The radiomorphological appearance of the invasive margin in pancreatic cancer is associated with tumor budding.

PURPOSE: Pancreatic cancer (PDAC) is characterized by infiltrative, spiculated tumor growth into the surrounding non-neoplastic tissue. Clinically, its diagnosis is often established by magnetic resonance imaging (MRI). At the invasive margin, tumor buds can be detected by histology, an established marker associated with poor prognosis in different types of tumors. METHODS: We analyzed PDAC by determining the degree of tumor spiculation on T2-weighted MRI using a 3-tier grading system. The grade of spiculation was correlated with the density of tumor buds quantified in histological sections of the respective surgical specimen according to the guidelines of the International Tumor Budding Consensus Conference (n = 28 patients). RESULTS: 64% of tumors revealed intermediate to high spiculation on MRI. In over 90% of cases, tumor buds were detected. We observed a significant positive rank correlation between the grade of radiological tumor spiculation and the histopathological number of tumor buds (rs = 0.745, p < 0.001). The number of tumor buds was not significantly associated with tumor stage, presence of lymph node metastases, or histopathological grading (p ≥ 0.352). CONCLUSION: Our study identifies a readily available radiological marker for non-invasive estimation of tumor budding, as a correlate for infiltrative tumor growth. This finding could help to identify PDAC patients who might benefit from more extensive peripancreatic soft tissue resection during surgery or stratify patients for personalized therapy concepts.

A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma.

BACKGROUND: This study aimed to evaluate the efficacy of radiomics signatures derived from polyenergetic images (PEIs) and virtual monoenergetic images (VMIs) obtained through dual-layer spectral detector CT (DLCT). Moreover, it sought to develop a clinical-radiomics nomogram based on DLCT for predicting cancer stage (early stage: stage I-II, advanced stage: stage III-IV) in pancreatic ductal adenocarcinoma (PDAC). METHODS: A total of 173 patients histopathologically diagnosed with PDAC and who underwent contrast-enhanced DLCT were enrolled in this study. Among them, 49 were in the early stage, and 124 were in the advanced stage. Patients were randomly categorized into training (n = 122) and test (n = 51) cohorts at a 7:3 ratio. Radiomics features were extracted from PEIs and 40-keV VMIs were reconstructed at both arterial and portal venous phases. Radiomics signatures were constructed based on both PEIs and 40-keV VMIs. A radiomics nomogram was developed by integrating the 40-keV VMI-based radiomics signature with selected clinical predictors. The performance of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves analysis (DCA). RESULTS: The PEI-based radiomics signature demonstrated satisfactory diagnostic efficacy, with the areas under the ROC curves (AUCs) of 0.92 in both the training and test cohorts. The optimal radiomics signature was based on 40-keV VMIs, with AUCs of 0.96 and 0.94 in the training and test cohorts. The nomogram, which integrated a 40-keV VMI-based radiomics signature with two clinical parameters (tumour diameter and normalized iodine density at the portal venous phase), demonstrated promising calibration and discrimination in both the training and test cohorts (0.97 and 0.91, respectively). DCA indicated that the clinical-radiomics nomogram provided the most significant clinical benefit. CONCLUSIONS: The radiomics signature derived from 40-keV VMI and the clinical-radiomics nomogram based on DLCT both exhibited exceptional performance in distinguishing early from advanced stages in PDAC, aiding clinical decision-making for patients with this condition.

[A rare case of intraductal tumor of the pancreas in which an intraductal tubulopapillary neoplasm was mixed with a widely spreading gastric-type intraductal papillary-mucinous neoplasm].

A 70-year-old man receiving treatment for diabetes mellitus presented with a cystic mass in the border area of the pancreatic body and tail on plain computed tomography (CT) due to impaired glucose intolerance. Contrast-enhanced CT showed a faint hyperattenuated nodular mass extending from the dilated main pancreatic duct (MPD) to the branch duct. Endoscopic retrograde cholangiopancreatography revealed a mildly dilated orifice of the papilla of Vater and MPD stenosis with entire upstream and immediate downstream dilatations. The patient underwent distal pancreatectomy due to the suspicion of mixed-type intraductal papillary-mucinous carcinoma. A pathological examination showed an intraductal solid-nodular mass measuring 25mm in length, consisting of two types of neoplasms. One showed tubulopapillary growth with entirely high-grade (HG) atypical cuboidal epithelium, in which immunohistochemical examinations were positive for MUC6 but negative for human gastric mucin (HGM), MUC1, MUC2, and MUC5AC, fitting the concept of intraductal tubulopapillary neoplasm (ITPN). The other showed the same growth of low-grade (LG) atypical columnar cells positive for HGM and MUC5AC and negative for MUC1 and MUC2, which corresponded to gastric-type intraductal papillary-mucinous neoplasm (IPMN) -LG. The tumor had not invaded the duct walls, and no metastatic lymph nodes were observed. The ITPN was adjacent to the IPMN mainly composed of tubular glands mimicking pyloric glands with LG dysplasia that corresponded to the so-called IPMN-pyloric gland variant. Moreover, the proliferation of low-papillary gastric-type IPMN spread around the intraductal tumors. Consequently, the patient was diagnosed with an intraductal tubular neoplasm comprising a noninvasive ITPN and gastric-type IPMN-LG. ITPN is a recently identified intraductal neoplasm of the pancreas proposed by Yamaguchi et al. and is distinguished by intraductal tubulopapillary growth with HG cellular atypia without overt mucin production, in contrast to IPMN. To date, no cases of intraductal nodular tumors comprising ITPN and IPMN have been reported. We report this original case with imaging and pathological observations and discuss potential processes via which ITPN and IPMN may arise adjacent to each other in the same pancreatic duct.

CT findings and clinical effects of high grade pancreatic intraepithelial neoplasia in patients with intraductal papillary mucinous neoplasms.

PURPOSE: To investigate the common CT findings of high-grade (HG) PanIN and clinical effects in the remnant pancreas in patients with intraductal papillary mucinous neoplasm (IPMN) of the pancreas. MATERIALS AND METHODS: Two hundred fifty-one patients with surgically confirmed IPMNs (118 malignant [invasive carcinoma/high-grade dysplasia] and 133 benign [low-grade dysplasia]) were retrospectively enrolled. The grade of PanIN (233 absent/low-grade and 18 high-grade) was recorded, and all patients underwent serial CT follow-up before and after surgery. Two radiologists analyzed CT findings of high-risk stigmata or worrisome features according to 2017 international consensus guidelines. They also analyzed tumor recurrence on serial follow-up CT after surgery. Statistical analyses were performed to identify significant predictors and clinical impact on postoperative outcomes of HG PanIN. RESULTS: PanIN grade showed a significant association with IPMN grade (p = 0.012). Enhancing mural nodules ≥5 mm, abrupt main pancreatic duct (MPD) changes with distal pancreatic atrophy, increased mural nodule size and MPD diameter were common findings in HG PanIN (P<0.05). In multivariate analysis, abrupt MPD change with distal pancreatic atrophy (odds ratio (OR) 6.59, 95% CI: 2.32-18.72, <0.001) and mural nodule size (OR, 1.05; 95% CI, 1.02-1.08, 0.004) were important predictors for HG PanIN. During postoperative follow-up, HG PanIN (OR, 4.98; 95% CI, 1.22-20.33, 0.025) was significantly associated with cancer recurrence in the remnant pancreas. CONCLUSION: CT can be useful for predicting HG PanIN using common features, such as abrupt MPD changes and mural nodules. In HG PanIN, extra caution is needed to monitor postoperative recurrence during follow-up.

Short- and long-term outcomes after distal pancreatectomy with radiologic infiltration of splenic vessels for pancreatic ductal adenocarcinoma.

BACKGROUND: The effect of radiologic splenic vessels involvement (RSVI) on the survival of patients with pancreatic adenocarcinoma (PAC) located in the body and tail of the pancreas is controversial, and its influence on postoperative morbidity after distal pancreatectomy (DP) is unknown. This study aimed to determine the influence of RSVI on postoperative complications, overall survival (OS), and disease-free survival (DFS) in patients undergoing DP for PAC. METHODS: A multicenter retrospective study of DP was conducted at 7 hepatopancreatobiliary units between January 2008 and December 2018. Patients were classified according to the presence of RSVI. A Clavien-Dindo grade of >II was considered to represent a major complication. RESULTS: A total of 95 patients were included in the analysis. Moreover, 47 patients had vascular infiltration: 4 had arterial involvement, 10 had venous involvement, and 33 had both arterial and venous involvements. The rates of major complications were 20.8% in patients without RSVI, 40.0% in those with venous RSVI, 25.0% in those with arterial RSVI, and 30.3% in those with both arterial and venous RSVIs (P = .024). The DFS rates at 3 years were 56% in the group without RSVI, 50% in the group with arterial RSVI, and 16% in the group with both arterial and venous RSVIs (P = .003). The OS rates at 3 years were 66% in the group without RSVI, 50% in the group with arterial RSVI, and 29% in the group with both arterial and venous RSVIs (P < .0001). CONCLUSION: RSVI increased the major complication rates after DP and reduced the OS and DFS. Therefore, it may be a useful prognostic marker in patients with PAC scheduled to undergo DP and may help to select patients likely to benefit from neoadjuvant treatment.

NIR Fluorescent/Photoacoustic Bimodal Imaging of Ferroptosis in Pancreatic Cancer Using Biothiols-Activable Probes.

Ferroptosis modulation is a powerful therapeutic option for pancreatic ductal adenocarcinoma (PDAC) with a low 5-year survival rate and lack of effective treatment methods. However, due to the dual role of ferroptosis in promoting and inhibiting pancreatic tumorigenesis, regulating the degree of ferroptosis is very important to obtain the best therapeutic effect of PDAC. Biothiols are suitable as biomarkers of imaging ferroptosis due to the dramatic decreases of biothiol levels in ferroptosis caused by the inhibited synthesis pathway of glutathione (GSH) and the depletion of biothiol by reactive oxygen species. Moreover, a very recent study reported that cysteine (Cys) depletion can lead to pancreatic tumor ferroptosis in mice and may be employed as an effective therapeutic strategy for PDAC. Therefore, visualization of biothiols in ferroptosis of PDAC will be helpful for regulating the degree of ferroptosis, understanding the mechanism of Cys depletion-induced pancreatic tumor ferroptosis, and further promoting the study and treatment of PDAC. Herein, two biothiol-activable near-infrared (NIR) fluorescent/photoacoustic bimodal imaging probes (HYD-BX and HYD-DX) for imaging of pancreatic tumor ferroptosis were reported. These two probes show excellent bimodal response performances for biothiols in solution, cells, and tumors. Subsequently, they have been employed successfully for real-time visualization of changes in concentration levels of biothiols during the ferroptosis process in PDAC cells and HepG2 cells. Most importantly, they have been further applied for bimodal imaging of ferroptosis in pancreatic cancer in mice, with satisfactory results. The development of these two probes provides new tools for monitoring changes in concentration levels of biothiols in ferroptosis and will have a positive impact on understanding the mechanism of Cys depletion-induced pancreatic tumor ferroptosis and further promoting the study and treatment of PDAC.

The diagnostic value of abbreviated MRI protocol in the surveillance of Branch-Duct intraductal papillary mucinous neoplasm.

PURPOSE: To assess the diagnostic value of abbreviated protocol (AP) MRI to detect the degeneration signs in branch-duct intraductal papillary mucinous neoplasms (BD-IPMNs) in patients undergoing a routine MRI follow-up. METHODS: This dual-center retrospective study include patients with BD-IPMN diagnosed on initial comprehensive protocol (CP) MRI who underwent routine MRI follow-up. CP included axial and coronal T2-weighted images (T2WI), axial T1-weighted images (T1WI) before and after contrast administration, 3D MR cholangiopancreatography (MRCP) and diffusion-weighted images (DWI). Two APs, eliminating dynamic sequences ± DWI, were extracted from CP. Two radiologists evaluated the APs separately for IPMN degeneration signs according to Fukuoka criteria and compared the results to the follow-up CP. In patients who underwent EUS, imaging findings were correlated with pathological results. Per-patient and per-lesion sensitivity, specificity, PPV, NPV, and accuracy of APs were calculated. Additionally, the acquisition time for different protocols was calculated. RESULTS: One hundred-fourteen patients (56.1 % women, median age: 71 years) with 256 lesions were included. Degeneration signs were observed in 24.6 % and 12.1 % per-patient and per-lesion, respectively. Regarding APs, the per patient sensitivity, specificity, PPV, NPV, and accuracy in the detection of the degeneration signs were 100 %, 93.5 %, 83.3 %, 100 %, and 95.1 %, respectively. No additional role for DWI was detected. AP without DWI economized nearly half of CP acquisition time (388 versus 663 s, respectively). CONCLUSION: AP can confidently replace CP for BD-IPMN follow-up with high sensitivity and PPV while offering benefits such as patient comfort, improved MRI accessibility, and reduced dedicated time for image analysis. DWI necessitates special consideration. CLINICAL RELEVANCE STATEMENT: Our data suggest that APs safely detect all degeneration signs of IPMN. While there is an overestimation of mural nodules due to the lack of contrast injection, this occurs in a negligible number of patients.

Effect of X-ray tube on image quality and pancreatic ductal adenocarcinoma conspicuity in pancreatic protocol dual-energy CT.

AIM: To compare the radiation dose, image quality, and conspicuity of pancreatic ductal adenocarcinoma (PDAC) in pancreatic protocol dual-energy computed tomography (CT) between two X-ray tubes mounted in the same CT machine. MATERIAL AND METHODS: This retrospective study comprised 80 patients (median age, 73 years; 45 men) who underwent pancreatic protocol dual-energy CT from January 2019 to March 2022 using either old (Group A, n=41) or new (Group B, n=39) X-ray tubes mounted in the same CT machine. The imaging parameters were completely matched between the two groups, and CT data were reconstructed at 70 and 40 keV. The CT dose-index volume (CTDIvol); CT attenuation of the abdominal aorta, pancreas, and PDAC; background noise; and qualitative scores for the image noise, overall image quality, and PDAC conspicuity were compared between the two groups. RESULTS: The CTDIvol was lower in Group B than Group A (7.9 versus 9.2 mGy; p<0.001). The CT attenuation of all anatomical structures at 70 and 40 keV was comparable between the two groups (p=0.06-0.78). The background noise was lower in Group B than Group A (12 versus 14 HU at 70 keV, p=0.046; and 26 versus 30 HU at 40 keV, p<0.001). Qualitative scores for image noise and overall image quality at 70 and 40 keV and PDAC conspicuity at 40 keV were higher in Group B than Group A (p<0.001-0.045). CONCLUSION: The latest X-ray tube could reduce the radiation dose and improve image quality in pancreatic protocol dual-energy CT.

Development and validation of a deep learning radiomics model with clinical-radiological characteristics for the identification of occult peritoneal metastases in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: Occult peritoneal metastases (OPM) in patients with pancreatic ductal adenocarcinoma (PDAC) are frequently overlooked during imaging. The authors aimed to develop and validate a computed tomography (CT)-based deep learning-based radiomics (DLR) model to identify OPM in PDAC before treatment. METHODS: This retrospective, bicentric study included 302 patients with PDAC (training: n =167, OPM-positive, n =22; internal test: n =72, OPM-positive, n =9: external test, n =63, OPM-positive, n =9) who had undergone baseline CT examinations between January 2012 and October 2022. Handcrafted radiomics (HCR) and DLR features of the tumor and HCR features of peritoneum were extracted from CT images. Mutual information and least absolute shrinkage and selection operator algorithms were used for feature selection. A combined model, which incorporated the selected clinical-radiological, HCR, and DLR features, was developed using a logistic regression classifier using data from the training cohort and validated in the test cohorts. RESULTS: Three clinical-radiological characteristics (carcinoembryonic antigen 19-9 and CT-based T and N stages), nine HCR features of the tumor, 14 DLR features of the tumor, and three HCR features of the peritoneum were retained after feature selection. The combined model yielded satisfactory predictive performance, with an area under the curve (AUC) of 0.853 (95% CI: 0.790-0.903), 0.845 (95% CI: 0.740-0.919), and 0.852 (95% CI: 0.740-0.929) in the training, internal test, and external test cohorts, respectively (all P <0.05). The combined model showed better discrimination than the clinical-radiological model in the training (AUC=0.853 vs. 0.612, P <0.001) and the total test (AUC=0.842 vs. 0.638, P <0.05) cohorts. The decision curves revealed that the combined model had greater clinical applicability than the clinical-radiological model. CONCLUSIONS: The model combining CT-based DLR and clinical-radiological features showed satisfactory performance for predicting OPM in patients with PDAC.

JS-K Combined with a Melanin-Based Theranostic Agent: A Novel Sequential Delivery Strategy to Enhance the Near-Infrared Fluorescence Imaging of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a 5 year survival rate less than 12%. This malignancy is closely related to the unique tumor microenvironment (TME), which is characterized by a hypovascular and hyperdense extracellular matrix, making it difficult for drugs to permeate the tumor center. Near-infrared fluorescence (NIRF) imaging, which has high sensitivity and resolution, may improve the survival rate of PDAC patients. In this study, we first used JS-K (O2-(2,4-dinitrophenyl) 1-[(4-ethoxycarbonyl) piperazine-1-yl] diazene-1-ium-1,2-diolate) to specifically dilate blood vessels within the TME of PDAC patients and subsequently injected IR820-PEG-MNPs (IPM NPs) to diagnose and treat orthotopic PDAC. We found that JS-K promoted the accumulation of IPM NPs in orthotopic Pan02 tumor-bearing mice and was able to increase the tumor signal-to-background ratio (SBR) in the orthotopic PDAC area by 41.5%. In addition, surgical navigation in orthotopic Pan02 tumor-bearing mice and complete tumor resection based on fluorescence imaging were achieved with a detection sensitivity of 81.0%. Moreover, we verified the feasibility of the combination of laparoscopy and photothermal ablation (PTA) for the treatment of PDAC. Finally, we demonstrated that IPM NPs had greater affinity for human PDAC tissues than for normal pancreatic tissues ex vivo, preliminarily highlighting the potential for clinical translation of these NPs. In conclusion, we developed and validated a novel sequential delivery strategy that promotes the accumulation of nanoagents in the tumor area and can be used for the diagnosis and treatment of PDAC.

KRAS Mutation Detection with (2S,4R)-4-[18F]FGln for Noninvasive PDAC Diagnosis.

Pancreatic ductal adenocarcinoma (PDAC), which has a poor prognosis and nonspecific symptoms and progresses rapidly, is the most common pancreatic cancer type. Inhibitors targeting KRAS G12D and G12C mutations have been pivotal in PDAC treatment. Cancer cells with different KRAS mutations exhibit various degrees of glutamine dependency; in particular, cells with KRAS G12D mutations exhibit increased glutamine uptake. (2S,4R)-4-[18F]FGln has recently been developed for clinical cancer diagnosis and tumor cell metabolism analysis. Thus, we verified the heterogeneity of glutamine dependency in PDAC models with different KRAS mutations by a visual and noninvasive method with (2S,4R)-4-[18F]FGln. Two tumor-bearing mouse models (bearing the KRAS G12D or G12C mutation) were injected with (2S,4R)-4-[18F]FGln, and positron emission tomography (PET) imaging features and biodistribution were observed and analyzed. The SUVmax in the regions of interest (ROI) was significantly higher in PANC-1 (G12D) tumors than in MIA PaCa-2 (G12C) tumors. Biodistribution analysis revealed higher tumor accumulation of (2S,4R)-4-[18F]FGln and other metrics, such as T/M and T/B, in the PANC-1 mouse models compared to those in the MIAPaCa-2 mouse models. In conclusion, PDAC cells with the KRAS G12D and G12C mutations exhibit various degrees of (2S,4R)-4-[18F]FGln uptake, indicating that (2S,4R)-4-[18F]FGln might be applied to detect KRAS G12C and G12D mutations and provide treatment guidance.

Dual-energy computed tomography in a multiparametric regression model for diagnosing lymph node metastases in pancreatic ductal adenocarcinoma.

OBJECTIVE: To investigate the diagnostic value of dual-energy computed tomography (DECT) quantitative parameters in the identification of regional lymph node metastasis in pancreatic ductal adenocarcinoma (PDAC). METHODS: This retrospective diagnostic study assessed 145 patients with pathologically confirmed pancreatic ductal adenocarcinoma from August 2016-October 2020. Quantitative parameters for targeted lymph nodes were measured using DECT, and all parameters were compared between benign and metastatic lymph nodes to determine their diagnostic value. A logistic regression model was constructed; the receiver operator characteristics curve was plotted; the area under the curve (AUC) was calculated to evaluate the diagnostic efficacy of each energy DECT parameter; and the DeLong test was used to compare AUC differences. Model evaluation was used for correlation analysis of each DECT parameter. RESULTS: Statistical differences in benign and metastatic lymph nodes were found for several parameters. Venous phase iodine density had the highest diagnostic efficacy as a single parameter, with AUC 0.949 [95% confidence interval (CI):0.915-0.972, threshold: 3.95], sensitivity 79.80%, specificity 96.00%, and accuracy 87.44%. Regression models with multiple parameters had the highest diagnostic efficacy, with AUC 0.992 (95% CI: 0.967-0.999), sensitivity 95.96%, specificity 96%, and accuracy 94.97%, which was higher than that for a single DECT parameter, and the difference was statistically significant. CONCLUSION: Among all DECT parameters for regional lymph node metastasis in PDAC, venous phase iodine density has the highest diagnostic efficacy as a single parameter, which is convenient for use in clinical settings, whereas a multiparametric regression model has higher diagnostic value compared with the single-parameter model.

Dual-layer spectral detector CT: A noninvasive preoperative tool for predicting histopathological differentiation in pancreatic ductal adenocarcinoma.

PURPOSE: To predict histopathological differentiation grades in patients with pancreatic ductal adenocarcinoma (PDAC) before surgery with quantitative and qualitative variables obtained from dual-layer spectral detector CT (DLCT). METHODS: Totally 128 patients with histopathologically confirmed PDAC and preoperative DLCT were retrospectively enrolled and categorized into the low-grade (LG) (well and moderately differentiated, n = 82) and high-grade (HG) (poorly differentiated, n = 46) subgroups. Both conventional and spectral variables for PDAC were measured. The ratio of iodine concentration (IC) values in arterial phase(AP) and venous phase (VP) was defined as iodine enhancement fraction_AP/VP (IEF_AP/VP). Necrosis was visually assessed on both conventional CT images (necrosis_con) and virtual mono-energetic images (VMIs) at 40 keV (necrosis_40keV). Forward stepwise logistic regression method was conducted to perform univariable and multivariable analysis. Receiver operating characteristic (ROC) curves and the DeLong method were used to evaluate and compare the efficiencies of variables in predicting tumor grade. RESULTS: Necrosis_con (odds ratio [OR] = 2.84, 95% confidence interval [CI]: 1.13-7.13; p < 0.001) was an independent predictor among conventional variables, and necrosis_40keV (OR = 5.82, 95% CI: 1.98-17.11; p = 0.001) and IEF_AP/VP (OR = 1.12, 95% CI:1.07-1.17; p < 0.001) were independent predictors among spectral variables for distinguishing LG PDAC from HG PDAC. IEF_AP/VP (AUC = 0.754, p = 0.016) and combination model (AUC = 0.812, p < 0.001) had better predictive performances than necrosis_con (AUC = 0.580). The combination model yielded the highest sensitivity (72%) and accuracy (79%), while IEF_AP/VP exhibited the highest specificity (89%). CONCLUSION: Variables derived from DLCT have the potential to preoperatively evaluate PDAC tumor grade. Furthermore, spectral variables and their combination exhibited superior predictive performances than conventional CT variables.

Does CT overestimate extra-pancreatic perineural invasion in patients with pancreatic ductal adenocarcinoma following neoadjuvant chemoradiation therapy?

OBJECTIVES: To evaluate the diagnostic performance of CT in the assessment of extra-pancreatic perineural invasion (EPNI) in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: This retrospective study included 123 patients (66 men; median age, 66 years) with PDAC who underwent radical surgery and pancreatic protocol CT for assessing surgical resectability between September 2011 and March 2019. Among the 123 patients, 97 patients had received neoadjuvant chemoradiation therapy (CRT). Two radiologists reviewed the CT images for evidence of EPNI using a 5-point scale (5 = definitely present, 4 = probably present, 3 = equivocally present, 2 = probably absent, and 1 = definitely absent). Diagnostic performance for assessing EPNI was evaluated with receiver operating characteristic (ROC) curve analysis. RESULTS: The sensitivity, specificity, and area under the ROC curve for assessing EPNI were 98%, 30%, and 0.62 in all patients; 97%, 22%, and 0.59 in patients with neoadjuvant CRT; and 100%, 100%, and 1.00 in patients without neoadjuvant CRT, respectively. False-positive assessment of EPNI occurred in 23% of patients (n = 28/123), and 100% of these (n = 28/28) had received neoadjuvant CRT. There was moderate to substantial agreement between the readers (ĸ = 0.49-0.62). CONCLUSION: Pancreatic protocol CT has better diagnostic performance for determination of EPNI in treatment naïve patients with PDAC and overestimation of EPNI is likely in patients who have received preoperative CRT. ADVANCES IN KNOWLEDGE: Pancreatic protocol CT has better diagnostic performance for the detection of EPNI in treatment naïve patients compared to patients receiving neoadjuvant CRT.

Multiplexed Imaging Mass Cytometry Analysis in Preclinical Models of Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers. PDAC is characterized by a complex tumor microenvironment (TME), that plays a pivotal role in disease progression and resistance to therapy. Investigating the spatial distribution and interaction of TME cells with the tumor is the basis for understanding the mechanisms underlying disease progression and represents a current challenge in PDAC research. Imaging mass cytometry (IMC) is the major multiplex imaging technology for the spatial analysis of tumor heterogeneity. However, there is a dearth of reports of multiplexed IMC panels for different preclinical mouse models, including pancreatic cancer. We addressed this gap by utilizing two preclinical models of PDAC: the genetically engineered, bearing KRAS-TP53 mutations in pancreatic cells, and the orthotopic, and developed a 28-marker panel for single-cell IMC analysis to assess the abundance, distribution and phenotypes of cells involved in PDAC progression and their reciprocal functional interactions. Herein, we provide an unprecedented definition of the distribution of TME cells in PDAC and compare the diversity between transplanted and genetic disease models. The results obtained represent an important and customizable tool for unraveling the complexities of PDAC and deciphering the mechanisms behind therapy resistance.

Artificial intelligence for assessment of vascular involvement and tumor resectability on CT in patients with pancreatic cancer.

OBJECTIVE: This study aimed to develop and evaluate an automatic model using artificial intelligence (AI) for quantifying vascular involvement and classifying tumor resectability stage in patients with pancreatic ductal adenocarcinoma (PDAC), primarily to support radiologists in referral centers. Resectability of PDAC is determined by the degree of vascular involvement on computed tomography scans (CTs), which is associated with considerable inter-observer variability. METHODS: We developed a semisupervised machine learning segmentation model to segment the PDAC and surrounding vasculature using 613 CTs of 467 patients with pancreatic tumors and 50 control patients. After segmenting the relevant structures, our model quantifies vascular involvement by measuring the degree of the vessel wall that is in contact with the tumor using AI-segmented CTs. Based on these measurements, the model classifies the resectability stage using the Dutch Pancreatic Cancer Group criteria as either resectable, borderline resectable, or locally advanced (LA). RESULTS: We evaluated the performance of the model using a test set containing 60 CTs from 60 patients, consisting of 20 resectable, 20 borderline resectable, and 20 locally advanced cases, by comparing the automated analysis obtained from the model to expert visual vascular involvement assessments. The model concurred with the radiologists on 227/300 (76%) vessels for determining vascular involvement. The model's resectability classification agreed with the radiologists on 17/20 (85%) resectable, 16/20 (80%) for borderline resectable, and 15/20 (75%) for locally advanced cases. CONCLUSIONS: This study demonstrates that an AI model may allow automatic quantification of vascular involvement and classification of resectability for PDAC. RELEVANCE STATEMENT: This AI model enables automated vascular involvement quantification and resectability classification for pancreatic cancer, aiding radiologists in treatment decisions, and potentially improving patient outcomes. KEY POINTS: • High inter-observer variability exists in determining vascular involvement and resectability for PDAC. • Artificial intelligence accurately quantifies vascular involvement and classifies resectability for PDAC. • Artificial intelligence can aid radiologists by automating vascular involvement and resectability assessments.

Artificial intelligence to predict T4 stage of pancreatic ductal adenocarcinoma using CT imaging.

BACKGROUND: The accurate assessment of T4 stage of pancreatic ductal adenocarcinoma (PDAC) has consistently presented a considerable difficulty for radiologists. This study aimed to develop and validate an automated artificial intelligence (AI) pipeline for the prediction of T4 stage of PDAC using contrast-enhanced CT imaging. METHODS: The data were obtained retrospectively from consecutive patients with surgically resected and pathologically proved PDAC at two institutions between July 2017 and June 2022. Initially, a deep learning (DL) model was developed to segment PDAC. Subsequently, radiomics features were extracted from the automatically segmented region of interest (ROI), which encompassed both the tumor region and a 3 mm surrounding area, to construct a predictive model for determining T4 stage of PDAC. The assessment of the models' performance involved the calculation of the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. RESULTS: The study encompassed a cohort of 509 PDAC patients, with a median age of 62 years (interquartile range: 55-67). The proportion of patients in T4 stage within the model was 16.9%. The model achieved an AUC of 0.849 (95% CI: 0.753-0.940), a sensitivity of 0.875, and a specificity of 0.728 in predicting T4 stage of PDAC. The performance of the model was determined to be comparable to that of two experienced abdominal radiologists (AUCs: 0.849 vs. 0.834 and 0.857). CONCLUSION: The automated AI pipeline utilizing tumor and peritumor-related radiomics features demonstrated comparable performance to that of senior abdominal radiologists in predicting T4 stage of PDAC.

Validation of dual energy X-ray absorptiometry for longitudinal quantification of tumor burden in a murine model of pancreatic ductal adenocarcinoma.

Noninvasive imaging is central to preclinical, in vivo models of pancreatic ductal adenocarcinoma (PDAC). While bioluminescent imaging (BLI) is a gold standard, its signal is dependent on the metabolic activity of tumor cells. In contrast, dual energy X-ray absorptiometry (DEXA) is a direct measure of body composition. Thus, we aimed to assess its potential for longitudinal quantification of tumor burden versus BLI. We utilized the KCKO murine model of PDAC and subjected tumor-bearing (n = 20) and non-tumor control (NTC) (n = 10) animals to weekly BLI and DEXA measurements for up to 10 weeks. While BLI detected tumors at 1-week, it failed to detect tumor growth, displayed a decreasing trend overtime (slope = -9.0x108; p = 0.0028), and terminal signal did not correlate with ex vivo tumor mass (r = 0.01853; p = 0.6286). In contrast, DEXA did not detect elevated changes in abdominal cavity lean mass until week 2 post inoculation and tumors were not visible until week 3, but successfully quantified a tumor growth trend (slope = 0.7322; p<0.0001), and strongly correlated with final tumor mass (r = 0.9351; p<0.0001). These findings support the use of BLI for initial tumor engraftment and persistence but demonstrate the superiority of DEXA for longitudinal tumor burden studies. As tumor detection by DEXA is not restricted to luciferase expressing models, future studies to assess its value in various cancer models and as an in vivo outcome measure of treatment efficacy are warranted.

Immunohistochemical FAP Expression Reflects 68Ga-FAPI PET Imaging Properties of Low- and High-Grade Intraductal Papillary Mucinous Neoplasms and Pancreatic Ductal Adenocarcinoma.

Pancreatic intraductal papillary mucinous neoplasms (IPMNs) are grossly visible (typically > 5 mm) intraductal epithelial neoplasms of mucin-producing cells, arising in the main pancreatic duct or its branches. According to the current 2-tiered grading scheme, these lesions are categorized as having either low-grade (LG) dysplasia, which has a benign prognosis, or high-grade (HG) dysplasia, which formally represents a carcinoma in situ and thus can transform to pancreatic ductal adenocarcinoma (PDAC). Because both entities require different treatments according to their risk of becoming malignant, a precise pretherapeutic diagnostic differentiation is inevitable for adequate patient management. Recently, our group has demonstrated that 68Ga-fibroblast activation protein (FAP) inhibitor (FAPI) PET/CT shows great potential for the differentiation of LG IPMNs, HG IPMNs, and PDAC according to marked differences in signal intensity and tracer dynamics. The purpose of this study was to biologically validate FAP as a target for PET imaging by analyzing immunohistochemical FAP expression in LG IPMNs, HG IPMNs, and PDAC and comparing with SUV and time to peak (TTP) measured in our prior study. Methods: To evaluate the correlation of the expression level of FAP and α-smooth muscle actin (αSMA) in neoplasm-associated stroma depending on the degree of dysplasia in IPMNs, 98 patients with a diagnosis of LG IPMN, HG IPMN, PDAC with associated HG IPMN, or PDAC who underwent pancreatic surgery at the University Hospital Heidelberg between 2017 and 2023 were identified using the database of the Institute of Pathology, University Hospital Heidelberg. In a reevaluation of hematoxylin- and eosin-stained tissue sections of formalin-fixed and paraffin-embedded resection material from the archive, which was originally generated for histopathologic routine diagnostics, a regrading of IPMNs was performed by a pathologist according to the current 2-tiered grading scheme, consequently eliminating the former diagnosis of "IPMN with intermediate-grade dysplasia." For each case, semithin tissue sections of 3 paraffin blocks containing neoplasm were immunohistologically stained with antibodies directed against FAP and αSMA. In a masked approach, a semiquantitative analysis of the immunohistochemically stained slides was finally performed by a pathologist by adapting the immunoreactive score (IRS) and human epidermal growth factor receptor 2 (Her2)/neu score to determine the intensity and percentage of FAP- and αSMA-positive cells. Afterward, the IRS of 14 patients who underwent 68Ga-FAPI-74 PET/CT in our previous study was compared with their SUVmax, SUVmean, and TTP for result validation. Results: From 98 patients, 294 specimens (3 replicates per patient) were immunohistochemically stained for FAP and αSMA. Twenty-three patients had LG IPMNs, 11 had HG IPMNs, 10 had HG IPMNs plus PDAC, and 54 had PDAC. The tumor stroma was in all cases variably positive for FAP. The staining intensity, percentage of FAP-positive stroma, IRS, and Her2/neu score increased with higher malignancy. αSMA expression could be shown in normal pancreatic stroma as well as within peri- and intraneoplastic desmoplastic reaction. No homogeneous increase in intensity, percentage, IRS, and Her2/neu score with higher malignancy was observed for αSMA. The comparison of the mean IRS of FAP with the mean SUVmax, SUVmean, and TTP of 68Ga-GAPI-74 PET/CT showed a matching value increasing with higher malignancy in 68Ga-FAPI-74 PET imaging and immunohistochemical FAP expression. Conclusion: The immunohistochemical staining of IPMNs and PDAC validates FAP as a biology-based stromal target for in vivo imaging. Increasing expression of FAP in lesions with a higher degree of malignancy matches the expectation of a stronger FAP expression in PDAC and HG IPMNs than in LG IPMNs and corroborates our previous findings of higher SUVs and a longer TTP in PDAC and HG IPMNs than in LG IPMNs.