LevelEmphasis_MLO; original_firstorder_Entropy_MLO; original_shape_Elongation_MLO) and RC (significant features: wavelet-HLH_glszm_GrayLevelNonUniformityNormalized_MLO; wavelet-LLH_firstorder_10Percentile_CC; original_firstorder_Maximum_MLO; wavelet-HHH_glcm_Autocorrelation_MLO; original_shape_Elongation_MLO; wavelet-LHL_glszm_GrayLevelNonUniformityNormalized_MLO; wavelet-LLH_firstorder_RootMeanSquared_MLO) images were set up with 7 features. Areas under the curve (AUCs) of RC models are significantly better than those of LE models with compact and expanded boundary (RC v.s. LE, compact: 0.81 v.s. 0.73, p <  0.05; expanded: 0.89 v.s. 0.81, p <  0.05) and RC models with 3 mm boundary extension yielded the best performance compared to those with other sizes (AUC = 0.89). Combining with radiologists' reading, the 3mm-boundary RC model achieved a sensitivity of 0.871 and negative predictive value of 0.937 with similar accuracy of 0.843 in predicting malignancy.

CONCLUSIONS

The machine learning model integrating intra- and peri-calcification regions on CEM has the potential to aid radiologists' performance in predicting malignancy of suspicious breast calcifications.

Value of multiple models of diffusion-weighted imaging to predict hepatic lymph node metastases in colorectal liver metastases patients

BACKGROUND

About 10%-31% of colorectal liver metastases (CRLM) patients would concomitantly show hepatic lymph node metastases (LNM), which was considered as sign of poor biological behavior and a relative contraindication for liver resection. Up to now, there's still lack of reliable preoperative methods to assess the status of hepatic lymph nodes in patients with CRLM, except for pathology examination of lymph node after resection.

AIM

To compare the ability of mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) models in distinguishing between benign and malignant hepatic lymph nodes in patients with CRLM who received neoadjuvant chemotherapy prior to surgery.

METHODS

In this retrospective study, 97 CRLM patients with pathologically confirmed hepatic lymph node status underwent magnetic resonance imaging, including DWI with ten b values before and after chemotherapy. Various parameters, such as the apparent diffusion coefficient from the mono-exponential model, and the true diffusion coefficient, the pseudo-diffusion coefficient, and the perfusion fraction derived from the intravoxel incoherent motion model, along with distributed diffusion coefficient (DDC) and α from the stretched-exponential model (SEM), were measured. The parameters before and after chemotherapy were compared between positive and negative hepatic lymph node groups. A nomogram was constructed to predict the hepatic lymph node status. The reliability and agreement of the measurements were assessed using the coefficient of variation and intraclass correlation coefficient.

RESULTS

Multivariate analysis revealed that the pre-treatment DDC value and the short diameter of the largest lymph node after treatment were independent predictors of metastatic hepatic lymph nodes. A nomogram combining these two factors demonstrated excellent performance in distinguishing between benign and malignant lymph nodes in CRLM patients, with an area under the curve of 0.873. Furthermore, parameters from SEM showed substantial repeatability.

CONCLUSION

The developed nomogram, incorporating the pre-treatment DDC and the short axis of the largest lymph node, can be used to predict the presence of hepatic LNM in CRLM patients undergoing chemotherapy before surgery. This nomogram was proven to be more valuable, exhibiting superior diagnostic performance compared to quantitative parameters derived from multiple b values of DWI. The nomogram can serve as a preoperative assessment tool for determining the status of hepatic lymph nodes and aiding in the decision-making process for surgical treatment in CRLM patients.

The differential diagnosis of lung precursor glandular lesions, micro-invasive adenocarcinoma, and invasive adenocarcinoma using low dose spectral computed tomography perfusion imaging

Background

Few studies about the association between computed tomography (CT) perfusion imaging parameters and invasiveness in lung adenocarcinoma (LUAD) have been conducted using low dose spectral CT perfusion imaging. The purpose of this study was to investigate application of spectral revolution CT low-dose perfusion imaging in the differential diagnosis of different pathological subtypes of LUAD.

Methods

This was a cross-sectional study based on historical data from January 2018 to May 2019 in Peking University Cancer Hospital & Institute. A total of 62 cases were enrolled, including 2 cases of atypical adenomatous hyperplasia (AAH), 3 cases of adenocarcinoma in situ (AIS), 4 cases of minimally invasive adenocarcinoma (MIA), and 53 cases of invasive adenocarcinoma (IAC), all confirmed with pathology. The inclusion and exclusion criteria were regulated. Using Revolution low-dose CT perfusion imaging (GE, USA), the CT perfusion parameters of hemodynamics were obtained: blood flow (BF), blood volume (BV), impulse residue function time of arrival (IRF TO), maximum slope of increase (MSI), mean transit time (MTT), permeability surface area product (PS), positive enhancement integral (PEI), and maximum enhancement time (Tmax). Univariate analysis of variance (ANOVA) or Kruskal-Wallis test was used to compare the differences of CT perfusion quantitative parameters among AAH, AIS, MIA, and IAC. Mann-Whitney test was used to compare the difference of CT perfusion imaging parameters between preinvasive lesions (AAH and AIS) and invasive lung cancer (MIA and IAC).

Results

Statistically significant differences in IRF TO were observed in LUAD with different invasiveness, namely, among AIS, MIA, and IAC groups (0.56±0.74 vs. 0.54±1.08 vs. 4.39±2.19, P=0.004). Statistically significant differences in IRF TO were also observed between pre-invasive lesions group (AAH and AIS) and invasive lung cancer group (MIA and IAC) (1.12±1.27 vs. 3.75±2.79, P=0.031), and between AAH + AIS + MIA groups and IAC group (0.83±1.13 vs. 4.12±2.69, P<0.001). There were no statistically significant differences in other CT perfusion parameters of hemodynamics among different pathological subtypes of LUAD (P>0.05).

Conclusions

The low-dose perfusion parameter IRF TO of revolution CT has the potential to be employed in the differential diagnosis of different pathological subtypes of LUAD.

Small arteriole sign: an imaging feature for staging T4a colon cancer

OBJECTIVES

By analyzing the distribution of existing and newly proposed staging imaging features in pT1-3 and pT4a tumors, we searched for a salient feature and validated its diagnostic performance.

METHODS

Preoperative multiphase contrast-enhanced CT images of the training cohort were retrospectively collected at three centers from January 2016 to December 2017. We used the chi-square test to analyze the distribution of several stage-related imaging features in pT1-3 and pT4a tumors, including small arteriole sign (SAS), outer edge of the intestine, tumor invasion range, and peritumoral adipose tissue. Preoperative multiphase contrast-enhanced CT images of the validation cohort were retrospectively collected at Beijing Cancer Hospital from January 2018 to December 2018. The diagnostic performance of the selected imaging feature, including accuracy, sensitivity, and specificity, was validated and compared with the conventional clinical tumor stage (cT) by the McNemar test.

RESULTS

In the training cohort, a total of 268 patients were enrolled, and only SAS was significantly different between pT1-3 and pT4a tumors. The accuracy, sensitivity, and specificity of the SAS and conventional cT in differentiating T1-3 and T4a tumors were 94.4%, 81.6%, and 97.3% and 53.7%, 32.7%, and 58.4%, respectively (all p < 0.001). In the validation cohort, a total of 135 patients were collected. The accuracy, sensitivity, and specificity of the SAS and the conventional cT were 93.3%, 76.2%, and 96.5% and 62.2%, 38.1%, and 66.7%, respectively (p < 0.001, p = 0.021, p < 0.001).

CONCLUSION

Small arteriole sign positivity, an indirect imaging feature of serosa invasion, may improve the accuracy of identifying T4a colon cancer.

CLINICAL RELEVANCE STATEMENT

Small arteriole sign helps to distinguish T1-3 and T4a colon cancer and further improves the accuracy of preoperative CT staging of colon cancer.

KEY POINTS

• The accuracy of preoperative CT staging of colon cancer is not ideal, especially for T4a tumors. • Small arteriole sign (SAS) is a newly defined imaging feature that shows the appearance of tumor-supplying arterioles at the site where they penetrate the intestine wall. • SAS is an indirect imaging marker of tumor invasion into the serosa with a great value in distinguishing between T1-3 and T4a colon cancer.

Radiomics analysis from magnetic resonance imaging in predicting the grade of nonfunctioning pancreatic neuroendocrine tumors: a multicenter study

OBJECTIVES

To explore the potential of radiomics features to predict the histologic grade of nonfunctioning pancreatic neuroendocrine tumor (NF-PNET) patients using non-contrast sequence based on MRI.

METHODS

Two hundred twenty-eight patients with NF-PNETs undergoing MRI at 5 centers were retrospectively analyzed. Data from center 1 (n = 115) constituted the training cohort, and data from centers 2-5 (n = 113) constituted the testing cohort. Radiomics features were extracted from T2-weighted images and the apparent diffusion coefficient. The least absolute shrinkage and selection operator was applied to select the most important features and to develop radiomics signatures. The area under receiver operating characteristic curve (AUC) was performed to assess models.

RESULTS

Tumor boundary, enhancement homogeneity, and vascular invasion were used to construct the radiological model to stratify NF-PNET patients into grade 1 and 2/3 groups, which yielded AUC of 0.884 and 0.684 in the training and testing groups. A radiomics model including 4 features was constructed, with an AUC of 0.941 and 0.871 in the training and testing cohorts. The fusion model combining the radiomics signature and radiological characteristics showed good performance in the training set (AUC = 0.956) and in the testing set (AUC = 0.864), respectively.

CONCLUSION

The developed model that integrates radiomics features with radiological characteristics could be used as a non-invasive, dependable, and accurate tool for the preoperative prediction of grade in NF-PNETs.

CLINICAL RELEVANCE STATEMENT

Our study revealed that the fusion model based on a non-contrast MR sequence can be used to predict the histologic grade before operation. The radiomics model may be a new and effective biological marker in NF-PNETs.

KEY POINTS

The diagnostic performance of the radiomics model and fusion model was better than that of the model based on clinical information and radiological features in predicting grade 1 and 2/3 of nonfunctioning pancreatic neuroendocrine tumors (NF-PNETs). Good performance of the model in the four external testing cohorts indicated that the radiomics model and fusion model for predicting the grades of NF-PNETs were robust and reliable, indicating the two models could be used in the clinical setting and facilitate the surgeons' decision on risk stratification. The radiomics features were selected from non-contrast T2-weighted images (T2WI) and diffusion-weighted imaging (DWI) sequence, which means that the administration of contrast agent was not needed in grading the NF-PNETs.

Prediction of the lymphatic, microvascular, and perineural invasion of pancreatic neuroendocrine tumors using preoperative magnetic resonance imaging

BACKGROUND

Significant correlation between lymphatic, microvascular, and perineural invasion (LMPI) and the prognosis of pancreatic neuroendocrine tumors (PENTs) was confirmed by previous studies. There was no previous study reported the relationship between magnetic resonance imaging (MRI) parameters and LMPI.

AIM

To determine the feasibility of using preoperative MRI of the pancreas to predict LMPI in patients with non-functioning PENTs (NFPNETs).

METHODS

A total of 61 patients with NFPNETs who underwent MRI scans and lymphadenectomy from May 2011 to June 2018 were included in this retrospective study. The patients were divided into group 1 (n = 34, LMPI negative) and group 2 (n = 27, LMPI positive). The clinical characteristics and qualitative MRI features were collected. In order to predict LMPI status in NF-PNETs, a multivariate logistic regression model was constructed. Diagnostic performance was evaluated by calculating the receiver operator characteristic (ROC) curve with area under ROC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy.

RESULTS

There were significant differences in the lymph node metastasis stage, tumor grade, neuron-specific enolase levels, tumor margin, main pancreatic ductal dilatation, common bile duct dilatation, enhancement pattern, vascular and adjacent tissue involvement, synchronous liver metastases, the long axis of the largest lymph node, the short axis of the largest lymph node, number of the lymph nodes with short axis > 5 or 10 mm, and tumor volume between two groups (P < 0.05). Multivariate analysis showed that tumor margin (odds ratio = 11.523, P < 0.001) was a predictive factor for LMPI of NF-PNETs. The area under the receiver value for the predictive performance of combined predictive factors was 0.855. The sensitivity, specificity, PPV, NPV and accuracy of the model were 48.1% (14/27), 97.1% (33/34), 97.1% (13/14), 70.2% (33/47) and 0.754, respectively.

CONCLUSION

Using preoperative MRI, ill-defined tumor margins can effectively predict LMPI in patients with NF-PNETs.

Effect of concomitant atrial septal defect on left ventricular function in adult patients with unrepaired Ebstein's anomaly: a cardiovascular magnetic resonance imaging study

BACKGROUND

Due to the heterogeneity of anatomic anomalies in Ebstein's anomaly (EA), particularly in the subset of patients with atrial septal defect (ASD), hemodynamic changes, which ultimately cause left ventricular (LV) deterioration remain unclear. The current study aimed to investigate the effect of concomitant ASD on LV function using cardiovascular magnetic resonance (CMR) imaging in patients with EA.

METHODS

This study included 31 EA patients with ASD, 76 EA patients without ASD, 35 patients with simple ASD and 40 healthy controls. Left/right ventricular (RV, the RV was defined as a summation of the functional RV and atrialized RV in EA patients) volumes and functional parameters, LV strain parameters, and echocardiogram indices were compared among the four groups. Associations between variables were evaluated via Spearman or Pearson correlation analyses. The association between risk factors and LV ejection fraction (EF) was determined via multivariate linear regression analysis.

RESULTS

Both EA patients and ASD patients had a higher RV/LV end-diastolic volume (RVEDV/LVEDV) as well as lower LV and RV ejection fractions (LVEF/RVEF) compared to healthy controls (all p < 0.05). Moreover, the EA patients with ASD had a significantly higher RVEDV/LVEDV and a lower LVEF and RVEF than those without ASD (all p < 0.05). Multivariate linear regression analysis revealed that the presence of ASD was independently associated with LVEF (β = - 0.337, p < 0.001). The RVEDV/LVEDV index was associated with LVEF (r = - 0.361, p < 0.001). Furthermore, the LV longitudinal peak diastolic strain rate (PDSR) was lower in EA patients with ASD than those without ASD, patients with simple ASD, and healthy controls (p < 0.05).

CONCLUSION

Concomitant ASD is an important risk factor of LV dysfunction in patients with EA, and diastolic dysfunction is likely the predominate mechanism related to LV dysfunction.

CT radiomics in the identification of preoperative understaging in patients with clinical stage T1-2N0 esophageal squamous cell carcinoma

Background

Predicting preoperative understaging in patients with clinical stage T1-2N0 (cT1-2N0) esophageal squamous cell carcinoma (ESCC) is critical to customizing patient treatment. Radiomics analysis can provide additional information that reflects potential biological heterogeneity based on computed tomography (CT) images. However, to the best of our knowledge, no studies have focused on identifying CT radiomics features to predict preoperative understaging in patients with cT1-2N0 ESCC. Thus, we sought to develop a CT-based radiomics model to predict preoperative understaging in patients with cT1-2N0 esophageal cancer, and to explore the value of the model in disease-free survival (DFS) prediction.

Methods

A total of 196 patients who underwent radical surgery for cT1-2N0 ESCC were retrospectively recruited from two hospitals. Among the 196 patients, 134 from Peking University Cancer Hospital were included in the training cohort, and 62 from Henan Cancer Hospital were included in the external validation cohort. Radiomics features were extracted from patients' CT images. Least absolute shrinkage and selection operator (LASSO) regression was used for feature selection and model construction. A clinical model was also built based on clinical characteristics, and the tumor size [the length, thickness and the thickness-to-length ratio (TLR)] was evaluated on the CT images. A radiomics nomogram was established based on multivariate logistic regression. The diagnostic performance of the models in predicting preoperative understaging was assessed by the area under the receiver operating characteristic curve (AUC). Kaplan-Meier curves with the log-rank test were employed to analyze the correlation between the nomogram and DFS.

Results

Of the patients, 50.0% (67/134) and 51.6% (32/62) were understaged in the training and validation groups, respectively. The radiomics scores and the TLRs of the tumors were included in the nomogram. The AUCs of the nomogram for predicting preoperative understaging were 0.874 [95% confidence interval (CI): 0.815-0.933] in the training cohort and 0.812 (95% CI: 0.703-0.912) in the external validation cohort. The diagnostic performance of the nomogram was superior to that of the clinical model (P<0.05). The nomogram was an independent predictor of DFS in patients with cT1-2N0 ESCC.

Conclusions

The proposed CT-based radiomics model could be used to predict preoperative understaging in patients with cT1-2N0 ESCC who have undergone radical surgery.

[The efficacy of chemotherapy re-challenge in third-line setting for metastatic colorectal cancer patients: a real-world study]

Objective: To explore the efficacy of chemotherapy re-challenge in the third-line setting for patients with metastatic colorectal cancer (mCRC) in the real world. Methods: The clinicopathological data, treatment information, recent treatment efficacy, adverse events and survival data of mCRC patients who had disease progression after treatment with oxaliplatin-based and/or irinotecan-based chemotherapy and received third-line chemotherapy re-challenge from January 2013 to December 2020 at Tianjin Medical University Cancer Institute and Hospital were retrospectively collected. Survival curves were plotted with the Kaplan-Meier method, and the Cox proportional hazard model was used to analyze the prognostic factors. Results: A total of 95 mCRC patients were included. Among them, 32 patients (33.7%) received chemotherapy alone and 63 patients (66.3%) received chemotherapy combined with targeted drugs. Eighty-three patients were treated with dual-drug chemotherapy (87.4%), including oxaliplatin re-challenge in 35 patients and irinotecan re-challenge in 48 patients. The remaining 12 patients were treated with triplet chemotherapy regimens (12.6%). Among them, as 5 patients had sequential application of oxaliplatin and irinotecan in front-line treatments, their third-line therapy re-challenged both oxaliplatin and irinotecan; 7 patients only had oxaliplatin prescription before, and these patients re-challenged oxaliplatin in the third-line treatment. The overall response rate (ORR) and disease control rate (DCR) reached 8.6% (8/93) and 61.3% (57/93), respectively. The median progression free survival (mPFS) and median overall survival (mOS) were 4.9 months and 13.0 months, respectively. The most common adverse events were leukopenia (34.7%) and neutropenia (34.7%), followed by gastrointestinal adverse reactions such as nausea (32.6%) and vomiting (31.6%). Grade 3-4 adverse events were mostly hematological toxicity. Cox multivariate analysis showed that gender (HR=1.609, 95% CI: 1.016-2.548) and the PFS of front-line treatments (HR=0.598, 95% CI: 0.378-0.947) were independent prognostic factors. Conclusion: The results suggested that it is safe and effective for mCRC patients to choose third-line chemotherapy re-challenge, especially for patients with a PFS of more than one year in front-line treatments.

Analysis of enhanced CT imaging signs and clinicopathological prognostic factors in hepatoid adenocarcinoma of stomach patients with radical surgery: a retrospective study

BACKGROUND

To investigate the association between CT signs and clinicopathological features and disease recurrence in patients with hepatoid adenocarcinoma of stomach (HAS).

METHODS

Forty nine HAS patients undergoing radical surgery were retrospectively collected. Association between CT and clinicopathological features and disease recurrence was analyzed. Multivariate logistic model was constructed and evaluated for predicting recurrence by using receiver operating characteristic (ROC) curve. Survival curves between model-defined risk groups was compared using Kaplan-Meier method.

RESULTS

24(49.0%) patients developed disease recurrence. Multivariate logistic analysis results showed elevated serum CEA level, peritumoral fatty space invasion and positive pathological vascular tumor thrombus were independent factors for disease recurrence. Odds ratios were 10.87 (95%CI, 1.14-103.66), 6.83 (95%CI, 1.08-43.08) and 42.67 (95%CI, 3.66-496.85), respectively. The constructed model showed an area under ROC of 0.912 (95%CI,0.825-0.999). The model-defined high-risk group showed poorer overall survival and recurrence-free survival than the low-risk group (both P < 0.001).

CONCLUSIONS

Preoperative CT appearance of peritumoral fatty space invasion, elevated serum CEA level, and pathological vascular tumor thrombus indicated poor prognosis of HAS patients.

Usefulness of attenuation value on computed tomography plain scan for diagnosing enlarged mediastinal lymph nodes metastases

Background

To evaluate the diagnostic value of computed tomography (CT) attenuation in mediastinal lymph node metastases of malignant tumors.

Methods

A retrospective review was conducted of a Chinese institutional database of consecutive patients with a history of malignant tumors. Those who had enlarged, necrotic, or hypermetabolic lymph nodes detected in the mediastinum during routine CT examination or positron emission tomography (PET)/CT imaging from January 2019 to December 2021 were collected for investigation. All patients underwent endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and were followed up for at least 6 months to diagnose lymph node metastases. One-to-one correlation was attempted between the CT images of the lymph nodes and EBUS-TBNA area of the same lymph node groups and similar size. Radiologists measured size, as well as plain CT and contrast-enhanced CT (CECT) attenuation values of mediastinal lymph nodes, and evaluated the effectiveness of these variables in diagnosing lymph node metastasis.

Results

A total of 135 lymph nodes of 114 patients were included in the study. In the univariate analysis, the long-axis diameter, short-axis diameter, short-axis/long-axis ratio, and plain CT attenuation values of lymph nodes were found to be statistically significantly different between the metastatic and non-metastatic lymph nodes. The areas under receiver operator characteristic (ROC) curves (AUCs) of long-axis diameter, short-axis diameter, short-axis/long-axis ratio, and plain CT attenuation value for diagnosing metastases were 0.711, 0.788, 0.671, and 0.827, respectively. The best value of the AUC for diagnosing lymph node metastases was 0.827 [95% confidence interval (CI): 0.749-0.890] using plain CT attenuation value ≤45 Hounsfield units (HU). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 92.8%, 69.2%, 86.5%, and 81.8%, respectively. Similar results were obtained from the 68 cases of lung cancer. Plain CT attenuation values reached the best AUC (0.860) for diagnosing lymph node metastases.

Conclusions

Plain CT attenuation of lymph nodes is an effective method for diagnosing enlarged mediastinal lymph nodes with a history of multiple malignancies or lung cancer. Plain CT could be used as an additional test where there is no PET/CT available in cases of diagnostic dilemma.

Tumor attachment to Major intrahepatic vascular for Colorectal liver metastases

BACKGROUND

Colorectal liver metastases attached major intrahepatic vessels has been considered to be a risk factor for survival outcome after liver resection. The present study aimed to clarify the outcomes of R1 surgery (margin < 1 mm) in CRLM patients, distinguishing parenchymal margin R1 and attached to major intrahepatic vessels R1.

METHODS

In present study, 283 CRLM patients who were evaluated to be attached to major intrahepatic vessels initially and underwent liver resection following preoperative chemotherapy. They were assigned to two following groups: R0 (n = 167), R1 parenchymal (n = 58) and R1 vascular (n = 58). The survival outcomes and local recurrence rates were analyzed in each group.

RESULTS

Overall, 3- and 5-year overall survival rates after liver resection were 53.0% and 38.2% (median overall survival 37 months). Five-year overall survival was higher in patients with R0 than parenchymal R1 (44.9%% vs. 26.3%, p = 0.009), whereas there was no significant difference from patients with vascular R1 (34.3%, p = 0.752). In the multivariable analysis, preoperative chemotherapy > 4 cycles, clinical risk score 3-5, RAS mutation, parenchymal R1 and CA199 > 100 IU/ml were identified as independent predictive factors of overall survival (p < 0.05). There was no significant difference for local recurrence among three groups.

CONCLUSION

Parenchymal R1 resection was independent risk factor for CRLM. Vascular R1 surgery achieved survival outcomes equivalent to R0 resection. Non-anatomic liver resection for CRLM attached to intrahepatic vessels might be pursued to increase patient resectability by preoperative chemotherapy.

Procedure-related pain during CT-guided percutaneous transthoracic needle biopsies of lung lesions: a prospective study

BACKGROUND

The existing data on the degree of pain in patients during CT-guided percutaneous transthoracic needle biopsy (PTNB) of lung lesions are limited and the factors related to pain are unclear. In this study, we aimed to evaluate the prevalence and severity of pain reported during PTNB and to identify factors associated with increased reported pain.

METHODS

Patients who underwent PTNB from April 2022 to November 2022 were prospectively evaluated using the numeric rating scale, which assesses subjective pain based on a 0-10 scoring system (0 = no pain; 10 = the worst pain imaginable). The scale divides the scores into three categories: mild pain (1-3 points), moderate pain (4-6 points), and severe pain (7-10 points). Pain scores from 4 to 10 were considered significant pain. Demographic data of patients, lesion characteristics, biopsy variables, complications, the patient's subjective feelings, and pathological result data were analyzed by multivariable logistic regression analysis to identify variables associated with significant pain.

RESULTS

We enrolled 215 participants who underwent 215 biopsy procedures (mean age: 64.5 ± 9.3 years, 123 were men). The mean procedure-related pain score was 2 ± 2. Overall, 20% (43/215) of participants reported no pain (score of 0), 67.9% (146/215) reported pain scores of 1-3, 11.2% (24/215) reported scores of 4-6, and 0.9% (2/215) reported scores of 7 or higher. Furthermore, non-significant pain (scores of 0-3) was reported during 87.9% (189/215) of the procedures. In the adjusted model, significant pain was positively associated with lesions ≥ 34 mm (p = 0.001, odds ratio [OR] = 6.90; 95% confidence interval [CI]: 2.18, 21.85), a needle-pleural angle ≥ 77° (p = 0.047, OR = 2.44; 95% CI: 1.01, 5.89), and a procedure time ≥ 26.5 min (p = 0.031, OR = 3.11; 95% CI: 1.11, 8.73).

CONCLUSIONS

Most participants reported no pain or mild pain from CT-guided percutaneous transthoracic needle biopsies of lung lesions. However, those with a larger lesion, a greater needle-pleural angle, and a longer procedure time reported greater pain.

Optimal selection of b-values for differential diagnosis of mediastinal lymph nodes using diffusion-weighted imaging

This study proposed to investigate the optimal selection of b-values in diffusion-weighted imaging for distinguishing malignant from benign mediastinal lymph nodes. Diffusion-weighted imaging with six b-values was performed on 35 patients at 1.5 T. Image quality score, signal-to-noise ratio, and relative contrast ratio of lymph node to chest muscle were compared between the diffusion-weighted images with a b-value up to 800 and 1000 s/mm². Using a lower and an upper b-value in the range of 0-1000 s/mm², eight apparent diffusion coefficient maps were obtained from a mono-exponential model. Receiver operating characteristic analysis was employed to evaluate the performance of the apparent diffusion coefficients for distinguishing malignant from benign mediastinal lymph nodes by using the area under the curve as a criterion. The mean image quality score and the relative contrast ratio showed no difference between b-values of 800 and 1000 s/mm². In the receiver operating characteristic analysis, the areas under the curve of apparent diffusion coefficient with b-value pairs of (0, 800), (0, 1000), and (50, 800) s/mm² were significantly higher than those from the other b-value pairs. No significant difference was observed among the three b-value pairs. Apparent diffusion coefficient obtained from b-value pairs of (0, 800), (0, 1000), and (50, 800) s/mm² showed superior diagnostic performance compared to the other b-value combinations. Based on several practical considerations, the b-value pair of (50, 800) s/mm² is recommended for differential diagnosis of mediastinal lymph nodes.

CT radiomics features of meso-esophageal fat in predicting overall survival of patients with locally advanced esophageal squamous cell carcinoma treated by definitive chemoradiotherapy

OBJECTIVE

To investigate the value of CT radiomics features of meso-esophageal fat in the overall survival (OS) prediction of patients with locally advanced esophageal squamous cell carcinoma (ESCC).

METHODS

A total of 166 patients with locally advanced ESCC in two medical centers were retrospectively analyzed. The volume of interest (VOI) of meso-esophageal fat and tumor were manually delineated on enhanced chest CT using ITK-SNAP. Radiomics features were extracted from the VOIs by Pyradiomics and then selected using the t-test, the Cox regression analysis, and the least absolute shrinkage and selection operator. The radiomics scores of meso-esophageal fat and tumors for OS were constructed by a linear combination of the selected radiomic features. The performance of both models was evaluated and compared by the C-index. Time-dependent receiver operating characteristic (ROC) analysis was employed to analyze the prognostic value of the meso-esophageal fat-based model. A combined model for risk evaluation was constructed based on multivariate analysis.

RESULTS

The CT radiomic model of meso-esophageal fat showed valuable performance for survival analysis, with C-indexes of 0.688, 0.708, and 0.660 in the training, internal, and external validation cohorts, respectively. The 1-year, 2-year, and 3-year ROC curves showed AUCs of 0.640-0.793 in the cohorts. The model performed equivalently compared to the tumor-based radiomic model and performed better compared to the CT features-based model. Multivariate analysis showed that meso-rad-score was the only factor associated with OS.

CONCLUSIONS

A baseline CT radiomic model based on the meso-esophagus provide valuable prognostic information for ESCC patients treated with dCRT.

Intentional Watch and Wait or Organ Preservation Surgery Following Neoadjuvant Chemoradiotherapy Plus Consolidation CAPEOX for MRI-defined Low-risk Rectal Cancer: Findings From a Prospective Phase 2 Trial (PKUCH-R01 Trial, NCT02860234)

OBJECTIVE

To assess the efficacy and safety of intentional watch and wait (W&W) and organ preservation surgery following neoadjuvant chemoradiotherapy plus consolidation CAPEOX in magnetic resonance imaging (MRI)-defined low-risk rectal cancer.

BACKGROUND

Clinical T2/early T3 rectal cancers can achieve high yield pathological complete response (ypCR) rates after chemoradiotherapy; thus, an intentional W&W or organ preservation strategy for good clinical responders in these subgroups can be further tested.

METHODS

This prospective, single-arm, phase 2 trial enrolled patients with low-risk MRI prestaged rectal cancers, who concurrently received chemoradiation, followed by four 3-weekly cycles of CAPEOX regimen. Following reassessment, clinical complete response (cCR) or near-cCR patients underwent W&W/organ preservation surgery; the primary endpoint was a 3-year organ preservation rate.

RESULTS

Of the 64 participants, 58 completed treatment, with 6.4% and 33.9% grade 3 to 4 toxicities in the radiotherapy and consolidation CAPEOX phases, respectively, during a median 39.5-month follow-up. Initial cCR, and non-cCR occurred in 33, 13, and 18 patients, respectively. Of the 31 cCR and 7 near-cCR cases managed by W&W, local regrowth occurred in 7; of these, 6 received salvage surgery. The estimated 2-year local regrowth rates were 12.9% [95% confidence interval (CI): 1.1%-24.7%] in cCR and 42.9% (95% CI: 6.2%-79.6%) in near-cCR cases, respectively. Eight patients received local excision, including 2 with regrowth salvage. Lung metastases occurred in 3 patients and multiple metastasis occurred in 1 patient; no local recurrence occurred. The estimated 3-year organ preservation rate was 67.2% (95% CI: 55.6%-78.8%). The estimated 3-year cancer-specific survival, non-regrowth disease-free survival, and stoma-free survival were 96.6% (95% CI: 92.1%-100%), 92.2% (95% CI: 85.5%-98.9%), and 82.7% (95% CI: 73.5%-91.9%), respectively.

CONCLUSIONS

Chemoradiotherapy plus consolidation CAPEOX for MRI-defined low-risk rectal cancer can lead to high rates of organ preservation through intentional W&W or local excision. The oncologic safety of this strategy should be further tested.

Discrimination of Liver Metastases of Digestive System Neuroendocrine Tumors From Neuroendocrine Carcinoma by Computed Tomography-Based Radiomics Analysis

OBJECTIVE

The aim of the study is to investigate the value of computed tomography (CT) radiomics features to discriminate the liver metastases (LMs) of digestive system neuroendocrine tumors (NETs) from neuroendocrine carcinoma (NECs).

METHODS

Ninety-nine patients with LMs of digestive system neuroendocrine neoplasms from 2 institutions were included. Radiomics features were extracted from the portal venous phase CT images by the Pyradiomics and then selected by using the t test, Pearson correlation analysis, and least absolute shrinkage and selection operator method. The radiomics score (Rad score) for each patient was constructed by linear combination of the selected radiomics features. The radiological model was constructed by radiological features using the multivariable logistic regression. Then, the combined model was constructed by combining Rad score and the radiological model into logistic regression. The performance of all models was evaluated by the receiver operating characteristic curves with the area under curve (AUC).

RESULTS

In the radiological model, only the enhancement degree (odds ratio, 8.299; 95% confidence interval, 2.070-32.703; P = 0.003) was an independent predictor for discriminating the LMs of digestive system NETs from those of NECs. The combined model constructed by the Rad score in combination with the enhancement degree showed good discrimination performance, with AUCs of 0.893, 0.841, and 0.740 in the training, testing, and external validation groups, respectively. In addition, it performed better than radiological model in the training and testing groups (AUC, 0.893 vs 0.726; AUC, 0.841 vs 0.621).

CONCLUSIONS

The CT radiomics might be useful for discrimination LMs of digestive system NECs from NETs.

Prediction of hepatic lymph node metastases based on magnetic resonance imaging before and after preoperative chemotherapy in patients with colorectal liver metastases underwent surgical resection

BACKGROUND

Patients with colorectal liver metastases (CRLM) combined with hepatic lymph node (HLN) metastases have a poor prognosis. In this study, we developed and validated a model using clinical and magnetic resonance imaging (MRI) parameters to predict HLN status before surgery.

METHODS

A total of 104 CRLM patients undergoing hepatic lymphonodectomy with pathologically confirmed HLN status after preoperative chemotherapy were enrolled in this study. The patients were further divided into a training group (n = 52) and a validation group (n = 52). The apparent diffusion coefficient (ADC) values, including ADC_mean and ADC_min of the largest HLN before and after treatment, were measured. rADC was calculated referring to the target liver metastases, spleen, and psoas major muscle (rADC_-LM, rADC_-SP, rADC_-m). In addition, ADC change rate (Δ% ADC) was quantitatively calculated. A multivariate logistic regression model for predicting HLN status in CRLM patients was constructed using the training group and further tested in the validation group.

RESULTS

In the training cohort, post-ADC_mean (P = 0.018) and the short diameter of the largest lymph node after treatment (P = 0.001) were independent predictors for metastatic HLN in CRLM patients. The model's AUC was 0.859 (95% CI, 0.757-0.961) and 0.767 (95% CI 0.634-0.900) in the training and validation cohorts, respectively. Patients with metastatic HLN showed significantly worse overall survival (p = 0.035) and recurrence-free survival (p = 0.015) than patients with negative HLN.

CONCLUSIONS

The developed model using MRI parameters could accurately predict HLN metastases in CRLM patients and could be used to preoperatively assess the HLN status and facilitate surgical treatment decisions in patients with CRLM.

CT Radiomics for Predicting Pathological Complete Response of Axillary Lymph Nodes in Breast Cancer After Neoadjuvant Chemotherapy: A Prospective Study

BACKGROUND

The diagnostic effectiveness of traditional imaging techniques is insufficient to assess the response of lymph nodes (LNs) to neoadjuvant chemotherapy (NAC), especially for pathological complete response (pCR). A radiomics model based on computed tomography (CT) could be helpful.

PATIENTS AND METHODS

Prospective consecutive breast cancer patients with positive axillary LNs initially were enrolled, who received NAC prior to surgery. Chest contrast-enhanced thin-slice CT scan was performed both before and after the NAC (recorded as the first and the second CT respectively), and on both of them, the target metastatic axillary LN was identified and demarcated layer by layer. Using pyradiomics-based software that was independently created, radiomics features were retrieved. A pairwise machine learning workflow based on Sklearn (https://scikit-learn.org/) and FeAture Explorer was created to increase diagnostic effectiveness. An effective pairwise auto encoder model was developed by the improvement of data normalization, dimensionality reduction, and features screening scheme as well as the comparison of the prediction effectiveness of the various classifiers.

RESULTS

A total of 138 patients were enrolled, and 77 (58.7%) in the overall group achieved pCR of LN after NAC. Nine radiomics features were finally chosen for modeling. The AUCs of the training group, validation group, and test group were 0.944 (0.919-0.965), 0.962 (0.937-0.985), and 1.000 (1.000-1.000), respectively, and the corresponding accuracies were 0.891, 0.912, and 1.000.

CONCLUSION

The pCR of axillary LNs in breast cancer following NAC can be precisely predicted using thin-sliced enhanced chest CT-based radiomics.

Efficacy evaluation of different measurement methods for target lesions after neoadjuvant chemotherapy and radical radiotherapy in locally advanced hypopharyngeal carcinoma

AIM

To assess the diagnostic efficacy in response evaluation of hypopharyngeal carcinoma (HPC) using different CT measurement methods.

METHODS AND MATERIALS

One hundred and three patients with locally advanced HPC receiving neoadjuvant chemotherapy (NACT) and radical radiotherapy (RT) were retrospectively enrolled. The long diameter, short diameter and largest axial area of the tumors and the largest metastatic cervical lymph node (LN) were measured before and after NACT, at the end of RT and 1 month after RT. Tumor regression ratios of the sum of the tumor's long diameter and LN's short diameter (LDTSDL), the sum of tumor and LN's short diameter (TTSDL), the sum of tumor and LN's largest axial area (AATML) were calculated. Analysis was conducted for overall survival (OS), metastasis-free survival, regional recurrence-free survival (RRFS), and local recurrence-free survival (LRFS).

RESULTS

Note that 35, 28, 23, and 16 patients suffered death, local recurrence, regional recurrence and distant metastasis, respectively. TTSDL-defined effective group demonstrated better LRFS (p = .039) and RRFS (p = .047) after NACT and better OS since the end of RT (p = .037); AATML-defined effective groups demonstrated better OS, LRFS, and RRFS since the end of RT (p = .015, .008, and .005). While LDTSDL-defined groups showed differences in OS and LRFS until 1 month after RT (p = .013 and .014).

CONCLUSIONS

The regression rate of TTSDL and AATML can distinguish prognosis at an earlier time and demonstrated better reliability compared with LDTSDL. They were recommended for response evaluation in HPC.

Total neoadjuvant treatment for MRI-stratified high-risk rectal cancer: a single-center, single-arm, prospective Phase II trial (PKUCH-R02)

Background

Induction chemotherapy combined with neoadjuvant chemoradiotherapy has been recommended for patients with high-risk, locally advanced rectal cancer. However, the benefit of more intensive total neoadjuvant treatment (TNT) is unknown. This study aimed to assess the safety and efficacy of induction chemotherapy combined with chemoradiotherapy and consolidation chemotherapy for magnetic resonance imaging-stratified high-risk rectal cancer.

Methods

This was a single-center, single-arm, prospective Phase II trial in Peking University Cancer Hospital (Beijing, China). Patients received three cycles of induction oxaliplatin and capecitabine (CapeOX) followed by chemoradiotherapy and two cycles of consolidation CapeOX. The primary end point was adverse event rate and the second primary end points were 3-year disease-free survival rate, completion of TNT, and pathological downstaging rate.

Results

Between August 2017 and August 2018, 68 rectal cancer patients with at least one high risk factor (cT3c/3d/T4a/T4b, cN2, mesorectal fascia involvement, or extramural venous invasion involvement) were enrolled. The overall compliance of receiving the entire treatment was 88.2% (60/68). All 68 patients received induction chemotherapy, 65 received chemoradiotherapy, and 61 received consolidation chemotherapy. The Grade 3-4 adverse event rate was 30.8% (21/68). Nine patients achieved clinical complete response and then watch and wait. Five patients (7.4%) developed distant metastasis during TNT and received palliative chemotherapy. Fifty patients underwent surgical resection. The complete response rate was 27.9%. After a median follow-up of 49.2 months, the overall 3-year disease-free survival rate was 69.7%.

Conclusions

For patients with high-risk rectal cancer, this TNT regimen can achieve favorable survival and complete response rates but with high toxicity. However, it is necessary to pay attention to the possibility of distant metastasis during the long treatment period.

Quantitative CT evaluation after two cycles of induction chemotherapy to predict prognosis of patients with locally advanced oesophageal squamous cell carcinoma before undergoing definitive chemoradiotherapy/radiotherapy

OBJECTIVE

To investigate the performance of quantitative CT analysis in predicting the prognosis of patients with locally advanced oesophageal squamous cell carcinoma (ESCC) after two cycles of induction chemotherapy before definitive chemoradiotherapy/radiotherapy.

METHODS

A total of 110 patients with locally advanced ESCC were retrospectively analysed. Baseline chest CT and CT after two cycles of induction chemotherapy were analysed. A multivariate Cox proportional-hazard regression model was used to identify independent prognostic markers for survival analysis. Then, a CT scoring system was established. Time-dependent receiver operating characteristic (ROC) curve analysis and the Kaplan-Meier method were employed for analysing the prognostic value of the CT scoring system.

RESULTS

Body mass index, treatment strategy, change ratios of thickness (ΔTH_max), CT value of the primary tumour (ΔCTV_axial) and the short diameter (ΔSD-LN), and the presence of an enlarged small lymph node (ESLN) after two cycles of chemotherapy were noted as independent factors for predicting overall survival (OS). The specificity of the presence of ESLN for death after 12 months was up to 100%. Areas under the curve value of the CT scoring system for predicting OS and progression-free survival (PFS) were higher than that of the RECIST (p < 0.05). Responders had significantly longer OS and PFS than non-responders.

CONCLUSION

Quantitative CT analysis after two cycles of induction chemotherapy could predict the outcome of locally advanced ESCC patients treated with definitive chemoradiotherapy/radiotherapy. The CT scoring system could contribute to the development of an appropriate strategy for patients with locally advanced ESCC.

KEY POINTS

• Quantitative CT evaluation after two cycles of induction chemotherapy can predict the long-term outcome of locally advanced oesophageal cancer treated with definitive chemoradiotherapy/radiotherapy. • A CT scoring system provides valuable imaging support for indicating the prognosis at the early stage of therapy. • Quantitative CT evaluation can assist clinicians in personalising treatment plans.

Quantitative CT analysis to predict esophageal fistula in patients with advanced esophageal cancer treated by chemotherapy or chemoradiotherapy

Background

Esophageal fistula is one of the most serious complications of chemotherapy or chemoradiotherapy (CRT) for advanced esophageal cancer. This study aimed to evaluate the performance of quantitative computed tomography (CT) analysis and to establish a practical imaging model for predicting esophageal fistula in esophageal cancer patients treated with chemotherapy or chemoradiotherapy.

Methods

This study retrospectively enrolled 204 esophageal cancer patients (54 patients with fistula, 150 patients without fistula) and all patients were allocated to the primary and validation cohorts according to the time of inclusion in a 1:1 ratio. Ulcer depth, tumor thickness and length, and minimum and maximum enhanced CT values of esophageal cancer were measured in pretreatment CT imaging. Logistic regression analysis was used to evaluate the associations of CT quantitative measurements with esophageal fistula. Receiver operating characteristic curve (ROC) analysis was also used.

Results

Logistic regression analysis showed that independent predictors of esophageal fistula included tumor thickness [odds ratio (OR) = 1.167; p = 0.037], the ratio of ulcer depth to adjacent tumor thickness (OR = 164.947; p < 0.001), and the ratio of minimum to maximum enhanced CT value (OR = 0.006; p = 0.039) in the primary cohort at baseline CT imaging. These predictors were used to establish a predictive model for predicting esophageal fistula, with areas under the receiver operating characteristic curves (AUCs) of 0.946 and 0.841 in the primary and validation cohorts, respectively. The quantitative analysis combined with T stage for predicting esophageal fistula had AUCs of 0.953 and 0.917 in primary and validation cohorts, respectively.

Conclusion

Quantitative pretreatment CT analysis has excellent performance for predicting fistula formation in esophageal cancer patients who treated by chemotherapy or chemoradiotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-022-00490-2.

Preoperative prediction of lymph node metastasis in nonfunctioning pancreatic neuroendocrine tumors from clinical and MRI features: a multicenter study

Background

The extent of surgery in nonfunctioning pancreatic neuroendocrine tumors (NF-PNETs) has not well established, partly owing to the dilemma of precise prediction of lymph node metastasis (LNM) preoperatively. This study proposed to develop and validate the value of MRI features for predicting LNM in NF-PNETs.

Methods

A total of 187 patients with NF-PNETs who underwent MR scan and subsequent lymphadenectomy from 4 hospitals were included and divided into training group (n = 66, 1 center) and validation group (n = 121, 3 centers). The clinical characteristics and qualitative MRI features were collected. Multivariate logistic regression model for predicting LNM in NF-PNETs was constructed using the training group and further tested using validation group.

Results

Nodal metastases were reported in 41 patients (21.9%). Multivariate analysis showed that regular shape of primary tumor (odds ratio [OR], 4.722; p = .038) and the short axis of the largest lymph node in the regional area (OR, 1.488; p = .002) were independent predictors for LNM in the training group. The area under the receiver operating characteristic curve in the training group and validation group were 0.890 and 0.849, respectively. Disease-free survival was significantly different between model-defined LNM and non-LNM group.

Conclusions

The novel MRI-based model considering regular shape of primary tumor and short axis of largest lymph node in the regional area can accurately predict lymph node metastases preoperatively in NF-PNETs patients, which might facilitate the surgeons’ decision on risk stratification.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01301-9.

Establishment of a multi-parameters MRI model for predicting small lymph nodes metastases (<10 mm) in patients with resected pancreatic ductal adenocarcinoma

PURPOSE

To evaluate the potential role of MR findings and DWI parameters in predicting small regional lymph nodes metastases (with short-axis diameter < 10 mm) in pancreatic ductal adenocarcinomas (PDACs).

METHODS

A total of 127 patients, 82 in training group and 45 in testing group, with histopathologically diagnosed PDACs who underwent pancreatectomy were retrospectively analyzed. PDACs were divided into two groups of positive and negative lymph node metastases (LNM) based on the pathological results. Pancreatic cancer characteristics, short axis of largest lymph node, and DWI parameters of PDACs were evaluated.

RESULTS

Univariate and multivariate analyses showed that extrapancreatic distance of tumor invasion, short-axis diameter of the largest lymph node, and mean diffusivity of tumor were independently associated with small LNM in patients with PDACs. The combining MRI diagnostic model yielded AUCs of 0.836 and 0.873, and accuracies of 81.7% and 80% in the training and testing groups. The AUC of the MRI model for predicting LNM was higher than that of subjective MRI diagnosis in the training group (rater 1, P = 0.01; rater 2, 0.008) and in a testing group (rater 1, P = 0.036; rater 2, 0.024). Comparing the subjective diagnosis, the error rate of the MRI model was decreased. The defined LNM-positive group by the MRI model showed significantly inferior overall survival compared to the negative group (P = 0.006).

CONCLUSIONS

The MRI model showed excellent performance for individualized and noninvasive prediction of small regional LNM in PDACs. It may be used to identify PDACs with small LNM and contribute to determining an appropriate treatment strategy for PDACs.

Primary malignant melanoma of the esophagus: differentiation from esophageal squamous cell carcinoma and leiomyoma using dynamic contrast-enhanced CT findings

PURPOSE

This study aimed to summarize the computed tomography (CT) findings of PMME and differentiate it from esophageal SCC and leiomyoma using CT analysis.

METHODS

This was a retrospective study including 23 patients with PMME, 69 patients with SCC, and 21 patients with leiomyoma in our hospital. Qualitative CT morphological characteristics of each lesion included the location, tumor range, ulcer, enhanced pattern, and so on. For quantitative CT analysis, thickness, length and area of tumor, size of largest lymph node, number of metastatic lymph node, and CT value of tumor in plain, arterial, and delayed phases were measured. The associated factors for differentiating PMME from SCC and leiomyoma were examined with univariate and multivariate analysis. Receive operating characteristic curve (ROC) was used to determine the performance of CT models in discriminating PMME from SCC and leiomyoma.

RESULTS

The thickness, mean CT value in arterial phase, and range of tumor were the independent factors for diagnosing PMME from SCC. These parameters were used to establish a diagnostic CT model with area under the ROC (AUC) of 0.969, and accuracy of 90.2%. In pathology, interstitial vessels in PMME were more abundant than that of SCC, and the stromal fibrosis was more obvious in SCC. PMME commonly exhibited intraluminal expansively growth pattern and SCC often showed infiltrative pattern. The postcontrast attenuation difference in maximum CT attenuation value between plain and arterial phases was the independent factor for diagnosing PMME from leiomyoma. This parameter was applied to differentiate PMME from leiomyoma with AUC of 0.929 and accuracy of 86.4%.

CONCLUSION

The qualitative and quantitative CT analysis had excellent performance for differentiating PMME from SCC and esophageal leiomyoma.

PKUCH 04 trial: Total neoadjuvant chemoradiation combined with neoadjuvant PD-1 blockade for pMMR/MSS locally advanced middle to low rectal cancer

3609

Background: Total neoadjuvant therapy (TNT) with induction chemotherapy and chemoradiation is the standard of care for locally advanced rectal cancers. Incorporation of PD-1 blockade in the neoadjuvant setting is promising for mismatch repair deficient (dMMR) patients, yet the efficacy of TNT combined with PD-1 blockage for pMMR/MSS patients is little unknown. The purpose of this study is to evaluate the clinical benefit of neoadjuvant PD-1 blockade combined with TNT in pMMR/MSS locally advanced rectal cancer. Methods: We designed a prospective, single-arm, phase II study on locally advanced dMMR/MSS rectal cancer (PKUCH 04 trial). Patients will receiving neoadjuvant regimen (PD-1 inhibitor, camrelizumab, also called SHR01210, 200mg d1, oxaliplatin 130mg/m2 d1, capecitabine 1250mg/m2 bid1-14, for three cycles, then long course chemoradiation (IMRT, 1.8Gy/f*25f), then another two cycles of CapeOx (oxaliplatin 130mg/m2 d1, capecitabine 1250mg/m2 bid1-14, q3wks) if no disease progression occurs. The primary endpoint was pathologic complete response (pCR) rate, and the secondary outcome include adverse event and surgical complication. Tumor assessment was carried out after induction, chemoradiation, and before the decision of either surgery or watch and wait. Results: A total of 27 patients were screened and finally 25 patients were eligible for further analysis, with median age 58 years (range 31-70). The median distance from the anal verge was 5.3 cm (1.2-10). 76% were male, 76% had N2 disease, 56% positive MRF, 80% positive EMVI. All patients have completed the induction and chemoradiation phases. 21 patients underwent TME surgery, of which 7 had pathological complete response (33.3%). Four achieved clinical complete or near complete response and chose watch and wait. 7 had major pathological remission (over 90% remission). Another 7 had partial pathological remission. No progressive disease was found. 14 had LAR, 7 APR, and. The surgical complication rate was 14.3%, and the mortality rate was 0. The common adverse events included nausea (80%), lymphopenia (80%), paresthesia (76%), reactive cutaneous capillary endothelial proliferation (72%), neutropenia (68%). Grade 3 adverse events include lymphopenia (24%), diarrhea (8%), and thrombocytopenia (4%) and no grade 4 or 5 events were observed. Till January 2022, no recurrence or regrowth was found. Conclusions: Total neoadjuvant chemoradiation combined with neoadjuvant PD-1 blockade is safe and effective which can achieve good regression and sphincter preservation for pMMR/MSS rectal cancer. This suggests a potential new paradigm for treatment of pMMR/MSS locally advanced rectal cancer and necessitates further investigation. Clinical trial information: NCT04340401.

Total neoadjuvant chemoradiation combined with neoadjuvant PD-1 blockade for patients with pMMR, high-risk, and locally advanced middle to low rectal cancer

3611

Background: Total neoadjuvant therapy (TNT) with chemotherapy and chemoradiotherapy (CRT) is the standard treatment for locally advanced rectal cancer patients, especially for those with high risk factors. And the effects of immune checkpoint inhibitors (ICIs) on rectal cancer with defect mismatch repair (dMMR) have been demonstrated. However, the efficacy of TNT combined with PD-1 blockage for rectal cancer patients with proficient mismatch repair (pMMR) is unknown. The purpose of this study is to evaluate the clinical safety and efficacy of neoadjuvant PD-1 blockade combined with TNT in locally advanced rectal cancer with pMMR. Methods: We designed a prospective, single-arm, phase II study on stage II and III dMMR rectal cancer with high risk factors. Patients received neoadjuvant POC regimen (PD-1 inhibitor, camrelizumab, also called SHR01210, 200mg d1, Oxaliplatin 130mg/m2 d1 and Capecitabine 1250mg/m2 bid1-14, q3wks) for three cycles, then with long course chemoradiation (IMRT, 1.8Gy/f*25f). If there were no disease progression occurs, patients would be treated with another two cycles of CapeOx. The primary endpoint was pathological complete response rate (pCR rate), and the secondary outcome include adverse events and surgical complication. Biopsies and plasma pre-neoadjuvant therapy were collected and performed with whole-exome sequencing (WES), and ctDNA sequencing, respectively. Results: 27 patients were screened, of whom 25 patients were enrolled. All patients have completed the TNT. After neoadjuvant treatment, 21 patients underwent TME surgery. 7 (33.3%) patients were pCR, 3 (14.3%) achieved clinical complete or near complete response and 7 (33.3%) had a major pathological response. No progressive disease was found. WES and ctDNA sequencing analysis showed that tumor mutation burden (TMB) and level of ctDNA did not differ significantly between responders and non-responders. However, 3 responders with TMB high were found to be defective in other DNA damage repair pathways. Conclusions: Total neoadjuvant chemoradiation combined with neoadjuvant PD-1 blockade can achieve high pathological response rate, demonstrating its antitumor efficacy in pMMR locally advanced rectal cancer patients with high risk factors.

Development and validation of a computed tomography-based immune ecosystem diversity index as an imaging biomarker in non-small cell lung cancer

OBJECTIVES

To date, there are no data on the noninvasive surrogate of intratumoural immune status that could be prognostic of survival outcomes in non-small cell lung cancer (NSCLC). We aimed to develop and validate the immune ecosystem diversity index (iEDI), an imaging biomarker, to indicate the intratumoural immune status in NSCLC. We further investigated the clinical relevance of the biomarker for survival prediction.

METHODS

In this retrospective study, two independent NSCLC cohorts (Resec1, n = 149; Resec2, n = 97) were included to develop and validate the iEDI to classify the intratumoural immune status. Paraffin-embedded resected specimens in Resec1 and Resec2 were stained by immunohistochemistry, and the density percentiles of CD3⁺, CD4⁺, and CD8⁺ T cells to all cells were quantified to estimate intratumoural immune status. Then, EDI features were extracted using preoperative computed tomography to develop an imaging biomarker, called iEDI, to determine the immune status. The prognostic value of iEDI was investigated on NSCLC patients receiving surgical resection (Resec1; Resec2; internal cohort Resec3, n = 419; external cohort Resec4, n = 96; and TCIA cohort Resec5, n = 55).

RESULTS

iEDI successfully classified immune status in Resec1 (AUC 0.771, 95% confidence interval [CI] 0.759-0.783; and 0.770 through internal validation) and Resec2 (0.669, 0.647-0.691). Patients with higher iEDI-score had longer overall survival (OS) in Resec3 (unadjusted hazard ratio 0.335, 95%CI 0.206-0.546, p < 0.001), Resec4 (0.199, 0.040-1.000, p < 0.001), and TCIA (0.303, 0.098-0.944, p = 0.001).

CONCLUSIONS

iEDI is a non-invasive surrogate of intratumoural immune status and prognostic of OS for NSCLC patients receiving surgical resection.

KEY POINTS

• Decoding tumour immune microenvironment enables advanced biomarkers identification. • Immune ecosystem diversity index characterises intratumoural immune status noninvasively. • Immune ecosystem diversity index is prognostic for NSCLC patients.

Radiomics analysis based on multiple parameters MR imaging in the spine: Predicting treatment response of osteolytic bone metastases to chemotherapy in breast cancer patients

PURPOSE

To assess the value of radiomics, apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and stretched-exponential (SE) MR imaging in prediction of therapeutic response in patients with spinal metastases before chemotherapy.

METHODS

Thirty-six patients with 190 osteolytic metastatic lesions from breast cancer were prospectively enrolled and underwent MR imaging before and after 6 months' treatment on a 1.5 T MRI. According to MDA criteria, 68 lesions were categorized as progressive disease (PD) and 122 lesions were categorized as stable or improvement (non-PD). The regions of interest (ROIs) were manually drawn on DWI, T1WI, T2WI and FS-T2WI by two radiologists with ITK-SNAP. The ADC_all (multiple b-values method), IVIM parameters (D, D* and f) and SE parameters (DDC and α) were generated. The radiomics features were selected from the ROIs.

RESULTS

The mean values of ADC, DDC, and D before treatment were significantly higher in non-PD group than those in PD group (P = 0.001). The radiomics based on ADC_all had the highest AUC value (0.852), followed by that of the T2WI (0.829) and FS-T2WI (0.798). The radiomics model using ADC_all and FS-T2WI showed excellent efficiency in predicting treatment response with AUCs of 0.905 and 0.873 in training and validation cohorts. The radiomics model had better performance than that of ADC_all, D, and DDC for predicting treatment response of bone metastases.

CONCLUSION

Radiomics model based on ADC_all and FS-T2WI could predict the treatment response and contribute to assisting clinicians in accurately choosing appropriated management.

Preoperative prediction of malignant potential of 2-5 cm gastric gastrointestinal stromal tumors by computerized tomography-based radiomics

BACKGROUND

The use of endoscopic surgery for treating gastrointestinal stromal tumors (GISTs) between 2 and 5 cm remains controversial considering the potential risk of metastasis and recurrence. Also, surgeons are facing great difficulties and challenges in assessing the malignant potential of 2-5 cm gastric GISTs.

AIM

To develop and evaluate computerized tomography (CT)-based radiomics for predicting the malignant potential of primary 2-5 cm gastric GISTs.

METHODS

A total of 103 patients with pathologically confirmed gastric GISTs between 2 and 5 cm were enrolled. The malignant potential was categorized into low grade and high grade according to postoperative pathology results. Preoperative CT images were reviewed by two radiologists. A radiological model was constructed by CT findings and clinical characteristics using logistic regression. Radiomic features were extracted from preoperative contrast-enhanced CT images in the arterial phase. The XGboost method was used to construct a radiomics model for the prediction of malignant potential. Nomogram was established by combing the radiomics score with CT findings. All of the models were developed in a training group (n = 69) and evaluated in a test group (n = 34).

RESULTS

The area under the curve (AUC) value of the radiological, radiomics, and nomogram models was 0.753 (95% confidence interval [CI]: 0.597-0.909), 0.919 (95%CI: 0.828-1.000), and 0.916 (95%CI: 0.801-1.000) in the training group vs 0.642 (95%CI: 0.379-0.870), 0.881 (95%CI: 0.772-0.990), and 0.894 (95%CI: 0.773-1.000) in the test group, respectively. The AUC of the nomogram model was significantly larger than that of the radiological model in both the training group (Z = 2.795, P = 0.0052) and test group (Z = 2.785, P = 0.0054). The decision curve of analysis showed that the nomogram model produced increased benefit across the entire risk threshold range.

CONCLUSION

Radiomics may be an effective tool to predict the malignant potential of 2-5 cm gastric GISTs and assist preoperative clinical decision making.

Correlation and prognostic value of CT-detected extramural venous invasion and pathological lymph-vascular invasion in colon cancer

PURPOSE

To explore the association between CT-detected extramural vascular invasion (ctEMVI) and lymph-vascular invasion (LVI) in colon cancer, and analyze the prognostic value of ctEMVI in different conditions of LVI.

METHODS

This single-center, retrospective study included 448 colon cancer patients from January 2015 to December 2017. Preoperative CT features and clinical and pathological data were collected. Associations between ctEMVI and LVI were tested. Univariate and multivariate logistic regression was performed. Multivariate Cox regression was performed adjusted with propensity score(PS). Kaplan-Meier method was used to compare survival differences between the ctEMVI and LVI groups. A 1:1 patient pairing was conducted using PS matching to assess the prognostic effect of ctEMVI in LVI subgroups.

RESULTS

Among the 448 patients, there were 261 men and 187 women, with an average age of 63 ± 12 years. The coincidence rate of ctEMVI and LVI was 73.9%. The k coefficient for identifying ctEMVI was 0.84. ctEMVI and LVI were both independent risk factors for overall survival (ctEMVI: HR 2.8, 95% CI 1.5-5.5; LVI: HR 2.2, 95% CI 1.2-4.1) and metastasis-free survival (ctEMVI: HR 3.3, 95% CI 1.7-6.4; LVI: HR 2.4, 95% CI 1.3-4.5) adjusted with PS. In the LVI(+) subgroup, the prognosis of ctEMVI(+) was significantly worse than that of ctEMVI(-); in the LVI(-) subgroup, the prognosis of different ctEMVI states was similar.

CONCLUSION

ctEMVI is an independent prognostic risk factor and has different prognostic value in different LVI states. It is recommended to perform the evaluation in routine work, especially for patients with positive LVI.

[A prediction model of pathological complete response in patients with locally advanced rectal cancer after PD-1 antibody combined with total neoadjuvant chemoradiotherapy based on MRI radiomics]

Objective: To construct a prediction model of pathologic complete response (pCR) in locally advanced rectal cancer patients who received programmed cell death protein-1 (PD-1) antibody and total neoadjuvant chemoradiotherapy by using radiomics based on MR imaging data and to investigate its predictive value. Methods: A clinical diagnostic test study was carried out. Clinicopathalogical and radiological data of 38 patients with middle-low rectal cancer who received PD-1 antibody combined with total neoadjuvant chemoradiotherapy and underwent TME surgery from January 2019 to September 2021 in our hospital were retrospectively collected. Among 38 patients, 23 were males and 15 were females with a median age of 68 (47-79) years and 13 (34.2%) a chieved pCR. These 38 patients were stratified and randomly divided into the training group (n=26) and test group (n=12) for modeling. All the patients underwent rectal MRI before treatment. The clinical, imaging and radiomics features of all the patients were collected, and the clinical feature model and radiomics model were constructed. The receiver operating characteristic (ROC) curves of each model were drawn, and the constructed model was evaluated through the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value and negative predictive value. Results: There were no significant differences in age, gender, primary location of tumor and postoperative pathology between the two groups (all P>0.05). Forty-one features were extracted from region of interest in each modality, including 9 first-order features, 24 gray level co-occurrence matrix features and 8 shape features. From 38 patients, 41 features were extracted from each imaging modality of baseline and preoperative DWI and T2WI images, totally 164 features. Only 4 features were preserved after correlation analysis between each pair of features and t-test between pCR and non-pCR subjects. After LASSO cross validation, only the first-order skewness of the baseline DWI image before treatment and the volume in the baseline T2WI image before treatment were retained. The area under the curve, sensitivity, specificity, positive and negative predictive values of the prediction model established by applying these two features in the training group and the test group were 0.856 and 0.844, 77.8% and 100.0%, 88.2% and 75.0%, 77.8% and 66.7%, 88.2% and 100.0%, respectively. The decision curve analysis of the radiomics model showed that the strategy of this model in predicting pCR was better than that in treating all the patients as pCR and that in treating all the patients as non-pCR. Conclusion: The pCR prediction model for rectal cancer patients receiving PD-1 antibody combined with total neoadjuvant radiochemotherapy based on MRI radiomics has the potential to be used in clinical screening or rectal cancer patients who can be spared from radical surgery.

Correlation Between the Distance to Mesorectal Fascia and Prognosis of cT3 Rectal Cancer: Results of a Multicenter Study From China

BACKGROUND

The cT3 substage criteria based on extramural depth of tumor invasion in rectal cancer have several limitations.

OBJECTIVE

This study proposed that the distance between the deepest tumor invasion and mesorectal fascia on pretherapy MRI can distinguish the prognosis of patients with cT3 rectal cancer.

DESIGN

This is a cohort study.

SETTING

This study included a prospective, single-center, observational cohort and a retrospective, multicenter, independent validation cohort.

PATIENT

Patients who had cT3 rectal cancer with negative mesorectal fascia undergoing neoadjuvant chemoradiotherapy followed by radical surgery were included in 4 centers in China from January 2013 to September 2014.

INTERVENTION

Baseline MRI with the distance between the deepest tumor invasion and mesorectal fascia, extramural depth of tumor invasion, and mesorectum thickness were measured.

MAIN OUTCOME MEASURES

The cutoff of the distance between the deepest tumor invasion and mesorectal fascia was determined by time-dependent receiver operating characteristic curves, supported by a 5-year progression rate from the prospective cohort, and was then validated in a retrospective cohort.

RESULTS

There were 124 and 274 patients included in the prospective and independent validation cohorts. The distance between the deepest tumor invasion and mesorectal fascia was the only predictor for cancer-specific death (HR, 0.1; 95% CI, 0.0-0.7) and was also a significant predictor for distant recurrence (HR, 0.4; 95% CI, 0.2-0.9). No statistically significant difference was observed in prognosis between patients classified as T3a/b and T3c/d.

LIMITATIONS

The sample size is relatively small, and the study focused on cT3 rectal cancers with a negative mesorectal fascia.

CONCLUSIONS

A cutoff of 7 mm of the distance between the deepest tumor invasion and mesorectal fascia on baseline MRI can distinguish cT3 rectal cancer from a different prognosis. We recommend using the distance between the deepest tumor invasion and mesorectal fascia on baseline MRI for local and systemic risk assessment and providing a tailored schedule of neoadjuvant treatment. See Video Abstract at http://links.lww.com/DCR/B682.CORRELACIÓN ENTRE LA DISTANCIA DE LA FASCIA MESORRECTAL Y EL PRONÓSTICO DEL CÁNCER DE RECTO cT3: RESULTADOS DE UN ESTUDIO MULTICÉNTRICO DE CHINAANTECEDENTES:Los criterios de subestadificación cT3 basados en la profundidad extramural de invasión tumoral en el cáncer de recto tienen varias limitaciones.OBJETIVO:Este estudio propuso que la distancia entre la invasión tumoral más profunda y la fascia mesorrectal en la resonancia magnética preterapia puede distinguir el pronóstico de los pacientes con cT3.DISEÑO:Estudio de cohorte.ENTORNO CLINICO:El estudio incluyó una cohorte observacional, prospectiva, unicéntrica, y una cohorte de validación retrospectiva, multicéntrica e independiente.PACIENTE:Se incluyeron pacientes con cáncer de recto cT3 con fascia mesorrectal negativa sometidos a quimio-radioterapia neoadyuvante seguida de cirugía radical en cuatro centros de China desde enero de 2013 hasta septiembre de 2014.INTERVENCIÓN:Imágenes de resonancia magnética de referencia fueron medidas con la distancia entre la invasión tumoral más profunda y la fascia mesorrectal; la profundidad extramural de la invasión tumoral y el grosor del mesorrecto.PRINCIPALES MEDIDAS DE VALORACION:El límite de la distancia entre la invasión tumoral más profunda y la fascia mesorrectal se determinó mediante curvas características operativas del receptor dependientes del tiempo y se apoyó en la tasa de progresión a 5 años de la cohorte prospectiva, y luego se validó en una cohorte retrospectiva.RESULTADOS:Se incluyeron 124 y 274 pacientes en la cohorte de validación prospectiva e independiente, respectivamente. La distancia entre la invasión tumoral más profunda de la fascia mesorrectal fue el único predictor de muerte específica por cáncer (Hazard ratio: 0.1, 95% CI, 0,0-0,7); y también fue un predictor significativo de recurrencia distante Hazard ratio: 0,4, 95% CI, 0,2-0,9). No se observaron diferencias estadísticamente significativas en el pronóstico entre los pacientes clasificados como T3a/b y T3c/d.LIMITACIONES:El tamaño de la muestra es relativamente pequeño y el estudio se centró en los cánceres de recto cT3 con fascia mesorrectal negativa.CONCLUSIONES:Un límite de 7 mm de distancia entre la invasión tumoral más profunda y la fascia mesorrectal en la resonancia magnética de referencia puede distinguir el cáncer de recto cT3 de diferentes pronósticos. Recomendamos la distancia entre la invasión tumoral más profunda y la fascia mesorrectal en la resonancia magnética de referencia para la evaluación del riesgo local y sistémico, proporcionando un programa personalizado de tratamiento neoadyuvante. Consulte Video Resumen en http://links.lww.com/DCR/B682. (Traducción- Dr. Francisco M. Abarca-Rendon).

The Conversion of MRI Data With Multiple b-Values into Signature-Like Pictures to Predict Treatment Response for Rectal Cancer

BACKGROUND

Diffusion weighted imaging (DWI) at multiple b-values has been used to predict the pathological complete response (pCR) to neoadjuvant chemoradiotherapy for locally advanced rectal cancer. Non-Gaussian models fit the signal decay of diffusion by several physical values from different approaches of approximation.

PURPOSE

To develop a deep learning method to analyze DWI data scanned at multiple b-values independent on Gaussian or non-Gaussian models and to apply to a rectal cancer neoadjuvant chemoradiotherapy model.

STUDY TYPE

Retrospective.

POPULATION

A total of 472 participants (age: 56.6 ± 10.5 years; 298 males and 174 females) with locally advanced adenocarcinoma were enrolled and chronologically divided into a training group (n = 200; 42 pCR/158 non-pCR), a validation group (n = 72; 11 pCR/61 non-pCR) and a test group (n = 200; 44 pCR/156 non-pCR).

FIELD STRENGTH/SEQUENCE

A 3.0 T MRI scanner. DWI with a single-shot spin echo-planar imaging pulse sequence at 12 b-values (0, 20, 50, 100, 200, 400, 600, 800, 1000, 1200, 1400, and 1600 sec/mm² ).

ASSESSMENT

DWI signals from manually delineated tumor region were converted into a signature-like picture by concatenating all histograms from different b-values. Pathological results (pCR/non-pCR) were used as the ground truth for deep learning. Gaussian and non-Gaussian methods were used for comparison.

STATISTICAL TESTS

Analysis of variance for age; Chi-square for gender and pCR/non-pCR; area under the receiver operating characteristic (ROC) curve (AUC); DeLong test for AUC. P < 0.05 for significant difference.

RESULTS

The AUC in the test group is 0.924 (95% CI: 0.866-0.983) for the signature-like pictures converted from 35 bins, and it is 0.931 (95% CI: 0.884-0.979) for the signature-like pictures converted from 70 bins, which is significantly (Z = 3.258, P < 0.05) larger than D_app , the best predictor in non-Gaussian methods with AUC = 0.773 (95% CI: 0.682-0.865).

DATA CONCLUSION

The proposed signature-like pictures provide more accurate pretreatment prediction of the response to neoadjuvant chemoradiotherapy than the fitted methods for locally advanced rectal cancer.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

[Short-term outcome of programmed cell death protein1 (PD-1) antibody combined with total neoadjuvant chemoradiotherapy in the treatment of locally advanced middle-low rectal cancer with high risk factors]

Objective: Total neoadjuvant chemoradiotherapy is one of the standard treatments for locally advanced rectal cancer. This study aims to investigate the safety and feasibility of programmed cell death protein 1 (PD-1) antibody combined with total neoadjuvant chemoradiotherapy in the treatment of locally advanced middle-low rectal cancer with high-risk factors. Methods: A descriptive cohort study was conducted. Clinicopathological data of 24 patients with locally advanced middle-low rectal cancer with high-risk factors receiving PD-1 antibody combined with neoadjuvant chemoradiotherapy in Gastrointestinal Cancer Center, Unit III, Peking University Cancer Hospital between January 2019 and April 2021 were retrospectively analyzed. Inclusion criteria: (1) rectal adenocarcinoma confirmed by pathology; patient age of ≥ 18 years and ≤ 80 years; (2) the distance from low margin of tumor to anal verge ≤ 10 cm under sigmoidoscopy; (3) ECOG performance status score 0-1; (4) clinical stage T3c, T3d, T4a or T4b, or extramural venous invasion (EMVI) (+) or mrN2 (+) or mesorectal fasciae (MRF) (+) based on MRI; (5) no evidence of distant metastases; (6) no prior pelvic radiation therapy, no prior chemotherapy or surgery for rectal cancer; (7) no systemic infection requiring antibiotic treatment and no immune system disease. Exclusion criteria: (1) anticipated unresectable tumor after neoadjuvant treatment; (2) patients with a history of a prior malignancy within the past 5 years, or with a history of any arterial thrombotic event within the past 6 months; (3) patients received other types of antitumor or experimental therapy; (4) women who were pregnant or breast-feeding; (5) patients with any other concurrent medical or psychiatric condition or disease; (6) patients received immunotherapy (PD-1 antibody). The neoadjuvant therapy consisted of three stages: PD-1 antibody (sintilimab 200 mg, IV, Q3W) combined with CapeOx regimen for three cycles; long-course intensity modulated radiation therapy (IMRT) with gross tumor volume (GTV) 50.6 Gy/CTV 41.8 Gy/22f; CapeOx regimen for two cycles after radiotherapy. After oncological evaluation following the end of the third stage of treatment, surgery or watch and wait would be carried out. Surgical safety, histopathological changes and short-term oncological outcome were analyzed. Results: There were 15 males and 9 females with a median age of 65 (47-78) years. Median distance from the lower margin of the tumor to the anal verge was 4 (3-7) cm. The median maximal diameter of the tumor was 5.1 (2.1-7.5) cm. Twenty patients were cT3, 4 were cT4, 8 were cN1, 5 were cN2a, 11 were cN2b. Ten cases were MRF (+) and 10 were EMVI (+). All the patients were mismatch repair proficient (pMMR). During the neoadjuvant treatment period, 6 patients (25.0%) developed grade 1-2 treatment-related adverse events, including 3 immune-related adverse events. As of April 30, 2021, 20 patients (83.3%, 20/24) had received surgical resection, including 19 R0 resections and 16 sphincter-preservation operations. Morbidity of postoperative complication was 25.0% (5/20), including 2 cases of Clavien-Dindo grade II (1 of anastomotic bleeding and 1 of pseudomembranous enteritis), 3 cases of grade I anastomotic stenosis. Pathological complete response (pCR) rate was 30.0% (6/20) and major pathological response rate was 20.0% (4/20). None of Ras/Raf mutants had pCR or cCR (0/5), while 6 of 17 Ras/Raf wild-type patients had pCR and 3 had cCR, which was significantly higher than that of Ras/Raf mutants (P<0.01). Nine of 16 patients with Ras/Raf wild-type and differentiated adenocarcinoma had pCR or cCR. Among other 4 patients without surgery, 3 patients preferred watch and wait strategy because their tumors were assessed as clinical complete response (cCR), while another one patient refused surgery as the tumor remained stable. After a median follow-up of 11 (6-24) months, only 1 patient with signet ring cell carcinoma had recurrence. Conclusions: PD-1 antibody combined with total neoadjuvant chemoradiotherapy in the treatment of locally advanced rectal cancer has quite good safety and histopathological regression results. Combination of histology and genetic testing is helpful to screen potential beneficiaries.

Automatic segmentation of rectal tumor on diffusion-weighted images by deep learning with U-Net

Purpose

Manual delineation of a rectal tumor on a volumetric image is time‐consuming and subjective. Deep learning has been used to segment rectal tumors automatically on T2‐weighted images, but automatic segmentation on diffusion‐weighted imaging is challenged by noise, artifact, and low resolution. In this study, a volumetric U‐shaped neural network (U‐Net) is proposed to automatically segment rectal tumors on diffusion‐weighted images.

Methods

Three hundred patients of locally advanced rectal cancer were enrolled in this study and divided into a training group, a validation group, and a test group. The region of rectal tumor was delineated on the diffusion‐weighted images by experienced radiologists as the ground truth. A U‐Net was designed with a volumetric input of the diffusion‐weighted images and an output of segmentation with the same size. A semi‐automatic segmentation method was used for comparison by manually choosing a threshold of gray level and automatically selecting the largest connected region. Dice similarity coefficient (DSC) was calculated to evaluate the methods.

Results

On the test group, deep learning method (DSC = 0.675 ± 0.144, median DSC is 0.702, maximum DSC is 0.893, and minimum DSC is 0.297) showed higher segmentation accuracy than the semi‐automatic method (DSC = 0.614 ± 0.225, median DSC is 0.685, maximum DSC is 0.869, and minimum DSC is 0.047). Paired t‐test shows significant difference (T = 2.160, p = 0.035) in DSC between the deep learning method and the semi‐automatic method in the test group.

Conclusion

Volumetric U‐Net can automatically segment rectal tumor region on DWI images of locally advanced rectal cancer.

Non-gaussian models of 3-Tesla diffusion-weighted MRI for the differentiation of pancreatic ductal adenocarcinomas from neuroendocrine tumors and solid pseudopapillary neoplasms

PURPOSE

To assess the MRI performance in differentiating pancreatic ductal adenocarcinomas (PDACs), from solid pseudopapillary neoplasms (SPNs) and pancreatic neuroendocrine tumors (PNETs) using non-gaussian diffusion-weighted imaging models.

METHODS

This was a retrospective study of patients diagnosed with PDACs (01/2015-06/2019) or with PNETs or SPNs diagnosed (01/2011-12/2019) at our hospital. The lesions were randomized 1:1 to the primary and validation cohorts. The regions of interest (ROIs) were manually drawn on each slice at DWI (b = 1500 s/mm²) from 3 T MRI. D (diffusion coefficient), D* (pseudodiffusion coefficient), f (perfusion fraction), distributed diffusion coefficient (DDC), α (diffusion heterogeneity index), mean diffusivity (MD) and mean kurtosis (MK) were obtained. The parameters with largest performance for differentiation were used to establish a diagnostic model.

RESULTS

There were 148, 56, and 60 patients with PDAC, PNET, and SPN, respectively. For differentiating PDACs from SPNs, f and MK values were used to establish a diagnostic model with areas under the receiver operating characteristic curves (AUCs) of 0.92 and 0.89 in the primary and validation groups, respectively. For distinguishing PDACs from PNETs, α and MK values were used to establish a diagnostic model with AUCs of 0.87 and 0.86 in the primary and validation groups, respectively. The accuracy rate of the subjective evaluation with the assistance of non-gaussian DWI models for differentiating PDAC from SPNs and PNETs were higher than that of subjective diagnosis alone (P < 0.05).

CONCLUSIONS

The non-gaussian DWI models could assist radiologists in accurately differentiating PDACs from PNETs and SPNs.

Primary extra-pancreatic pancreatic-type acinar cell carcinoma in the right perinephric space: A case report and review of literature

BACKGROUND

Primary extra-pancreatic pancreatic-type acinar cell carcinoma (ACC) is a rare malignancy, and has only been reported in the gastrointestinal tract, liver, and lymph nodes until now. Extra-pancreatic pancreatic-type ACC in the perinephric space has not been reported. Herein, we report the first case of ACC in the perinephric space and describe its clinical and imaging features, which should be considered when differentiating perinephric space neoplasms.

CASE SUMMARY

A 48-year-old man with a 5-year history of hypertension was incidentally found to have an asymptomatic right retroperitoneal mass during a routine health check-up. Laboratory tests were normal. Abdominal computed tomography and magnetic resonance imaging showed an oval hypervascular mass with a central scar and enhanced capsule in the right perinephric space. After surgical resection of the neoplasm, the diagnosis was primary extra-pancreatic pancreatic-type ACC. The patient was alive without recurrence or metastasis during a 15-mo follow-up.

CONCLUSION

This is the first report of an extra-pancreatic ACC in right perinephric space, which should be considered as a possible diagnosis in perinephric tumors.