CT-determined resectability of borderline resectable and unresectable pancreatic adenocarcinoma following FOLFIRINOX therapy

Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images

Pancreatic ductal adenocarcinoma (PDAC) stands out as the predominant malignant neoplasm affecting the pancreas, characterized by a poor prognosis, in most cases patients being diagnosed in a nonresectable stage. Image-based artificial intelligence (AI) models implemented in tumor detection, segmentation, and classification could improve diagnosis with better treatment options and increased survival. This review included papers published in the last five years and describes the current trends in AI algorithms used in PDAC. We analyzed the applications of AI in the detection of PDAC, segmentation of the lesion, and classification algorithms used in differential diagnosis, prognosis, and histopathological and genomic prediction. The results show a lack of multi-institutional collaboration and stresses the need for bigger datasets in order for AI models to be implemented in a clinically relevant manner.

Predicting Pathological Response to Preoperative Chemotherapy in Pancreatic Ductal Adenocarcinoma Using Post-Chemotherapy Computed Tomography Radiomics

INTRODUCTION

Assessing the response to preoperative treatment in pancreatic cancer provides valuable information for guiding subsequent treatment strategies. The present study aims to develop and validate a computed tomography (CT) radiomics-based machine learning (ML) model for predicting pathological response (PR) to preoperative chemotherapy in pancreatic ductal adenocarcinoma (PDAC).

METHODS

Retrospective data were analyzed from 86 PDAC patients undergoing neoadjuvant or conversion chemotherapy followed by surgical resection from January 2018 to May 2023. The cohort was randomly divided into training (70%, n = 60) and testing (30%, n = 26) sets. Favorable PR was defined as Evans grade IIb or greater. Radiomic features were extracted from post-chemotherapy CT images, and dimensionality reduction was performed using the least absolute shrinkage and selection operator (LASSO) logistic regression. Four ML classifiers (Light Gradient Boosting Machine (LGBM), Random Forest, AdaBoost, and Quadratic Discriminant Analysis) were evaluated for predicting a favorable PR. Model performance was primarily assessed using the area under the receiver operating characteristic curve (AUC), Brier score, and decision curve analysis.

RESULTS

Forty-one (47.7%) patients had a favorable PR. LASSO analysis on the training set identified five radiomic features. The LGBM model demonstrated the best performance, with a training AUC of 0.902 and a testing AUC of 0.923. It also exhibited the lowest Brier scores, both in training (0.136) and testing (0.135). Decision curve analysis further confirmed its clinical potential.

CONCLUSION

The CT radiomics-based ML model exhibited promising performance in predicting PR in PDAC after neoadjuvant/conversion chemotherapy. This suggests clinical utility in optimizing surgical candidates and timing of surgery, leading to personalized treatment strategies.

Using a CT-based scale to evaluate disease extension and the resectability of locally advanced thyroid cancer

OBJECTIVES

To establish a computed tomography (CT)-based scale to evaluate the resectability of locally advanced thyroid cancer.

METHODS

This twin-centre retrospective study included 95 locally advanced thyroid cancer patients from the 1st centre as the training cohort and 31 patients from the 2nd centre as the testing cohort, who were categorised into the resectable and unresectable groups. Three radiologists scored the CT scans of each patient by evaluating the extension to the recurrent laryngeal nerve (RLN), trachea, oesophagus, artery, vein, soft tissue, and larynx. A 14-score scale (including all comprised structures) and a 12-score scale (excluding larynx) were developed. Receiver-operating characteristic (ROC) analysis was used to evaluate the performance of the scales. Stratified fivefold cross-validation and external verification were used to validate the scale.

RESULTS

In the training cohort, compromised RLN (p < 0.001), trachea (p = 0.001), oesophagus (p = 0.002), artery (p < 0.001), vein (p = 0.005), and soft tissue (p < 0.001) were predictors for unresectability, while compromised larynx (p = 0.283) was not. The 12-score scale (AUC = 0.882, 95%CI: 0.812-0.952) was not inferior to the 14-score scale (AUC = 0.891, 95%CI: 0.823-0.960). In subgroup analysis, the AUCs of the 12-score scale were 0.826 for treatment-naïve patients and 0.976 for patients with prior surgery. The 12-score scale was further validated with a fivefold cross-validation analysis, with an overall accuracy of 78.9-89.4%. Finally, external validation using the testing cohort showed an AUC of 0.875.

CONCLUSIONS

The researchers built a CT-based 12-score scale to evaluate the resectability of locally advanced thyroid cancer. Validation with a larger sample size is required to confirm the efficacy of the scale.

CLINICAL RELEVANCE STATEMENT

This 12-score CT scale would help clinicians evaluate the resectability of locally advanced thyroid cancer.

KEY POINTS

• The researchers built a 12-score CT scale (including recurrent laryngeal nerve, trachea, oesophagus, artery, vein, and soft tissue) to evaluate the resectability of locally advanced thyroid cancer. • This scale has the potential to help clinicians make treatment plans for locally advanced thyroid cancer.

CT Imaging Assessment of Pancreatic Adenocarcinoma Resectability after Neoadjuvant Therapy: Current Status and Perspective on the Use of Radiomics

Pancreatic adenocarcinoma (PDAC) is the most common pancreatic cancer and is associated with poor prognosis, a high mortality rate, and a substantial number of healthy life years lost. Surgical resection is the primary treatment option for patients with resectable disease; however, only 10-20% of all patients with PDAC are eligible for resection at the time of diagnosis. In this context, neoadjuvant therapy has the potential to increase the number of patients who are eligible for resection, thereby improving the overall survival rate. For patients who undergo neoadjuvant therapy, computed tomography (CT) remains the primary imaging tool for assessing treatment response. Nevertheless, the interpretation of imaging findings in this context remains challenging, given the similarity between viable tumor and treatment-related changes following neoadjuvant therapy. In this review, following an overview of the various treatment options for PDAC according to its resectability status, we will describe the key challenges regarding CT-based evaluation of PDAC treatment response following neoadjuvant therapy, as well as summarize the literature on CT-based evaluation of PDAC treatment response, including the use of radiomics. Finally, we will outline key recommendations for the management of PDAC after neoadjuvant therapy, taking into consideration CT-based findings.

Computed Tomography-Based Radiomics Using Tumor and Vessel Features to Assess Resectability in Cancer of the Pancreatic Head

The preoperative prediction of resectability pancreatic ductal adenocarcinoma (PDAC) is challenging. This retrospective single-center study examined tumor and vessel radiomics to predict the resectability of PDAC in chemo-naïve patients. The tumor and adjacent arteries and veins were segmented in the portal-venous phase of contrast-enhanced CT scans, and radiomic features were extracted. Features were selected via stability and collinearity testing, and least absolute shrinkage and selection operator application (LASSO). Three models, using tumor features, vessel features, and a combination of both, were trained with the training set (N = 86) to predict resectability. The results were validated with the test set (N = 15) and compared to the multidisciplinary team's (MDT) performance. The vessel-features-only model performed best, with an AUC of 0.92 and sensitivity and specificity of 97% and 73%, respectively. Test set validation showed a sensitivity and specificity of 100% and 88%, respectively. The combined model was as good as the vessel model (AUC = 0.91), whereas the tumor model showed poor performance (AUC = 0.76). The MDT's prediction reached a sensitivity and specificity of 97% and 84% for the training set and 88% and 100% for the test set, respectively. Our clinician-independent vessel-based radiomics model can aid in predicting resectability and shows performance comparable to that of the MDT. With these encouraging results, improved, automated, and generalizable models can be developed that reduce workload and can be applied in non-expert hospitals.

A phase II study of neoadjuvant liposomal irinotecan with 5-FU and oxaliplatin (NALIRIFOX) in pancreatic adenocarcinoma

For patients with localized pancreatic cancer with minimal vascular involvement, optimal survivability requires a multidisciplinary approach of surgical resection and systemic chemotherapy. FOLFIRINOX is a combination chemotherapy regimen that offers promising results in the perioperative and metastatic settings; however, it can cause significant adverse effects. Such toxicity can negatively impact some patients, resulting in chemotherapy discontinuation or surgical unsuitability. In an effort to reduce toxicities and optimize outcomes, this investigation explores the safety and feasibility of substituting liposomal irinotecan (nal-IRI) for nonliposomal irinotecan to improve tumor drug delivery and potentially reduce toxicity. This regimen, NALIRIFOX, has the potential to be both safer and more effective when administered in the preoperative setting.

High-resolution pancreatic computed tomography for assessing pancreatic ductal adenocarcinoma resectability: a multicenter prospective study

OBJECTIVE

This prospective multicenter study aimed to evaluate the diagnostic performance of 80-kVp thin-section pancreatic CT in determining pancreatic ductal adenocarcinoma (PDAC) resectability according to the recent National Comprehensive Cancer Network (NCCN) guidelines.

METHODS

We prospectively enrolled surgical resection candidates for PDAC from six tertiary referral hospitals (study identifier: NCT03895177). All participants underwent pancreatic CT using 80 kVp tube voltage with 1-mm reconstruction interval. The local resectability was prospectively evaluated using NCCN guidelines at each center and classified into three categories: resectable, borderline resectable, and unresectable.

RESULTS

A total of 138 patients were enrolled; among them, 60 patients underwent neoadjuvant therapy. R0 resection was achieved in 103 patients (74.6%). The R0 resection rates were 88.7% (47/53), 52.4% (11/21), and 0.0% (0/4) for resectable, borderline resectable, and unresectable disease, respectively, in 78 patients who underwent upfront surgery. Meanwhile, the rates were 90.9% (20/22), 76.7% (23/30), and 25.0% (2/8) for resectable, borderline resectable, and unresectable PDAC, respectively, in patients who received neoadjuvant therapy. The area under curve of high-resolution CT in predicting R0 resection was 0.784, with sensitivity, specificity, and accuracy of 87.4% (90/103), 48.6% (17/35), and 77.5% (107/138), respectively. Tumor response was significantly associated with the R0 resection after neoadjuvant therapy (odds ratio [OR] = 38.99, p = 0.016).

CONCLUSION

An 80-kVp thin-section pancreatic CT has excellent diagnostic performance in assessing PDAC resectability, enabling R0 resection rates of 88.7% and 90.9% for patients with resectable PDAC who underwent upfront surgery and patients with resectable PDAC after neoadjuvant therapy, respectively.

KEY POINTS

• The margin-negative (R0) resection rates were 88.7% (47/53), 52.4% (11/21), and 0.0% (0/4) for resectable, borderline resectable, and unresectable pancreatic ductal adenocarcinoma (PDAC), respectively, on 80-kVp thin-section pancreatic CT in the 78 patients who underwent upfront surgery. • Among the 60 patients who underwent neoadjuvant therapy, the R0 rates were 90.9% (20/22), 76.7% (23/30), and 25.0% (2/8) for resectable, borderline resectable, and unresectable PDAC, respectively. • Tumor response, along with the resectability status on pancreatic CT, was significantly associated with the R0 resection rate after neoadjuvant therapy.

Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19-9

BACKGROUND

CT prediction of resectability and prognosis following neoadjuvant treatment (NAT) in patients with pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aims to determine whether addition of ¹⁸F-fluorodeoxyglucose (FDG) postiron emission tomography (PET)/MRI and carbohydrate antigen (CA) 19-9 to contrast-enhanced CT (CECT) can improve accuracy of predicting resectability compared to CECT alone and predict prognosis in PDAC patients after NAT.

METHODS

In this retrospective study, 120 PDAC patients (65 women; mean age, 66.7 years [standard deviation, 8.4]) underwent CECT, PET/MRI, and CA 19-9 examinations after NAT between January 2013 and June 2021. Three board-certified radiologists independently rated the overall resectability on a 5-point scale (score 5, definitely resectable) in three sessions (session 1, CECT; 2, CECT plus PET/MRI─no FDG avidity and no diffusion restriction at tumor-vessel contact indicated modification of CECT scores to ≥ 3; 3, CECT plus PET plus CA 19-9─no FDG avidity at tumor-vessel contact and normalized CA 19-9 indicated modification of CECT scores to ≥ 3). Jackknife free-response receiver operating characteristic method and generalized estimating equations were used to compare pooled area under the curve (AUC), sensitivity, and specificity of three sessions. Predictors for recurrence-free survival (RFS) were assessed using Cox regression analyses.

RESULTS

Each session showed different pooled AUC (session 1 vs. 2 vs. 3, 0.853 vs. 0.873 vs. 0.874, p = 0.026), sensitivity (66.2% [137/207] vs. 86.0% [178/207] vs. 84.5% [175/207], p < 0.001) and specificity (67.3% [103/153] vs. 58.8% [90/153] vs. 60.1% [92/153], p = 0.048). According to pairwise comparison, specificity of CECT plus PET/MRI was lower than that of CECT alone (adjusted p = 0.042), while there was no significant difference in specificity between CECT alone and CECT plus PET plus CA 19-9 (adjusted p = 0.081). Twenty-eight of 69 patients (40.6%) with R0 resection experienced tumor recurrence (mean follow-up, 18.0 months). FDG avidity at tumor-vessel contact on post-NAT PET (HR = 4.37, p = 0.033) and pathologically confirmed vascular invasion (HR = 5.36, p = 0.004) predicted RFS.

CONCLUSION

Combination of CECT, PET and CA 19-9 increased area under the curve and sensitivity for determining resectability, compared to CECT alone, without compromising the specificity. Furthermore, ¹⁸F-FDG avidity at tumor-vessel contact on post-NAT PET predicted RFS.

Predictive value of computed tomography on surgical resectability in locally advanced pancreatic cancer treated with multiagent induction chemotherapy: Results from a prospective, multicentre phase 2 trial (NEOLAP-AIO-PAK-0113)

PURPOSE

To assess the role of current imaging-based resectability criteria and the degree of radiological downsizing in locally advanced pancreatic adenocarcinoma (LAPC) after multiagent induction chemotherapy (ICT) in multicentre, open-label, randomized phase 2 trial.

METHOD

LAPC patients were prospectively treated with multiagent ICT followed by surgical exploration within the NEOLAP trial. All patients underwent CT scan at baseline and after ICT to assess resectability status according to national comprehensive cancer network guidelines (NCCN) criteria and response evaluation criteria in solid tumors (RECIST) at the local study center and retrospectively in a central review. Imaging results were compared in terms of local and central staging, downsizing and pathological resection status.

RESULTS

83 patients were evaluable for central review of baseline and restaging imaging results. Downstaging by central review was rarely seen after multiagent ICT (7.7%), whereas tumor downsizing was documented frequently (any downsizing 90.4%, downsizing to partial response (PR) according to RECIST: 26.5%). Patients with any downsizing showed no significant different R0 resection rate (37.3%) as patients that fulfilled the criteria of PR (40.9%). The sensitivity of any downsizing for predicting R0 resection was 97% with a negative predictive value (NPV) of 0.88. ROC-analysis revealed that tumor downsizing was a predictor of R0 resection (AUC 0.647, p = 0.028) with a best cut-off value of 22.5% downsizing yielding a sensitivity of 65% and a specificity of 61%.

CONCLUSIONS

Imaging-based tumor downsizing and not downstaging can guide the selection of patients with a realistic chance of R0-resection in LAPC after multi-agent ICT.

Multidisciplinary team diagnosis and treatment of pancreatic cancer: Current landscape and future prospects

The pathogenesis of pancreatic cancer has not been completely clear, there is no highly sensitive and specific detection method, so early diagnosis is very difficult. Despite the rapid development of tumor diagnosis and treatment, it is difficult to break through in the short term and the overall 5-year survival rate of pancreatic cancer is less than 8%. In the face of the increasing incidence of pancreatic cancer, in addition to strengthening basic research, exploring its etiology and pathogenesis, it is urgent to optimize the existing diagnosis and treatment methods through standard multidisciplinary team (MDT), and formulate personalized treatment plan to achieve the purpose of improving the curative effect. However, there are some problems in MDT, such as insufficient understanding and enthusiasm of some doctors, failure to operate MDT according to the system, lack of good communication between domestic and foreign peers, and lack of attention in personnel training and talent echelon construction. It is expected to protect the rights and interests of doctors in the future and ensure the continuous operation of MDT. To strengthen the research on the diagnosis and treatment of pancreatic cancer, MDT can try the Internet +MDT mode to improve the efficiency of MDT.

Prediction of Margin-Negative Resection of Pancreatic Ductal Adenocarcinoma Following Neoadjuvant Therapy: Diagnostic Performance of NCCN Criteria for Resection vs. CT-Determined Resectability

BACKGROUND

Accurate assessment of pancreatic ductal adenocarcinoma (PDAC) resectability after neoadjuvant therapy (NAT) is crucial. Recently, the NCCN introduced criteria for resection of PDAC following NAT.

METHODS

We analyzed 127 patients who underwent NAT and pancreatectomy for PDAC between January 2010 and March 2020. CT-determined resectability according to the NCCN guideline, and CA 19-9 level was evaluated before and after NAT. Diagnostic performance of the NCCN criteria for margin-negative (R0) resection was investigated and compared with CT alone.

RESULTS

R0 resection was achieved in 104 (81.9%) patients. After NAT, there were 30 (23.6%) resectable, 90 (70.9%) borderline resectable, and seven (5.5%) locally advanced tumors. Significantly decreased or stable CA 19-9 levels were noted in 114 (89.8%) patients. The sensitivity and specificity of the NCCN criteria were 87.5% (91/104) and 21.7% (5/23), respectively, which were significantly different from CT including only resectable PDAC (26.9% [28/104] and 91.3% [21/23]; p<0.001), but less prominently different from CT including resectable and borderline resectable PDAC (95.2% [99/104]; p=0.022 and 8.7% [2/23]; p=0.375).

CONCLUSIONS

The NCCN criteria for resection following NAT showed high sensitivity and low specificity for predicting R0 resection. It had supplementary benefit over CT alone, mainly in preventing underestimation of R0 resection.

Retrospective Evaluation of Treatment Response in Patients with Nonmetastatic Pancreatic Cancer Using CT and CA 19-9

Background Imaging studies have limitations in evaluating pancreatic ductal adenocarcinoma (PDAC) treatment response. Purpose To investigate the effectiveness of combined CT and carbohydrate antigen 19-9 (CA 19-9) evaluation at 8 weeks after first-line treatment to predict overall survival (OS) of patients with nonmetastatic PDAC. Materials and Methods Patients with nonmetastatic PDAC who received first-line treatment with either chemotherapy or concurrent chemoradiation in a single-center PDAC cohort registry were retrospectively enrolled in the study between January 2013 and December 2016. Follow-up CT images obtained 8 weeks after treatment were evaluated according to Response Evaluation Criteria in Solid Tumors. Patients with partial response (PR) or stable disease (SD) were defined as CT responders, and those with progressive disease (PD) were defined as CT nonresponders. Patients with a normalized CA 19-9 level at 8-week follow-up were defined as CA 19-9 responders, and those with a nonnormalized or nonelevated CA 19-9 level were defined as CA 19-9 nonresponders. OS was compared using the Kaplan-Meier method with Breslow analysis. Results A total of 197 patients (mean age ± standard deviation, 65 years ± 10; 107 men) were evaluated. Patients with PD (n = 17) showed shorter OS than those with SD (n = 147; P < .001) or PR (n = 33; P = .003). OS did not differ between the patients with PR and those with SD (P = .60). When the CT and CA 19-9 responses were integrated, OS was longest in CT and CA 19-9 responders (group 1, n = 27; median OS, 26.6 months [95% CI: 9.0, 44.1]), followed by CT responders but CA 19-9 nonresponders (group 2, n = 153; median OS, 15.9 months [95% CI: 13.3, 18.5]; P = .007 vs group 1) and CT and CA 19-9 nonresponders (group 3, n = 17; median OS, 6.5 months [95% CI: 0.8, 12.2]; P < .001 vs group 2). Conclusion Integrated evaluation with CT and carbohydrate antigen 19-9 response allowed more accurate stratification of survival in patients with pancreatic ductal adenocarcinoma in the early treatment period than did evaluation according to Response Evaluation Criteria in Solid Tumors. © RSNA, 2022 Online supplemental material is available for this article.

Application of Magnetic Resonance Imaging in Neoadjuvant Treatment of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignant tumors of the human digestive system. Due to its insidious onset, many patients have already lost the opportunity for radical resection upon tumor diagnosis. In recent years, neoadjuvant treatment for patients with borderline resectable PDAC has been recommended by multiple guidelines to increase the resection rate of radical surgery and improve the postoperative survival. However, further developments are required to accurately assess the tumor response to neoadjuvant therapy and to select the population suitable for such treatment. Reductions in drug toxicity and the number of neoadjuvant cycles are also critical. At present, the clinical evaluation of neoadjuvant treatment is mainly based on several serological and imaging indicators; however, the unique characteristics of PDAC and the insufficient sensitivity and specificity of the markers render this system ineffective. The imaging evaluation system, magnetic resonance imaging (MRI), has its own unique imaging advantages compared with computed tomography (CT) and other imaging examinations. One key advantage is the ability to reflect the changes more rapidly in tumor tissue components, such as the degree of fibrosis, microvessel density, and tissue hypoxia. It can also perform multiparameter quantitative analysis of tumor tissue and changes, attributing to its increasingly important role in imaging evaluation, and potentially the evaluation of neoadjuvant treatment of pancreatic cancer, as several current articles have studied. At the same time, owing to the complexity of MRI and some of its limitations, its wider application is limited. Compared with CT imaging, few relevant studies have been conducted. In this review article, we will investigate and summarize the advantages, limitations, and future development of MRI in the evaluation of neoadjuvant treatment of PDAC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

[Surgical treatment of pancreatic cancer-What is new?]

The incidence of pancreatic ductal adenocarcinoma is continuously increasing and will become the second leading cause of cancer-related death in Europe and the USA by 2030. With a 5-year overall survival rate of less than 10% the prognosis remains poor. So far surgical tumor resection remains the only curative treatment option, which is now partially supported by multimodal neoadjuvant and adjuvant therapy concepts. Due to the aggressive tumor biology patients with advanced pancreatic cancer in particular can profit from these multimodal therapy concepts. Additionally, in recent years surgical treatment was optimized, the criteria for tumor resectablity were defined and minimally invasive surgery was widely introduced. This review article summarizes the newest developments and the new German S3 guidelines concerning surgery of pancreatic cancer.

Imaging Assessment of Pancreatic Cancer Resectability After Neoadjuvant Therapy: AJR Expert Panel Narrative Review

Despite important innovations in the treatment of pancreatic ductal adenocarcinoma (PDAC), PDAC remains a disease with poor prognosis and high mortality. A key area for potential improvement in the management of PDAC, aside from earlier detection in patients with treatable disease, is the improved ability of imaging techniques to differentiate treatment response after neoadjuvant therapy (NAT) from worsening disease. It is well established that current imaging techniques cannot reliably make this distinction. This narrative review provides an update on the imaging assessment of pancreatic cancer resectability after NAT. Current definitions of borderline resectable PDAC, as well as implications for determining likely patient benefit from NAT, are described. Challenges associated with PDAC pathologic evaluation and surgical decision making that are of relevance to radiologists are discussed. Also explored are the specific limitations of imaging in differentiating the response after NAT from stable or worsening disease, including issues relating to protocol optimization, tumor size assessment, vascular assessment, and liver metastasis detection. The roles of MRI as well as PET and/or hybrid imaging are considered. Finally, a short PDAC reporting template is provided for use after NAT. The highlighted methods seek to improve radiologists' assessment of PDAC treatment response after NAT.

Computed tomography-based radiomic to predict resectability in locally advanced pancreatic cancer treated with chemotherapy and radiotherapy

BACKGROUND

Surgical resection after neoadjuvant treatment is the main driver for improved survival in locally advanced pancreatic cancer (LAPC). However, the diagnostic performance of computed tomography (CT) imaging to evaluate the residual tumour burden at restaging after neoadjuvant therapy is low due to the difficulty in distinguishing neoplastic tissue from fibrous scar or inflammation. In this context, radiomics has gained popularity over conventional imaging as a complementary clinical tool capable of providing additional, unprecedented information regarding the intratumor heterogeneity and the residual neoplastic tissue, potentially serving in the therapeutic decision-making process.

AIM

To assess the capability of radiomic features to predict surgical resection in LAPC treated with neoadjuvant chemotherapy and radiotherapy.

METHODS

Patients with LAPC treated with intensive chemotherapy followed by ablative radiation therapy were retrospectively reviewed. One thousand six hundred and fifty-five radiomic features were extracted from planning CT inside the gross tumour volume. Both extracted features and clinical data contribute to create and validate the predictive model of resectability status. Patients were repeatedly divided into training and validation sets. The discriminating performance of each model, obtained applying a LASSO regression analysis, was assessed with the area under the receiver operating characteristic curve (AUC). The validated model was applied to the entire dataset to obtain the most significant features.

RESULTS

Seventy-one patients were included in the analysis. Median age was 65 years and 57.8% of patients were male. All patients underwent induction chemotherapy followed by ablative radiotherapy, and 19 (26.8%) ultimately received surgical resection. After the first step of variable selections, a predictive model of resectability was developed with a median AUC for training and validation sets of 0.862 (95%CI: 0.792-0.921) and 0.853 (95%CI: 0.706-0.960), respectively. The validated model was applied to the entire dataset and 4 features were selected to build the model with predictive performance as measured using AUC of 0.944 (95%CI: 0.892-0.996).

CONCLUSION

The present radiomic model could help predict resectability in LAPC after neoadjuvant chemotherapy and radiotherapy, potentially integrating clinical and morphological parameters in predicting surgical resection.

Identifying optimal candidates for tumor resection among borderline and locally advanced pancreatic cancer: A population-based predictive model

BACKGROUND

Whether patients with borderline resectable and locally advanced pancreatic cancer (BR/LAPC) benefit from resection of the primary cancer is controversial. We developed a nomogram to screen who would benefit from surgery for the primary tumor.

METHODS

We identified patients from the Surveillance, Epidemiology, and End Results (SEER) database and then divided them into surgical and non-surgical groups. A 1:1 propensity score matching (PSM) was used to mitigate the bias. We hypothesized that patients who underwent surgery would benefit from surgery by having a longer median overall survival (OS) than patients who did not undergo surgery. Univariate and multivariate logistic regression analyses were used to determine the variables affecting surgical outcomes, and a nomogram was created based on the multivariate logistic results. Finally, we verified the discrimination and calibration of the nomogram with receiver operator characteristic (ROC) curve and calibration plots.

RESULTS

A total of 518 pairs of surgical and non-surgical pancreatic cancer patients were matched after PSM. Survival curves showed longer OS in the surgical group than in the non-surgical group, median survival times were 14 months versus 8 months. In the surgical group, 340 (65.63%) patients have a longer survival time than 8 months (beneficial group). Multifactorial logit regression results showed that including age, tumor size, degree of differentiation, and chemotherapy were significant influences on the benefit of surgery for primary tumors and were used as predictors to construct a nomogram. The area under the ROC curve (AUC) reached 0.747 and 0.706 in the training and validation sets.

CONCLUSION

We developed a practical predictive model to support clinical decision-making that can be used to help clinicians determine if there is a benefit to surgical resection of the primary tumor in patients with BR/LAPC.

CT Radiomic Features of Superior Mesenteric Artery Involvement in Pancreatic Ductal Adenocarcinoma: A Pilot Study

Background Current imaging methods for prediction of complete margin resection (R0) in patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To investigate whether tumor-related and perivascular CT radiomic features improve preoperative assessment of arterial involvement in patients with surgically proven PDAC. Materials and Methods This retrospective study included consecutive patients with PDAC who underwent surgery after preoperative CT between 2012 and 2019. A three-dimensional segmentation of PDAC and perivascular tissue surrounding the superior mesenteric artery (SMA) was performed on preoperative CT images with radiomic features extracted to characterize morphology, intensity, texture, and task-based spatial information. The reference standard was the pathologic SMA margin status of the surgical sample: SMA involved (tumor cells ≤1 mm from margin) versus SMA not involved (tumor cells >1 mm from margin). The preoperative assessment of SMA involvement by a fellowship-trained radiologist in multidisciplinary consensus was the comparison. High reproducibility (intraclass correlation coefficient, 0.7) and the Kolmogorov-Smirnov test were used to select features included in the logistic regression model. Results A total of 194 patients (median age, 66 years; interquartile range, 60-71 years; age range, 36-85 years; 99 men) were evaluated. Aside from surgery, 148 patients underwent neoadjuvant therapy. A total of 141 patients' samples did not involve SMA, whereas 53 involved SMA. A total of 1695 CT radiomic features were extracted. The model with five features (maximum hugging angle, maximum diameter, logarithm robust mean absolute deviation, minimum distance, square gray level co-occurrence matrix correlation) showed a better performance compared with the radiologist assessment (model vs radiologist area under the curve, 0.71 [95% CI: 0.62, 0.79] vs 0.54 [95% CI: 0.50, 0.59]; P < .001). The model showed a sensitivity of 62% (33 of 53 patients) (95% CI: 51, 77) and a specificity of 77% (108 of 141 patients) (95% CI: 60, 84). Conclusion A model based on tumor-related and perivascular CT radiomic features improved the detection of superior mesenteric artery involvement in patients with pancreatic ductal adenocarcinoma. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Do and Kambadakone in this issue.

Neoadjuvant therapy vs. upfront surgery for resectable pancreatic cancer: An update on a systematic review and meta-analysis

The effectiveness of neoadjuvant therapy (NAT) remains controversial in the treatment of pancreatic cancer (PC). Therefore, this meta-analysis aimed to investigate the clinical differences between NAT and upfront surgery (US) in resectable pancreatic cancer (RPC). Eligible studies were retrieved from PubMed, Embase, and Cochrane Library. The endpoints assessed were R0 resection rate, pathological T stage < 2 rate, positive lymph node rate, and overall survival. A total of 4,588 potentially relevant studies were identified, and 13 studies were included in this study. In patients with RPC, this meta-analysis showed that NAT presented an increased R0 resection rate, pathological T stage < 2 rate, and a remarkably reduced positive lymph node rate compared to US. However, patients receiving NAT did not result in a significantly increased overall survival. These findings supported the application of NAT, especially as a patient selection strategy, in the management of RPC. Additional large clinical studies are needed to determine whether NAT is superior to US.

CT-diagnosed extra-pancreatic extension of pancreatic ductal adenocarcinoma is a more reliable prognostic factor for survival than pathology-diagnosed extension

OBJECTIVES

To determine the correlation between CT-diagnosed extra-pancreatic extension of pancreatic ductal adenocarcinoma (PDAC), pathology-diagnosed extra-pancreatic extension, and survival in patients with PDAC.

METHODS

This retrospective study included 87 patients with resected PDAC. Two radiologists evaluated negative ((i) tumours surrounded by the pancreatic parenchyma and (ii) tumours contacting the pancreatic surface) or positive ((iii) tumours with peri-pancreatic strand appearances and/or with expansive growth) CT-diagnosed extra-pancreatic extension. Clinical, pathological, and CT imaging characteristics predicting disease-free survival (DFS) and overall survival (OS) were assessed using Cox proportional-hazards models. Diagnostic accuracy for pathology-diagnosed extra-pancreatic extension was also assessed.

RESULTS

CT-diagnosed extra-pancreatic extension (42/87 tumours, 48.3%; κ = 0.82) had a higher hazard ratio (HR) for the DFS (HR, 5.30; p < 0.01) and OS (HR, 5.31; p < 0.01) rates than pathology-diagnosed extension in univariable analyses. It was also an independent prognostic factor for the DFS (HR, 4.22; p < 0.01) and OS (HR, 4.38; p < 0.01) rates in multivariable analyses. Of 45 tumours without CT-diagnosed extra-pancreatic extension, pathology-diagnosed extra-pancreatic extension was observed in 2/8 (25.0%) and 32/37 (86.5%) tumours with CT categories (i) and (ii), respectively. However, the differences in the survival rates between patients with CT categories (i) and (ii) were insignificant, although those in the latter category had significantly better survival rates than those with CT-diagnosed extra-pancreatic extension (category (iii)).

CONCLUSIONS

CT-diagnosed extra-pancreatic extension was a better prognostic factor than pathology-diagnosed extension and considered an independent factor for the postoperative DFS and OS rates with reasonable frequency and high reproducibility, despite the low diagnostic accuracy for predicting pathology-diagnosed extra-pancreatic extension.

KEY POINTS

• A CT-diagnosed extra-pancreatic extension had a higher hazard ratio for both disease-free survival and overall survival compared to pathology-diagnosed extension in univariable survival analyses. • A CT-diagnosed extra-pancreatic extension was a significant independent predictor of both disease-free survival and overall survival, as observed in multivariable survival analyses. • Patients with tumours contacting with the pancreatic surface on CT images (CT category (ii)) showed similar survival rates to those whose tumours were surrounded by the pancreatic parenchyma (CT category (i)), although many tumours with CT category (ii) extended pathologically beyond the pancreas.

How to approach pancreatic cancer after neoadjuvant treatment: assessment of resectability using multidetector CT and tumor markers

OBJECTIVES

To investigate clinical and CT factors associated with local resectability in patients with nonmetastatic pancreatic cancers after neoadjuvant chemotherapy ± radiation therapy (CRT).

METHODS

This retrospective study included consecutive patients with nonmetastatic pancreatic cancers who underwent neoadjuvant CRT between June 2009 and June 2019. Tumor size, tumor-vascular contact with artery/vein, and local resectability categories (resectable, borderline resectable, or locally advanced) were assessed at baseline and post-CRT CT. Baseline and post-CRT carbohydrate antigen (CA) 19-9 levels were also assessed. Clinical or imaging features related to R0 resection were determined using logistic regression analysis.

RESULTS

A total of 179 patients (mean age, 62.4 ± 9.3 years; 92 men) were included. After neoadjuvant CRT, 105 (58.7%) patients received R0 resection, while 74 (41.3%) did not. R0 resection rates were significantly different according to post-CRT CT resectability categories (p < 0.001): 82.8% (48/58), 70.1% (47/67), and 18.5% (10/54) for resectable, borderline resectable, and locally advanced disease, respectively. For post-CRT borderline resectable disease, ≥ 50% decrease in CA 19-9 was significantly associated with R0 resection (odds ratio (OR), 3.160; p = 0.02). For post-CRT locally advanced disease, small post-CRT tumor size ≤ 2 cm (OR, 9.668; p = 0.026) and decreased tumor-arterial contact (OR, 24.213; p = 0.022) were significantly associated with R0 resection.

CONCLUSION

Post-CRT CT resectability categorization may be useful for the assessment of R0 resectability in patients with pancreatic cancer following neoadjuvant CRT. Additionally, ≥ 50% decrease in CA 19-9 was associated with R0 resection in post-CRT borderline resectable disease, while small post-CRT tumor size and decreased tumor-arterial contact were with locally advanced disease.

KEY POINTS

• R0 resection rates following neoadjuvant chemotherapy ± radiation therapy (CRT) were 82.8%, 70.1%, and 18.5% in resectable, borderline resectable, and locally advanced disease, respectively, at post-CRT CT (p < 0.001). • For post-CRT borderline resectable disease, ≥ 50% decrease in carbohydrate antigen (CA) 19-9 was significantly associated with R0 resection. • For post-CRT locally advanced disease, small post-CRT tumor size ≤ 2 cm and decreased tumor-arterial contact were significantly associated with R0 resection.

Role of imaging in evaluating the response after neoadjuvant treatment for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Despite the development of multimodality treatments, including surgical resection, radiotherapy, and chemotherapy, the long-term prognosis of patients with PDAC remains poor. Recently, the introduction of neoadjuvant treatment (NAT) has made more patients amenable to surgery, increasing the possibility of R0 resection, treatment of occult micro-metastasis, and prolongation of overall survival. Imaging plays a vital role in tumor response evaluation after NAT. However, conventional imaging modalities such as multidetector computed tomography have limited roles in the assessment of tumor resectability after NAT for PDAC because of the similar appearance of tissue fibrosis and tumor infiltration. Perfusion computed tomography, using blood perfusion as a biomarker, provides added value in predicting the histopathologic response of PDAC to NAT by reflecting the changes in tumor matrix and fibrosis content. Other imaging technologies, including diffusion-weighted imaging of magnetic resonance imaging and positron emission tomography, can reveal the tumor response by monitoring the structural changes in tumor cells and functional metabolic changes in tumors after NAT. In addition, with the renewed interest in data acquisition and analysis, texture analysis and radiomics have shown potential for the early evaluation of the response to NAT, thus improving patient stratification to achieve accurate and intensive treatment. In this review, we briefly introduce the application and value of NAT in resectable and unresectable PDAC. We also summarize the role of imaging in evaluating the response to NAT for PDAC, as well as the advantages, limitations, and future development directions of current imaging techniques.

Optimized scan delay for late hepatic arterial or pancreatic parenchymal phase in dynamic contrast-enhanced computed tomography with bolus-tracking method

OBJECTIVES

To determine the optimal scan delay corresponding to individual hemodynamic status for pancreatic parenchymal phase in dynamic contrast-enhanced CT of the abdomen.

METHODS

One hundred and fourteen patients were included in this retrospective study (69 males and 45 females; mean age, 67.9 ± 12.1 years; range, 39-87 years). These patients underwent abdominal dynamic contrast-enhanced CT between November 2019 and May 2020. We calculated and recorded the time from contrast material injection to the bolus-tracking trigger of 100 Hounsfield unit (HU) at the abdominal aorta (s) (Time_TRIG) and scan delay from the bolus-tracking trigger to the initiation of pancreatic parenchymal phase scanning (s) (Time_SD). The scan delay ratio (SDR) was defined by dividing the Time_SD by Time_TRIG. Non-linear regression analysis was conducted to assess the association between CT number of the pancreas and SDR and to reveal the optimal SDR, which was ≥120 HU in pancreatic parenchyma.

RESULTS

The non-linear regression analysis showed a significant association between CT number of the pancreas and the SDR (p < 0.001). The mean Time_TRIG and Time_SD were 16.1 s and 16.8 s, respectively. The SDR to peak enhancement of the pancreas (123.5 HU) was 1.00. An SDR between 0.89 and 1.18 shows an appropriate enhancement of the pancreas (≥120 HU).

CONCLUSION

The CT number of the pancreas peaked at an SDR of 1.00, which means Time_SD should be approximately the same as Time_TRIG to obtain appropriate pancreatic parenchymal phase images in dynamic contrast-enhanced CT with bolus-tracking method.

ADVANCES IN KNOWLEDGE

The hemodynamic state is different in each patient; therefore, scan delay from the bolus-tracking trigger should also vary based on the time from contrast material injection to the bolus-tracking trigger. This is necessary to obtain appropriate late hepatic arterial or pancreatic parenchymal phase images in dynamic contrast-enhanced CT of the abdomen.

Radiomics-Assisted Presurgical Prediction for Surgical Portal Vein-Superior Mesenteric Vein Invasion in Pancreatic Ductal Adenocarcinoma

Objectives

To develop a radiomics signature for predicting surgical portal vein-superior mesenteric vein (PV-SMV) in patients with pancreatic ductal adenocarcinoma (PDAC) and measure the effect of providing the predictions of radiomics signature to radiologists with different diagnostic experiences during imaging interpretation.

Methods

Between February 2008 and June 2020, 146 patients with PDAC in pancreatic head or uncinate process from two institutions were retrospectively included and randomly split into a training (n = 88) and a validation (n =58) cohort. Intraoperative vascular exploration findings were used to identify surgical PV-SMV invasion. Radiomics features were extracted from the portal venous phase CT images. Radiomics signature was built with a linear elastic-net regression model. Area under receiver operating characteristic curve (AUC) of the radiomics signature was calculated. A senior and a junior radiologist independently review CT scans and made the diagnosis for PV-SMV invasion both with and without radiomics score (Radscore) assistance. A 2-sided Pearson's chi-squared test was conducted to evaluate whether there was a difference in sensitivity, specificity, and accuracy between the radiomics signature and the unassisted radiologists. To assess the incremental value of providing Radscore predictions to the radiologists, we compared the performance between unassisted evaluation and Radscore-assisted evaluation by using the McNemar test.

Results

Numbers of patients identified as presence of surgical PV-SMV invasion were 33 (37.5%) and 19 (32.8%) in the training and validation cohort, respectively. The radiomics signature achieved an AUC of 0.848 (95% confidence interval, 0.724-0.971) in the validation cohort and had a comparable sensitivity, specificity, and accuracy as the senior radiologist in predicting PV-SMV invasion (all p-values > 0.05). Providing predictions of radiomics signature increased both radiologists' sensitivity in identifying PV-SMV invasion, while only the increase of the junior radiologist was significant (63.2 vs 89.5%, p-value = 0.025) instead of the senior radiologist (73.7 vs 89.5%, p-value = 0.08). Both radiologists' accuracy had no significant increase when provided radiomics signature assistance (both p-values > 0.05).

Conclusions

The radiomics signature can predict surgical PV-SMV invasion in patients with PDAC and may have incremental value to the diagnostic performance of radiologists during imaging interpretation.

CT in the prediction of margin-negative resection in pancreatic cancer following neoadjuvant treatment: a systematic review and meta-analysis

OBJECTIVES

We aimed to systematically evaluate the diagnostic accuracy of CT-determined resectability following neoadjuvant treatment for predicting margin-negative resection (R0 resection) in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

Original studies with sufficient details to obtain the sensitivity and specificity of CT-determined resectability following neoadjuvant treatment, with a reference on the pathological margin status, were identified in PubMed, EMBASE, and Cochrane databases until February 24, 2020. The identified studies were divided into two groups based on the criteria of R0 resectable tumor (ordinary criterion: resectable PDAC alone; extended criterion: resectable and borderline resectable PDAC). The meta-analytic summary of the sensitivity and specificity for each criterion was estimated separately using a bivariate random-effect model. Summary results of the two criteria were compared using a joint-model bivariate meta-regression.

RESULTS

Of 739 studies initially searched, 6 studies (6 with ordinary criterion and 5 with extended criterion) were included for analysis. The meta-analytic summary of sensitivity and specificity was 45% (95% confidence interval [CI], 19-73%; I² = 88.3%) and 85% (95% CI, 65-94%; I² = 60.5%) for the ordinary criterion, and 81% (95% CI, 71-87%; I² = 0.0%) and 42% (95% CI, 28-57%; I² = 6.2%) for the extended criterion, respectively. The diagnostic accuracy significantly differed between the two criteria (p = 0.02).

CONCLUSIONS

For determining resectability on CT, the ordinary criterion might be highly specific but insensitive for predicting R0 resection, whereas the extended criterion increased sensitivity but would decrease specificity. Further investigations using quantitative parameters may improve the identification of R0 resection.

KEY POINTS

• CT-determined resectability of PDAC after neoadjuvant treatment using the ordinary criterion shows low sensitivity and high specificity in predicting R0 resection. • With the extended criterion, CT-determined resectability shows higher sensitivity but lower specificity than with the ordinary criterion. • CT-determined resectability with both criteria achieved suboptimal diagnostic performances, suggesting that care should be taken while selecting surgical candidates and when determining the surgical extent after neoadjuvant treatment in patients with PDAC.