Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma.

Despite tremendous gains in the molecular understanding of exocrine pancreatic cancer, the prognosis for this disease remains very poor, largely because of delayed disease detection and limited effectiveness of systemic therapies. Both incidence rates and mortality rates for pancreatic cancer have increased during the past decade, in contrast to most other solid tumor types. Recent improvements in multimodality care have substantially improved overall survival, local control, and metastasis-free survival for patients who have localized tumors that are amenable to surgical resection. The widening gap in prognosis between patients with resectable and unresectable or metastatic disease reinforces the importance of detecting pancreatic cancer sooner to improve outcomes. Furthermore, the developing use of therapies that target tumor-specific molecular vulnerabilities may offer improved disease control for patients with advanced disease. Finally, the substantial morbidity associated with pancreatic cancer, including wasting, fatigue, and pain, remains an under-addressed component of this disease, which powerfully affects quality of life and limits tolerance to aggressive therapies. In this article, the authors review the current multidisciplinary standards of care in pancreatic cancer with a focus on emerging concepts in pancreatic cancer detection, precision therapy, and survivorship.

Microbiota and metabolite alterations in pancreatic head and body/tail cancer patients.

Pancreatic head cancer (PHC) and pancreatic body/tail cancer (PBTC) have distinct clinical and biological behaviors. The microbial and metabolic differences in PHC and PBTC have not been studied. The pancreatic microbiota and metabolome of 15 PHC and 8 PBTC tissues and their matched nontumor tissues were characterized using 16S rRNA amplicon sequencing and untargeted metabolomics. At the genus level, Bradyrhizobium was increased while Corynebacterium and Ruminococcus were decreased in the PHC tissues (Head T) compared with the matched nontumor tissues (Head N) significantly. Shuttleworthia, Bacillus, and Bifidobacterium were significantly decreased in the PBTC tissues (Body/Tail T) compared with the matched nontumor tissues (Body/Tail N). Significantly, Ileibacterium was increased whereas Pseudoxanthomonas was decreased in Head T and Body/Tail T, and Lactobacillus was increased in Head T but decreased in Body/Tail T. A total of 102 discriminative metabolites were identified between Head T and Head N, which were scattered through linoleic acid metabolism and purine metabolism pathways. However, there were only four discriminative metabolites between Body/Tail T and Body/Tail N, which were related to glycerophospholipid metabolism and autophagy pathways. The differential metabolites in PHC and PBTC were commonly enriched in alpha-linolenic acid metabolism and choline metabolism in cancer pathways. Eubacterium decreased in Head T was positively correlated with decreased linoleic acid while negatively correlated with increased arachidyl carnitine and stearoylcarnitine. Bacillus decreased in Body/Tail T was negatively correlated with increased L-carnitine. These microbiota and metabolites deserve further investigations to reveal their roles in the pathogenesis of PHC and PBTC, providing clues for future treatments.

Update in the management of gastroenteropancreatic neuroendocrine tumors.

Neuroendocrine neoplasms are a diverse group of neoplasms that can occur in various areas throughout the body. Well-differentiated neuroendocrine tumors (NETs) most often arise in the gastrointestinal tract, termed gastroenteropancreatic neuroendocrine tumors (GEP-NETs). Although GEP-NETs are still uncommon, their incidence and prevalence have been steadily increasing over the past decades. The primary treatment for GEP-NETs is surgery, which offers the best chance for a cure. However, because GEP-NETs are often slow-growing and do not cause symptoms until they have spread widely, curative surgery is not always an option. Significant advances have been made in systemic and locoregional treatment options in recent years, including peptide-receptor radionuclide therapy with α and ß emitters, somatostatin analogs, chemotherapy, and targeted molecular therapies.

Hand therapy interventions for the prevention of chemotherapy-induced peripheral neuropathy of the hands in patients with pancreatic cancer.

BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN), a common problem, can impair function and quality of life in patients, potentially limiting chemotherapy and adversely affecting outcomes. METHODS: This trial compared investigational hand therapy intervention (Investigational) compared with a traditional occupational therapy approach (Traditional) to prevent CIPN in patients with pancreatic cancer receiving gemcitabine and albumin-bound paclitaxel containing regimens. RESULTS: forty-nine patients were enrolled with 40 evaluable for statistical analysis (21 Investigational/19 Traditional). CIPN in the hands was reported in 6 patients (28.6%) in Investigational, and 4 (21.1%) in Traditional P = .721. Kaplan-Meier analysis showed a mean time-to-event of 76.0 days (90% CI: 68.5, 83.6), and 75.8 (90% CI: 68.5, 83.2) days respectively, P = .614. Fifteen patients in each group (78.9% Traditional, 71.4% in Investigational) were censored as they did not develop CIPN. No correlation was found between CIPN risk and age, sex, BMI, disease stage, performance status, or chemotherapy dose. CONCLUSION: Seventy-four percent of patients receiving gemcitabine, albumin-bound paclitaxel, and cisplatin did not develop CIPN of the hands by day 84. There was no statistical difference in time to onset of CIPN between the two groups. Early adaption of occupational therapy may prevent early onset CIPN in chemotherapy patients. CLINICALTRIALS.GOV IDENTIFIER: NCT05374876.

The Revised Kyoto Criteria and Risk of Malignancy Among Patients With Intraductal Papillary Mucinous Neoplasms.

BACKGROUND & AIMS: The revised Kyoto guidelines have a new catalog of high-risk stigmata and worrisome features for the risk stratification of intraductal papillary mucinous neoplasms (IPMNs). We aimed to validate the stratification system in terms of short- and long-term risks of pancreatic carcinoma. METHODS: We included 3336 patients diagnosed with IPMNs in 2000-2021 and examined short-term (≤6 months) and long-term risks of pancreatic carcinoma diagnosis. We used the multivariable competing-risks proportional hazards regression model to calculate subdistribution hazard ratios for long-term incidence of pancreatic carcinoma with adjustment for potential confounders. RESULTS: In short-term analyses, pancreatic carcinomas were prevalent predominantly in IPMNs with high-risk stigmata (49% vs 1.3% and 0.05% in IPMNs with worrisome features and no risk factors, respectively). In long-term analyses of worrisome features, the main pancreatic duct diameter of 5-9.9 mm, acute pancreatitis, and IPMN growth rate of 2.5 mm/y were associated with a high incidence with multivariable subdistribution hazard ratios of 3.46 (95% confidence interval [CI], 2.04-5.89), 5.65 (95% CI, 1.86-17.2), and 3.83 (95% CI, 2.14-6.86), respectively. An increasing number of worrisome features at baseline was associated with a higher prevalence and incidence of pancreatic carcinoma (Ptrend < .001). Patients with 1, 2, and 3-4 worrisome features had multivariable subdistribution hazard ratios for pancreatic cancer incidence of 1.43 (95% CI, 0.93-2.19), 2.17 (95% CI, 1.17-4.05), and 10.1 (95% CI, 4.20-24.5), respectively (vs no positive feature). CONCLUSIONS: The revised Kyoto criteria stratify IPMN patients well in terms of the short- and long-term risks of pancreatic carcinoma diagnosis, potentially informing personalized patient management.

Multimodal pancreatic cancer detection using methylated DNA biomarkers in pancreatic juice and plasma CA 19-9: A prospective multicenter study.

BACKGROUND AND AIMS: In previous studies methylated DNA markers (MDMs) have been identified in pancreatic juice (PJ) for detecting pancreatic ductal adenocarcinoma (PDAC). In this prospective multicenter study, the sensitivity and specificity characteristics of this panel of PJ-MDMs was evaluated standalone and in combination with plasma CA 19-9. METHODS: Paired PJ and plasma were assayed from 88 biopsy-proven treatment naïve PDAC cases and 134 controls (normal pancreas: 53, chronic pancreatitis (CP): 23, intraductal papillary mucinous neoplasm (IPMN): 58). Bisulfite-converted DNA from buffered PJ was analyzed using long-probe quantitative amplified signal assay targeting 14 MDMs (NDRG4, BMP3, TBX15, C13orf18, PRKCB, CLEC11A, CD1D, ELMO1, IGF2BP1, RYR2, ADCY1, FER1L4, EMX1, and LRRC4) and a reference gene (methylated B3GALT6). Logistic regression was used to fit the previously identified 3-MDM PJ panel (FER1L4, C13orf18 and BMP3). Discrimination accuracy was summarized using area under the receiver operating characteristic curve (AUROC) with corresponding 95% confidence intervals. RESULTS: Methylated FER1L4 had the highest individual AUROC of 0.83 (95% CI: 0.78-0.89). The AUROC for the 3-MDM PJ + Plasma CA 19-9 model (0.95 (0.92-0.98))) was higher than both the 3-MDM PJ panel (0.87 (0.82-0.92)) and plasma CA 19-9 alone ((0.91 (0.87-0.96) (p=0.0002 and 0.0135, respectively). At a specificity of 88% (95% CI: 81-93%), the sensitivity of this model was 89% (80-94%) for all PDAC stages and 83% (64-94%) for stage I/II PDAC. CONCLUSION: A panel combining PJ-MDMs and plasma CA19-9 discriminates PDAC from both healthy and disease control groups with high accuracy. This provides support for combining pancreatic juice and blood-based biomarkers for enhancing diagnostic sensitivity and successful early PDAC detection.

Long-Term Outcomes of Endoscopic Ultrasound-Guided Ablation Vs Surgery for Pancreatic Cystic Tumors.

BACKGROUND & AIMS: Endoscopic ultrasound-guided pancreatic cyst ablation (EUS-PCA) is performed as an alternative to surgical resection in selected patients with pancreatic cystic tumors (PCTs). We aimed to directly compare the long-term outcomes between EUS-PCA and surgery for PCTs. METHODS: We reviewed a PCT database to identify patients with unilocular or oligolocular PCTs who underwent EUS-PCA or surgery between January 2004 and July 2019. We performed 1:1 propensity score matching based on potential confounding factors. The primary outcome was long-term morbidities. Secondary outcomes included early (≤14 days) and late (>14 days) major adverse events (MAEs), development of diabetes mellitus, readmission, length of hospital stay, and therapeutic efficacy. RESULTS: A total of 620 patients (EUS-PCA, n = 310; surgery, n = 310) were selected after propensity score matching. The EUS-PCA group showed a lower 10-year rate of cumulative long-term morbidities (1.6% vs 33.5%; P = .001) as well as lower rates of early MAE (1.0% vs 8.7%; P = .001), late MAE (0.3% vs 5.5%; P = .001), and readmission (1.0% vs 15.2%; P = .001). The EUS-PCA group had a shorter hospital stay (3.5 vs 10.3 d; P = .001) and a lower incidence of diabetes mellitus (2.2% vs 22.8%; P = .001), whereas the surgery group had a higher complete resolution rate (76.5% vs 100%; P = .001) and a lower relapse rate (4.6% vs 0.3%; P = .001). CONCLUSIONS: For select patients with PCTs, EUS-PCA showed superior results to surgery in terms of long-term safety profile and preservation of pancreatic function.

Predictors for Long-Term Survival After Resection of Pancreatic Ductal Adenocarcinoma: A Systematic Review and Meta-Analysis.

BACKGROUND: Improved systemic therapy has made long term (≥ 5 years) overall survival (LTS) after resection of pancreatic ductal adenocarcinoma (PDAC) increasingly common. However, a systematic review on predictors of LTS following resection of PDAC is lacking. METHODS: The PubMed, Embase, Scopus, and Cochrane CENTRAL databases were systematically searched from inception until March 2023. Studies reporting actual survival data (based on follow-up and not survival analysis estimates) on factors associated with LTS were included. Meta-analyses were conducted by using a random effects model, and study quality was gauged by using the Newcastle-Ottawa Scale (NOS). RESULTS: Twenty-five studies with 27,091 patients (LTS: 2,132, non-LTS: 24,959) who underwent surgical resection for PDAC were meta-analyzed. The median proportion of LTS patients was 18.32% (IQR 12.97-21.18%) based on 20 studies. Predictors for LTS included sex, body mass index (BMI), preoperative levels of CA19-9, CEA, and albumin, neutrophil-lymphocyte ratio, tumor grade, AJCC stage, lymphovascular and perineural invasion, pathologic T-stage, nodal disease, metastatic disease, margin status, adjuvant therapy, vascular resection, operative time, operative blood loss, and perioperative blood transfusion. Most articles received a "good" NOS assessment, indicating an acceptable risk of bias. CONCLUSIONS: Our meta-analysis pools all true follow up data in the literature to quantify associations between prognostic factors and LTS after resection of PDAC. While there appears to be evidence of a complex interplay between risk, tumor biology, patient characteristics, and management related factors, no single parameter can predict LTS after the resection of PDAC.

Comparing clinical and genomic features based on the tumor location in patients with resected pancreatic cancer.

BACKGROUND: Pancreatic cancer is anatomically divided into pancreatic head and body/tail cancers, and some studies have reported differences in prognosis. However, whether this discrepancy is induced from the difference of tumor biology is hotly debated. Therefore, we aimed to evaluate the differences in clinical outcomes and tumor biology depending on the tumor location. METHODS: In this retrospective cohort study, we identified 800 patients with pancreatic ductal adenocarcinoma who had undergone upfront curative-intent surgery. Cox regression analysis was performed to explore the prognostic impact of the tumor location. Among them, 153 patients with sufficient tumor tissue and blood samples who provided informed consent for next-generation sequencing were selected as the cohort for genomic analysis. RESULTS: Out of the 800 patients, 500 (62.5%) had pancreatic head cancer, and 300 (37.5%) had body/tail cancer. Tumor location in the body/tail of the pancreas was not identified as a significant predictor of survival outcomes compared to that in the head in multivariate analysis (hazard ratio, 0.94; 95% confidence interval, 0.77-1.14; P = 0.511). Additionally, in the genomic analyses of 153 patients, there were no significant differences in mutational landscapes, distribution of subtypes based on transcriptomic profiling, and estimated infiltration levels of various immune cells between pancreatic head and body/tail cancers. CONCLUSIONS: We could not find differences in prognosis and tumor biology depending on tumor location in pancreatic ductal adenocarcinoma. Discrepancies in prognosis may represent a combination of lead time, selection bias, and clinical differences, including the surgical burden between tumor sites.

Efficacy and safety of temozolomide-based regimens in advanced pancreatic neuroendocrine tumors: a systematic review and meta-analysis.

BACKGROUND: Recent advances in the management of pancreatic neuroendocrine tumors (pNETs) highlight the potential benefits of temozolomide, an alkylating agent, for these patients. In this meta-analysis, we aimed to assess the outcome of temozolomide, alone or in combination with other anticancer medications in patients with advanced pNET. METHODS: Online databases of PubMed, Web of Science, Embase, the Cochrane Library, and ClinicalTrials.gov were searched systematically for clinical trials that reported the efficacy and safety of temozolomide in patients with advanced pNET. Random-effect model was utilized to estimate pooled rates of outcomes based on Response Evaluation Criteria in Solid Tumors criteria, biochemical response, and adverse events (AEs). RESULTS: A total of 14 studies, providing details of 441 individuals with advanced pNET, were included. The quantitative analyses showed a pooled objective response rate (ORR) of 41.2% (95% confidence interval, CI, of 32.4%-50.6%), disease control rate (DCR) of 85.3% (95% CI of 74.9%-91.9%), and a more than 50% decrease from baseline chromogranin A levels of 44.9% (95% CI of 31.6%-49.0%). Regarding safety, the results showed that the pooled rates of nonserious AEs and serious AEs were 93.8% (95% CI of 88.3%-96.8%) and 23.7% (95% CI of 12.0%-41.5%), respectively. The main severe AEs encompassed hematological toxicities. CONCLUSIONS: In conclusion, our meta-analysis suggests that treatment with temozolomide, either as a monotherapy or in combination with other anticancer treatments might be an effective and relatively safe option for patients with advanced locally unresectable and metastatic pNET. However, additional clinical trials are required to further strengthen these findings. This study has been registered in PROSPERO (CRD42023409280).

Performance of explainable artificial intelligence in guiding the management of patients with a pancreatic cyst.

BACKGROUND/OBJECTIVES: Pancreatic cyst management can be distilled into three separate pathways - discharge, monitoring or surgery- based on the risk of malignant transformation. This study compares the performance of artificial intelligence (AI) models to clinical care for this task. METHODS: Two explainable boosting machine (EBM) models were developed and evaluated using clinical features only, or clinical features and cyst fluid molecular markers (CFMM) using a publicly available dataset, consisting of 850 cases (median age 64; 65 % female) with independent training (429 cases) and holdout test cohorts (421 cases). There were 137 cysts with no malignant potential, 114 malignant cysts, and 599 IPMNs and MCNs. RESULTS: The EBM and EBM with CFMM models had higher accuracy for identifying patients requiring monitoring (0.88 and 0.82) and surgery (0.66 and 0.82) respectively compared with current clinical care (0.62 and 0.58). For discharge, the EBM with CFMM model had a higher accuracy (0.91) than either the EBM model (0.84) or current clinical care (0.86). In the cohort of patients who underwent surgical resection, use of the EBM-CFMM model would have decreased the number of unnecessary surgeries by 59 % (n = 92), increased correct surgeries by 7.5 % (n = 11), identified patients who require monitoring by 122 % (n = 76), and increased the number of patients correctly classified for discharge by 138 % (n = 18) compared to clinical care. CONCLUSIONS: EBM models had greater sensitivity and specificity for identifying the correct management compared with either clinical management or previous AI models. The model predictions are demonstrated to be interpretable by clinicians.

Efficiency evaluation of dual-energy CT to predict the postoperative early recurrence of pancreatic ductal adenocarcinoma.

OBJECTIVES: To evaluate the efficacy of quantitative parameters from dual-energy CT (DECT) and basic CT features in predicting the postoperative early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC). METHODS: In this study, patients with PDAC who underwent radical resection and DECT from 2018 to 2022 were enrolled and categorised into ER and non-ER groups. The clinical data, basic CT features and DECT parameters of all patients were analyzed. Independent predictors of ER were identified with Logistic regression analyses. Three models (model A: basic CT features; model B: DECT parameters; model C: basic CT features + DECT parameters) were established. Receiver operating characteristic curve analysis was utilized to evaluate predictive performance. RESULTS: A total of 150 patients were enrolled (ER group: n = 63; non-ER group: n = 87). Rim enhancement (odds ratio [OR], 3.32), peripancreatic strands appearance (OR, 2.68), electron density in the pancreatic parenchymal phase (P-Rho; OR, 0.90), arterial enhancement fraction (AEF; OR, 0.05) and pancreatic parenchyma fat fraction in the delayed phase (OR, 1.25) were identified as independent predictors of ER. Model C showed the highest area under the curve of 0.898. In addition, the corresponding ER risk factors were identified separately for resectable and borderline resectable PDAC subgroups. CONCLUSIONS: DECT quantitative parameters allow for the noninvasive prediction of postoperative ER in patients with PDAC, and the combination of DECT parameters and basic CT features shows a high prediction efficiency. Our model can help to identify patients with high-risk factors to guide preoperative decision making.

Contrast-enhanced endoscopic ultrasound likely does not improve diagnostic adequacy during endoscopic ultrasound guided tissue acquisition: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Solid pancreatic masses are sampled through tissue acquisition by endoscopic ultrasound (EUS). Inadequate samples may significantly delay diagnosis, increasing costs and carrying risks to the patients. AIM: assess the diagnostic adequacy of tissue acquisition using contrast-enhanced harmonic endoscopic ultrasound (CEH-EUS) compared to conventional EUS. METHODS: Five databases (PubMed, Embase, CENTRAL, Scopus and Web of Science) were searched in November 2023. Studies comparing diagnostic adequacy, accuracy and safety using CEH-EUS versus conventional EUS for tissue acquisition of solid pancreatic masses were included. Risk of bias was assessed using the Risk of Bias tool for randomized controlled trials (RoB2) and the Risk Of Bias In Non-Randomized Studies - of Interventions (ROBINS-I) tool for non-randomized studies, level of evidence using the GRADE approach, Odds Ratios (RR) with 95 % Confidence Intervals (CI) calculated and pooled using a random-effects model. I2 quantified heterogeneity. RESULTS: The search identified 3858 records; nine studies (1160 patients) were included. OR for achieving an adequate sample was 1.467 (CI: 0.850-2.533), for randomized trials 0.902 (CI: 0.541-1.505), for non-randomized 2.396 (CI: 0.916-6.264), with significant subgroup difference. OR for diagnostic accuracy was 1.326 (CI: 0.890-1977), for randomized trials 0.997 (CI: 0.593-1.977) and for non-randomized studies 1.928 (CI: 1.096-3.393), significant subgroup difference (p = 0.0467). No differences were observed for technical failures or adverse events. Heterogeneity was low, risk of bias "low" to "some concerns" for most outcomes, mostly moderate for non-randomized studies. CONCLUSION: Non-randomized studies indicated differences in favor of contrast-enhanced EUS, randomized studies showed no difference in diagnostic adequacy, accuracy or sensitivity when using CEH-EUS.

Pancreatic juice cytology for diagnosing invasive pancreatic carcinoma/high-grade pancreatic intraepithelial neoplasia without visible tumors on endoscopic ultrasound.

OBJECTIVES: Pancreatic ductal adenocarcinoma (PDAC) with a diameter ≤10 mm and high-grade pancreatic intraepithelial neoplasia (HG-PanIN) require pre-operative diagnosis. Most cases present only indirect imaging findings without visible tumors on endoscopic ultrasound (EUS). Therefore, EUS-guided fine-needle aspiration/biopsy is not applicable. An alternative diagnostic method is pancreatic juice cytology (PJC) via endoscopic naso-pancreatic drainage (ENPD-PJC), which is not the standard practice. This study aimed to investigate ENPD-PJC for diagnosing suspected PDAC/HG-PanIN cases without visible tumors on EUS. METHODS: Data of patients with suspected PDAC/HG-PanIN without visible tumors who underwent PJC were retrospectively evaluated. One PJC sample was collected during endoscopic retrograde pancreatography (ERP-PJC), and 12 samples were collected during ENPD-PJC, 3-hourly for cytological analysis. ERP-PJC, ERP/ENPD-PJC, and ENPD-PJC positivity indicated cytologically positive samples. Patients with positive/negative PJC with follow-up for <4-years were excluded as undiagnosed cases. A non-malignant diagnosis was based on histopathological absence/stable imaging findings for ≥4-years. The primary endpoint was to demonstrate that ERP/ENPD-PJC has a higher diagnostic ability than ERP-PJC. RESULTS: Twenty-two patients with histopathologically diagnosed PDAC/HG-PanIN and 31 with a non-malignant diagnosis were enrolled. ERP-PJC, ERP/ENPD-PJC, and ENPD-PJC showed sensitivities of 36.4 %, 86.4 %, and 77.3 %, specificities of 93.5 %, 87.1 %, and 93.5 %, and accuracies of 69.8 %, 86.7 %, and 86.7 %, respectively. ERP/ENPD-PJC and ENPD-PJC demonstrated superior sensitivity and accuracy compared to ERP-PJC. A greater occurrence of positive outcomes markedly distinguished true positives from false positives. CONCLUSIONS: ERP/ENPD-PJC and ENPD-PJC had higher diagnostic accuracies for PDAC/HG-PanIN without visible tumors on EUS. ENPD-PJC is recommended for the diagnosis of these lesions.

Differentiating small (< 2 cm) pancreatic ductal adenocarcinoma from neuroendocrine tumors with multiparametric MRI-based radiomic features.

OBJECTIVES: To assess MR-based radiomic analysis in preoperatively discriminating small (< 2 cm) pancreatic ductal adenocarcinomas (PDACs) from neuroendocrine tumors (PNETs). METHODS: A total of 197 patients (146 in the training cohort, 51 in the validation cohort) from two centers were retrospectively collected. A total of 7338 radiomics features were extracted from T2-weighted, diffusion-weighted, T1-weighted, arterial phase, portal venous phase and delayed phase imaging. The optimal features were selected by the Mann-Whitney U test, Spearman's rank correlation test and least absolute shrinkage and selection operator method and used to construct the radiomic score (Rad-score). Conventional radiological and clinical features were also assessed. Multivariable logistic regression was used to construct a radiological model, a radiomic model and a fusion model. RESULTS: Nine optimal features were identified and used to build the Rad-score. The radiomic model based on the Rad-score achieved satisfactory results with AUCs of 0.905 and 0.930, sensitivities of 0.780 and 0.800, specificities of 0.906 and 0.952 and accuracies of 0.836 and 0.863 for the training and validation cohorts, respectively. The fusion model, incorporating CA19-9, tumor margins, pancreatic duct dilatation and the Rad-score, exhibited the best performance with AUCs of 0.977 and 0.941, sensitivities of 0.914 and 0.852, specificities of 0.954 and 0.950, and accuracies of 0.932 and 0.894 for the training and validation cohorts, respectively. CONCLUSIONS: The MR-based Rad-score is a novel image biomarker for discriminating small PDACs from PNETs. A fusion model combining radiomic, radiological and clinical features performed very well in differentially diagnosing these two tumors. CLINICAL RELEVANCE STATEMENT: A fusion model combining MR-based radiomic, radiological, and clinical features could help differentiate between small pancreatic ductal adenocarcinomas and pancreatic neuroendocrine tumors. KEY POINTS: Preoperatively differentiating small pancreatic ductal adenocarcinomas (PDACs) and pancreatic neuroendocrine tumors (PNETs) is challenging. Multiparametric MRI-based Rad-score can be used for discriminating small PDACs from PNETs. A fusion model incorporating radiomic, radiological, and clinical features differentiated small PDACs from PNETs well.

Clinical sonochemotherapy of inoperable pancreatic cancer using diagnostic ultrasound and microbubbles: a multicentre, open-label, randomised, controlled trial.

OBJECTIVES: Sonochemotherapy, which uses microbubble (MB)-assisted ultrasound (US) to deliver chemotherapeutic agents, has the potential to enhance tumour chemotherapy. The combination of US and MB has been demonstrated to prolong the survival of patients with pancreatic cancer. This phase 2 clinical trial aimed to determine the clinical efficacy and safety of sonochemotherapy for inoperable pancreatic ductal adenocarcinoma by using US and MB. METHODS: Eighty-two patients with stage III or IV pancreatic cancer were recruited from July 2018 to March 2021 and followed up until September 2022. US treatment was performed with a modified diagnostic US scanner for 30 min after chemotherapeutic infusion. The primary endpoint was overall survival (OS), and the secondary endpoints were Eastern Cooperative Oncology Group (ECOG) status < 2, progression-free survival (PFS), disease control rate (DCR), and adverse events. RESULTS: Seventy-eight patients were randomly allocated (40 to chemotherapy and 38 to sonochemotherapy). The median OS was longer with sonochemotherapy than with chemotherapy (9.10 vs. 6.10 months; p = 0.037). The median PFS with sonochemotherapy was 5.50 months, compared with 3.50 months (p = 0.080) for chemotherapy. The time of ECOG status < 2 was longer with sonochemotherapy (7.20 months) than with chemotherapy (5.00 months; p = 0.029). The DCR was 73.68% for sonochemotherapy compared with 42.50% for the control (p = 0.005). The incidence of overall adverse events was balanced between the two groups. CONCLUSIONS: The use of sonochemotherapy can extend the survival and well-being time of stage III or IV pancreatic cancer patients without any increase in serious adverse events. TRIAL REGISTRATION: ChineseClinicalTrials.gov ChiCTR2100044721 CLINICAL RELEVANCE STATEMENT: This multicentre, randomised, controlled trial has proven that sonochemotherapy, namely, the combination of diagnostic ultrasound, microbubbles, and chemotherapy, could extend the overall survival of patients with end-stage pancreatic ductal adenocarcinoma from 6.10 to 9.10 months without increasing any serious adverse events. KEY POINTS: • This is the first multicentre, randomised, controlled trial of sonochemotherapy for clinical pancreatic cancer treatment using ultrasound and a commercial ultrasound contrast agent. • Sonochemotherapy extended the median overall survival from 6.10 (chemotherapy alone) to 9.10 months. • The disease control rate increased from 42.50% with chemotherapy to 73.68% with sonochemotherapy.

Quantitative MR imaging biomarkers for distinguishing inflammatory pancreatic mass and pancreatic cancer-a systematic review and meta-analysis.

OBJECTIVES: To evaluate the diagnostic performance of quantitative magnetic resonance (MR) imaging biomarkers in distinguishing between inflammatory pancreatic masses (IPM) and pancreatic cancer (PC). METHODS: A literature search was conducted using PubMed, Embase, the Cochrane Library, and Web of Science through August 2023. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to evaluate the risk of bias and applicability of the studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using the DerSimonian-Laird method. Univariate meta-regression analysis was used to identify the potential factors of heterogeneity. RESULTS: Twenty-four studies were included in this meta-analysis. The two main types of IPM, mass-forming pancreatitis (MFP) and autoimmune pancreatitis (AIP), differ in their apparent diffusion coefficient (ADC) values. Compared with PC, the ADC value was higher in MFP but lower in AIP. The pooled sensitivity/specificity of ADC were 0.80/0.85 for distinguishing MFP from PC and 0.82/0.84 for distinguishing AIP from PC. The pooled sensitivity/specificity for the maximal diameter of the upstream main pancreatic duct (dMPD) was 0.86/0.74, with a cutoff of dMPD ≤ 4 mm, and 0.97/0.52, with a cutoff of dMPD ≤ 5 mm. The pooled sensitivity/specificity for perfusion fraction (f) was 0.82/0.68, and 0.82/0.77 for mass stiffness values. CONCLUSIONS: Quantitative MR imaging biomarkers are useful in distinguishing between IPM and PC. ADC values differ between MFP and AIP, and they should be separated for consideration in future studies. CLINICAL RELEVANCE STATEMENT: Quantitative MR parameters could serve as non-invasive imaging biomarkers for differentiating malignant pancreatic neoplasms from inflammatory masses of the pancreas, and hence help to avoid unnecessary surgery. KEY POINTS: • Several quantitative MR imaging biomarkers performed well in differential diagnosis between inflammatory pancreatic mass and pancreatic cancer. • The ADC value could discern pancreatic cancer from mass-forming pancreatitis or autoimmune pancreatitis, if the two inflammatory mass types are not combined. • The diameter of main pancreatic duct had the highest specificity for differentiating autoimmune pancreatitis from pancreatic 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.

Radiomics model versus 2017 revised international consensus guidelines for predicting malignant intraductal papillary mucinous neoplasms.

OBJECTIVES: To evaluate a CT-based radiomics model for identifying malignant pancreatic intraductal papillary mucinous neoplasms (IPMNs) and compare its performance with the 2017 international consensus guidelines (ICGs). MATERIALS AND METHODS: We retrospectively included 194 consecutive patients who underwent surgical resection of pancreatic IPMNs between January 2008 and December 2020. Surgical histopathology was the reference standard for diagnosing malignancy. Using radiomics features from preoperative contrast-enhanced CT, a radiomics model was built with the least absolute shrinkage and selection operator by a five-fold cross-validation. CT and MR images were independently reviewed based on the 2017 ICGs by two abdominal radiologists, and the performances of the 2017 ICGs and radiomics model were compared. The areas under the curve (AUCs) were compared using the DeLong method. RESULTS: A total of 194 patients with pancreatic IPMNs (benign, 83 [43%]; malignant, 111 [57%]) were chronologically divided into training (n = 141; age, 65 ± 8.6 years; 88 males) and validation sets (n = 53; age, 66 ± 9.7 years; 31 males). There was no statistically significant difference in the diagnostic performance of the 2017 ICGs between CT and MRI (AUC, 0.71 vs. 0.71; p = 0.93) with excellent intermodality agreement (k = 0.86). In the validation set, the CT radiomics model had higher AUC (0.85 vs. 0.71; p = 0.038), specificity (84.6% vs. 61.5%; p = 0.041), and positive predictive value (84.0% vs. 66.7%; p = 0.044) than the 2017 ICGs. CONCLUSION: The CT radiomics model exhibited better diagnostic performance than the 2017 ICGs in classifying malignant IPMNs. CLINICAL RELEVANCE STATEMENT: Compared with the radiologists' evaluation based on the 2017 international consensus guidelines, the CT radiomics model exhibited better diagnostic performance in classifying malignant intraductal papillary mucinous neoplasms. KEY POINTS: • There is a paucity of comparisons between the 2017 international consensus guidelines (ICGs) and radiomics models for malignant intraductal papillary mucinous neoplasms (IPMNs). • The CT radiomics model developed in this study exhibited better diagnostic performance than the 2017 ICGs in classifying malignant IPMNs. • The radiomics model may serve as a valuable complementary tool to the 2017 ICGs, potentially allowing a more quantitative assessment of IPMNs.

Imaging classification of pancreatic ductal adenocarcinoma with histological large duct pattern.

OBJECTIVES: To investigate the imaging features of pancreatic ductal adenocarcinoma (PDAC) with histological large duct pattern. METHODS: Our study included 37 patients (mean age, 66.5 years; 22 women) with surgically proven PDAC with histological large duct pattern, whose imaging features were classified into four types: Type I, solid mass; Type II, predominantly cystic mass with intracystic solid components; Type III, predominantly solid mass with intratumoral cysts; and Type IV, solid mass with peritumoral retention cysts or pseudocysts. Two radiologists independently analyzed both CT and MRI images for the morphological type, presence of abrupt main pancreatic duct (MPD) cutoff, adjacent vascular invasion, diffusion restriction, and reached consensus. RESULTS: On CT, 26 patients (70.3%) had Type I tumors, five (13.5%) had Type II, three (8.1%) had Type III, and three (8.1%) had Type IV. Among the 26 patients with Type I tumors on CT, 16 had tumors with multiple intratumoral cysts within the solid mass on MRI and were subsequently classified as Type III. Accordingly, 10 patients (27.0%) were classified as Type I, five (13.5%) as Type II, 19 (51.7%) as Type III, and three (8.1%) as Type IV on MRI. Of the 37 patients, 27 (73.0%) had an abrupt MPD cutoff, 15 (40.5%) had adjacent vascular invasion, and 25 (67.6%) had diffusion restriction on MRI. CONCLUSIONS: Predominantly solid pancreatic masses with small intratumoral cysts visualized on MRI may be a characteristic imaging finding of PDAC with histological large duct pattern, and differentiate it from conventional PDAC or other cystic pancreatic tumors. CLINICAL RELEVANCE STATEMENT: Radiologists should be familiar with the various imaging features of PDAC with histological large duct pattern and should be aware that it may mimic other solid or cystic tumors of the pancreas. KEY POINTS: Imaging features of pancreatic ductal adenocarcinoma with histological large duct pattern can be classified into four types. This pathology more frequently appears as a predominantly solid mass with intratumoral cysts on MRI than on CT. Adding MRI to CT may help identify pancreatic ductal adenocarcinoma with histological large duct pattern.