White paper on pancreatic ductal adenocarcinoma from society of abdominal radiology's disease-focused panel for pancreatic ductal adenocarcinoma: Part II, update on imaging techniques and screening of pancreatic cancer in high-risk individuals

Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma

BACKGROUND

One of the primary reasons for the dismal survival rates in pancreatic ductal adenocarcinoma (PDAC) is that most patients are usually diagnosed at late stages. There is an urgent unmet clinical need to identify and develop diagnostic methods that could precisely detect PDAC at its earliest stages.

AIM

To evaluate the potential value of radiomics analysis in the differentiation of early-stage PDAC from late-stage PDAC.

METHODS

A total of 71 patients with pathologically proved PDAC based on surgical resection who underwent contrast-enhanced computed tomography (CT) within 30 d prior to surgery were included in the study. Tumor staging was performed in accordance with the 8th edition of the American Joint Committee on Cancer staging system. Radiomics features were extracted from the region of interest (ROI) for each patient using Analysis Kit software. The most important and predictive radiomics features were selected using Mann-Whitney U test, univariate logistic regression analysis, and minimum redundancy maximum relevance (MRMR) method. Random forest (RF) method was used to construct the radiomics model, and 10-times leave group out cross-validation (LGOCV) method was used to validate the robustness and reproducibility of the model.

RESULTS

A total of 792 radiomics features (396 from late arterial phase and 396 from portal venous phase) were extracted from the ROI for each patient using Analysis Kit software. Nine most important and predictive features were selected using Mann-Whitney U test, univariate logistic regression analysis, and MRMR method. RF method was used to construct the radiomics model with the nine most predictive radiomics features, which showed a high discriminative ability with 97.7% accuracy, 97.6% sensitivity, 97.8% specificity, 98.4% positive predictive value, and 96.8% negative predictive value. The radiomics model was proved to be robust and reproducible using 10-times LGOCV method with an average area under the curve of 0.75 by the average performance of the 10 newly built models.

CONCLUSION

The radiomics model based on CT could serve as a promising non-invasive method in differential diagnosis between early and late stage PDAC.

Advancements in Pancreatic Cancer Detection: Integrating Biomarkers, Imaging Technologies, and Machine Learning for Early Diagnosis

Artificial intelligence (AI) has come to play a pivotal role in revolutionizing medical practices, particularly in the field of pancreatic cancer detection and management. As a leading cause of cancer-related deaths, pancreatic cancer warrants innovative approaches due to its typically advanced stage at diagnosis and dismal survival rates. Present detection methods, constrained by limitations in accuracy and efficiency, underscore the necessity for novel solutions. AI-driven methodologies present promising avenues for enhancing early detection and prognosis forecasting. Through the analysis of imaging data, biomarker profiles, and clinical information, AI algorithms excel in discerning subtle abnormalities indicative of pancreatic cancer with remarkable precision. Moreover, machine learning (ML) algorithms facilitate the amalgamation of diverse data sources to optimize patient care. However, despite its huge potential, the implementation of AI in pancreatic cancer detection faces various challenges. Issues such as the scarcity of comprehensive datasets, biases in algorithm development, and concerns regarding data privacy and security necessitate thorough scrutiny. While AI offers immense promise in transforming pancreatic cancer detection and management, ongoing research and collaborative efforts are indispensable in overcoming technical hurdles and ethical dilemmas. This review delves into the evolution of AI, its application in pancreatic cancer detection, and the challenges and ethical considerations inherent in its integration.

PET/MRI for evaluation of patients with pancreatic cancer

Pancreatic cancers are the third leading cause of cancer-related death in the USA and outcomes remain poor despite improvements in imaging and treatment paradigms. Currently, computed tomography (CT) and magnetic resonance imaging (MRI) are frequently utilized for staging and restaging of these malignancies, but positron emission tomography (PET)/CT can play a role in troubleshooting and improve whole-body staging. PET/MRI is a novel imaging modality that allows for simultaneous acquisition of PET and MRI images, leading to improved image quality and potential increased sensitivity. Early studies suggest that PET/MRI may play a larger role in pancreatic cancer imaging in future. This manuscript will briefly discuss current imaging approaches to pancreatic cancer and outline existing evidence and published data supporting the use of PET/MRI for pancreatic cancers.

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.

Evaluation of the performance of and interobserver agreement on postoperative baseline CT findings in the identification of locoregional recurrence in patients with pancreatic ductal adenocarcinoma

PURPOSE

To evaluate interobserver agreement on the findings of baseline contrast-enhanced multidetector computed tomography (CE-MDCT) performed at the postoperative third month in patients who underwent surgery due to ductal adenocarcinoma of the pancreatic head and investigate the value of these findings in predicting locoregional recurrence.

MATERIAL AND METHODS

The baseline CE-MDCT images of 198 patients who underwent the Whipple procedure due to pancreatic head tumors were evaluated independently by three radiologists at the postoperative third month. The radiologists were asked to note suspicious findings in terms of locoregional recurrence, including postoperative fat stranding, the presence of perivascular contrast-enhanced solid tissue, short diameter of solid tissue if present, the shape of solid tissue (convex/concave), presence of peritoneal implants, diameter (mm) of pancreatic duct dilatation if present, the presence of lymph nodes larger than 5 mm, portal vein stenosis (≥50 and <50%), the presence of ascites, and the presence of distant metastases, as specified by the Society of Abdominal Radiology in October 2022. The agreement between the radiologists and the value of these parameters in predicting locoregional recurrence were investigated.

RESULTS

Among the CE-MDCT findings evaluated, the radiologists had a moderate-to-high level of agreement concerning the presence of perivascular contrast-enhanced solid tissue. However, there was a poor interobserver agreement on the shape of solid tissue. A very high level of agreement was found among the radiologists in the evaluation of pancreatic duct dilatation, peritoneal implants, ascites, and the presence of distant metastases. According to the univariate analysis, the rates of portal vein stenosis had a 1.419 -fold effect [odds ratio (OR)=1.419, [95% confidence interval (CI)= 0.548-3.679, p=0.041], lymph node presence had a 2.337 -fold effect [odds ratio (OR)=2.337, [95% confidence interval (CI)= 1.165-4.686, p=0.015], perivascular contrast-enhanced solid tissue had 2.241 -fold effect [odds ratio (OR)=2.241, [95% confidence interval (CI)= 1.072-4.684, p=0.005]. In the multivariate analysis, perivascular contrast-enhanced solid tissue had 2.241 -fold effect [odds ratio (OR)=2.519, [95% confidence interval (CI)= 1.132-5.605, p=0.024].

CONCLUSION

In the postoperative baseline CE-MDCT examination, the presence of solid tissue, lymph node presence, and portal vein stenosis in the surgical bed are among the findings that may indicate early locoregional recurrence in patients with pancreatic ductal adenocarcinoma.

A pancreatic adenocarcinoma mimicking hepatoid carcinoma of uncertain histogenesis: A case report and literature review

In rare cases, metastatic adenocarcinomas of different origin may exhibit the features of hepatoid carcinoma (HC), a rare malignant epithelial tumor, most commonly occurring in the ovaries and stomach, as well as in the pancreas and biliary ducts. A case of a 72-year-old female patient who developed a highly aggressive, poorly differentiated pancreatic ductal adenocarcinoma with peritoneal carcinomatosis, demonstrating hepatoid differentiation upon conventional hematoxylin and eosin staining is reported in the present study. The patient presented with severe abdominal pain, and the radiological investigations performed revealed ovarian and hepatic tumor masses and peritoneal lesions, which were surgically removed. The gross examination of the peritoneum and omentum revealed multiple solid, firm, grey-white nodules, diffusely infiltrating the adipose tissue. The microscopic examination revealed a malignant epithelial proliferation, composed of polygonal cells with abundant eosinophilic cytoplasm and irregular, pleomorphic nuclei. Certain cells presented with intracytoplasmic mucus inclusions, raising suspicion of a HC with an uncertain histogenesis. Immunohistochemical staining was performed, and the tumor cells were found to be positive for cytokeratin (CK)7, CK18 and mucin 5AC, whereas negative staining for CK20, caudal-type homeobox transcription factor 2, α-fetoprotein, paired box gene 8, GATA-binding protein 3 and Wilms tumor 1 were documented. Thus, the diagnosis of metastatic pancreatic adenocarcinoma was established. The main aim of the present study was to provide further knowledge concerning poorly differentiated metastatic adenocarcinoma resembling HC, emphasizing the histopathological and immunohistochemical features of these malignant lesions and raising awareness of the diagnostic difficulties that may arise, as well as the importance of the use immunohistochemistry in differentiating carcinomas of uncertain histogenesis.

Papel da imagem na indicação da eletroporação irreversível no manejo terapêutico do adenocarcinoma de pâncreas

Resumo O adenocarcinoma ductal de pâncreas é uma das neoplasias malignas mais agressivas, com taxas de sobrevivência anuais inferiores a 20%. Os métodos axiais (tomografia computadorizada e ressonância magnética) têm papel fundamental no diagnóstico e estadiamento da doença, por fornecerem adequada resolução anatômica na avaliação de estruturas-chave, principalmente vasculares. O adenocarcinoma ductal de pâncreas é frequentemente descoberto em estágios avançados e sem viabilidade de ressecção cirúrgica, e nesse cenário o desenvolvimento de alternativas terapêuticas minimamente invasivas tem sido ainda mais importante para a mudança de sua história natural. A eletroporação irreversível, procedimento intervencionista que minimiza efeitos deletérios nos tecidos adjacentes, vem se destacando no tratamento de lesões tradicionalmente consideradas irressecáveis. Essa técnica, apesar de ganhar cada vez mais espaço no manejo terapêutico do adenocarcinoma ductal de pâncreas, ainda é pouco familiar aos radiologistas. Neste estudo, buscamos expor, de forma sucinta e didática, os fundamentos da técnica, as principais características de imagem e os critérios de elegibilidade que devem ser considerados para indicação da eletroporação irreversível nessa doença.

The progress of PET/MRI in clinical management of patients with pancreatic malignant lesions

Recently, the morbidity and mortality of pancreatic cancer have been increasing year by year. Because of its deep anatomical location and because most presented patients often suffer from abdominal pain or jaundice, it is difficult to diagnose pancreatic cancer at an early stage, leading to late clinical stage and poor prognosis. integrated positron emission tomography/magnetic resonance imaging (PET/MRI) fusion imaging not only has the characteristics of high resolution and multi-parameter imaging of MRI, but also combines the high sensitivity and the semi-quantitative characteristics of PET. In addition, the continuous development of novel MRI imaging and PET imaging biomarkers provide a unique and precise research direction for future pancreatic cancer research. This review summarizes the value of PET/MRI in the diagnosis, staging, efficacy monitoring, and prognosis evaluation of pancreatic cancer, and prognosis for developing emerging imaging agents and artificial intelligence radiomics in pancreatic cancer.

Role of imaging in the applicability of irreversible electroporation for the management of pancreatic adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the most aggressive malignant neoplasms, with a one-year survival rate below 20%. Axial methods (computed tomography and magnetic resonance imaging) play a fundamental role in the diagnosis and staging of the disease, because they provide adequate anatomical resolution in the assessment of key structures, mainly vascular structures. Pancreatic ductal adenocarcinoma is most often discovered in advanced stages, when surgical resection is no longer feasible. In that scenario, minimally invasive treatment alternatives have been developed in attempts to change the natural history of the disease. Irreversible electroporation, an interventional procedure that minimizes deleterious effects on adjacent tissues, has proven useful for the treatment of tumors traditionally considered unresectable. Despite the growing acknowledgment of this technique as a tool for the management of pancreatic ductal adenocarcinoma, it is still relatively unknown among radiologists. In this study, we sought to provide an overview of the main characteristics and eligibility criteria that must be considered for the indication of irreversible electroporation in cases of pancreatic ductal adenocarcinoma.

Application of Unenhanced Computed Tomography Texture Analysis to Differentiate Pancreatic Adenosquamous Carcinoma from Pancreatic Ductal Adenocarcinoma

OBJECTIVE

The objective of this study was to investigate the application of unenhanced computed tomography (CT) texture analysis in differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC).

METHODS

Preoperative CT images of 112 patients (31 with PASC, 81 with PDAC) were retrospectively reviewed. A total of 396 texture parameters were extracted from AnalysisKit software for further texture analysis. Texture features were selected for the differentiation of PASC and PDAC by the Mann-Whitney U test, univariate logistic regression analysis, and the minimum redundancy maximum relevance algorithm. Furthermore, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the texture feature-based model by the random forest (RF) method. Finally, the robustness and reproducibility of the predictive model were assessed by the 10-times leave-group-out cross-validation (LGOCV) method.

RESULTS

In the present study, 10 texture features to differentiate PASC from PDAC were eventually retained for RF model construction after feature selection. The predictive model had a good classification performance in differentiating PASC from PDAC, with the following characteristics: sensitivity, 95.7%; specificity, 92.5%; accuracy, 94.3%; positive predictive value (PPV), 94.3%; negative predictive value (NPV), 94.3%; and area under the ROC curve (AUC), 0.98. Moreover, the predictive model was proved to be robust and reproducible using the 10-times LGOCV algorithm (sensitivity, 90.0%; specificity, 71.3%; accuracy, 76.8%; PPV, 59.0%; NPV, 95.2%; and AUC, 0.80).

CONCLUSION

The unenhanced CT texture analysis has great potential for differentiating PASC from PDAC.

Resectable and Borderline Resectable Pancreatic Ductal Adenocarcinoma: Role of the Radiologist and Oncologist in the Era of Precision Medicine

The incidence and mortality of pancreatic ductal adenocarcinoma are growing over time. The management of patients with pancreatic ductal adenocarcinoma involves a multidisciplinary team, ideally involving experts from surgery, diagnostic imaging, interventional endoscopy, medical oncology, radiation oncology, pathology, geriatric medicine, and palliative care. An adequate staging of pancreatic ductal adenocarcinoma and re-assessment of the tumor after neoadjuvant therapy allows the multidisciplinary team to choose the most appropriate treatment for the patient. This review article discusses advancement in the molecular basis of pancreatic ductal adenocarcinoma, diagnostic tools available for staging and tumor response assessment, and management of resectable or borderline resectable pancreatic cancer.

Abnormal Findings on "T1WI or DWI or MRCP:" An Effective Boolean Interpretation Model in Discriminating Small Pancreatic Ductal Adenocarcinoma from Control Group

Objectives

The objectives of the study was to evaluate the diagnostic performance of findings on T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and magnetic resonance cholangiopancreatography (MRCP) separately and to identify an optimal Boolean interpretation model for discriminating patients with small pancreatic ductal adenocarcinoma (PDAC) from control groups in clinical practice.

Material and Methods

We retrospectively enrolled 30 patients with surgery confirmed small PDAC (≤20 mm) and 302 patients without pancreatic abnormality between April 2008 and February 2020. The presence of masses was evaluated by T1WI, T2WI, and DWI. Abnormality of the main pancreatic duct (MPD) was evaluated by T2WI and MRCP. Multivariate logistic regression analysis was performed to select significant sequences for discriminating the small PDAC and control groups. Boolean operators "OR" or "AND" were used to construct sequence combinations. Diagnostic performances of these sequences and combinations were evaluated by X ² tests.

Results

The sensitivity of T2WI was lowest (20%) for detecting masses. For evaluating MPD abnormality, sensitivity was higher for MRCP than for T2WI (86.7% vs. 53.3%). Multivariate logistic regression analysis showed that T1WI and DWI for detecting the presence of masses and MRCP for evaluating MPD abnormality were significantly associated with differentiation between the two groups (P = 0.0002, P = 0.0484, and P < 0.0001, respectively). Seven combinations were constructed with T1WI, DWI, and MRCP. The combination of findings on "T1WI or DWI or MRCP" achieved the highest sensitivity of 96.7% and negative predictive value of 99.6%.

Conclusion

The combination of findings on "T1WI or DWI or MRCP" might be an optimal interpretation model for discriminating small PDAC from control groups in clinical practice.

Multimodality Imaging for the Staging of Pancreatic Cancer

Imaging plays a key role in the diagnosis, staging, and follow-up of pancreatic ductal adenocarcinoma. The pancreatic protocol dual-phase multidetector computed tomography scan is the imaging modality of choice. A computed tomography scan is highly accurate for pancreatic tumor detection, assessment of resectability, and detection of metastatic disease. This article reviews key principles of the acquisition, interpretation, and reporting of pancreatic ductal adenocarcinoma imaging with computed tomography scanning and highlights potential roles for newer and supplemental imaging technologies. We discuss the importance of structured interpretation and reporting for providing the most complete and accurate assessment of tumor stage and resectability.

18F-FDG PET/CT imaging biomarkers for early and late evaluation of response to first-line chemotherapy in patients with pancreatic ductal adenocarcinoma

Purpose: The purpose of this study was to evaluate ¹⁸F-FDG-PET/CT as an early and late interim imaging biomarker in patients with pancreatic ductal adenocarcinoma (PDAC) who undergo first-line systemic therapy. Methods: This was a prospective, single-center, single-arm, open-label study (IRB12-000770). Patient receiving first line chemotherapy were planned to undergo a baseline ¹⁸F-FDG-PET/CT (PET1), early interim ¹⁸F-FDG PET/CT (PET2) and late interim ¹⁸F-FDG-PET/CT (PET3). ROC selected and established (mPERCIST / RECIST1.1) cut-offs for metabolic and radiographic tumor response assessment were applied. Patients were followed to collect data on further treatments and overall survival (OS). Results: The study population consisted of 28 patients who underwent PET1. Twenty-three of these (82%) underwent PET2 and 21 (75%) PET3, respectively. Twenty-three deaths occurred during a median follow up period of 14 months (maximum follow up, 58.3 months). The median OS was 36.2 months (95%CI, 28-NYR) in early metabolic responders (6/23 (26%), P = 0.016) and 25.4 months (95%CI, 19.6-NYR) in early radiographic responders (7/23 (30%), P = 0.16). The median overall survival was 27.4 months (95%CI, 21.4-NYR) in late metabolic responders (10/21 (48%), P = 0.058) and 58.2 months (95%CI, 21.4-NYR) in late radiographic responders (7/21 (33%), P = 0.008). Conclusion: ¹⁸F-FDG PET may serve as early interim imaging biomarker (~ at 4 weeks) for evaluation of response to first-line chemotherapy in patients with PDAC. Radiographic changes might be sufficient for response evaluation after the completion of first line chemotherapy.

CT Abnormalities of the Pancreas Associated With the Subsequent Diagnosis of Clinical Stage I Pancreatic Ductal Adenocarcinoma More Than One Year Later: A Case-Control Study

Background: Pancreatic ductal adenocarcinoma (PDAC) is highly lethal, partly due to challenges in early diagnosis. However, the prognosis for earlier stages (carcinoma in situ or stage T1a invasive carcinoma) is relatively favorable. Objective: To investigate findings of an earlier diagnosis of PDAC on pre-diagnostic CT examinations performed at least one year before the diagnosis of clinical stage I PDAC. Methods: This retrospective study included 103 patients with clinical stage I PDAC and a pre-diagnostic CT at least one year before the CT that detected PDAC, as well as 103 control patients without PDAC on CT examinations separated by at least 10 years. The frequency and temporal characteristics of focal pancreatic abnormalities (pancreatic mass, main pancreatic duct (MPD) change, parenchymal atrophy, faint parenchymal enhancement, cyst, and parenchymal calcification) on pre-diagnostic CT examinations were determined. Results: A focal pancreatic abnormality was present on the most recent pre-diagnostic CT in 55/103 (53.4%) patients with PDAC versus 21/103 (20.4%) control patients (p<.001). In patients with PDAC, the most common focal abnormalities on pre-diagnostic CT were atrophy (39/103, 37.9%), faint enhancement (17/65, 26.2%), and MPD change (14/103, 13.6%), which were all more frequent in patients with PDAC than in control patients (p<.05). In 54/55 (98.2%) patients with PDAC, the PDAC corresponded with the site of a focal abnormality (exact location or the abnormality's upstream or downstream edge) on pre-diagnostic CT. Frequency of focal abnormalities decreased with increasing time before the CT that detected PDAC (1-2 years before diagnosis, 64.9%; 2-3 years, 49.2%; 3-5 years, 41.8%; 5-7 years, 29.7%; 7-10 years, 18.5%; over 10 years, 0%). Mean duration from the finding's initial appearance to diagnosis of PDAC was 4.6 years for atrophy, 3.3 years for faint enhancement, and 1.1 years for MPD change. Conclusion: Most patients with clinical stage I PDAC demonstrated focal pancreatic abnormalities on pre-diagnostic CT obtained at least one year before diagnosis. Focal MPD change exhibited the shortest duration from its development to subsequent diagnosis, where atrophy and faint enhancement exhibited a relatively prolonged course. Clinical impact: These findings could facilitate earlier PDAC diagnosis and thus improve prognosis.

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.

New advances in CT imaging of pancreas diseases: a narrative review

Computed tomography (CT) plays a pivotal role as a diagnostic tool in many diagnostic and diffuse pancreatic diseases. One of the major limits of CT is related to the radiation exposure of young patients undergoing repeated examinations. Besides the standard CT protocol, the most recent technological advances, such as low-voltage acquisitions with high performance X-ray tubes and iterative reconstructions, allow for significant optimization of the protocol with dose reduction. The variety of CT tools are further expanded by the introduction of dual energy: the production of energy-selective images (i.e., virtual monochromatic images) improves the image contrast and lesion detection while the material-selective images (e.g., iodine maps or virtual unenhanced images) are valuable for lesion detection and dose reduction. The perfusion techniques provide diagnostic and prognostic information lesion and parenchymal vascularization and interstitium. Both dual energy and perfusion CT have the potential for pushing the limits of conventional CT from morphological evaluation to quantitative imaging applied to inflammatory and oncological diseases. Advances in post-processing of CT images, such as pancreatic volumetry, texture analysis and radiomics provide relevant information for pancreatic function but also for the diagnosis, management and prognosis of pancreatic neoplasms. Artificial intelligence is promising for optimization of the workflow in qualitative and quantitative analyses. Finally, basic concepts on the role of imaging on screening of pancreatic diseases will be provided.

Emodin-Conjugated PEGylation of Fe3O4 Nanoparticles for FI/MRI Dual-Modal Imaging and Therapy in Pancreatic Cancer

BACKGROUND

Pancreatic cancer (PC) remains a difficult tumor to diagnose and treat. It is often diagnosed as advanced by reason of the anatomical structure of the deep retroperitoneal layer of the pancreas, lack of typical symptoms and effective screening methods to detect this malignancy, resulting in a low survival rate. Emodin (EMO) is an economical natural product with effective treatment and few side effects of cancer treatment. Magnetic nanoparticles (MNPs) can achieve multiplexed imaging and targeted therapy by loading a wide range of functional materials such as fluorescent dyes and therapeutic agents.

PURPOSE

The purpose of this study was to design and evaluate a multifunctional theranostic nanoplatform for PC diagnosis and treatment.

METHODS

In this study, we successfully developed EMO-loaded, Cy7-functionalized, PEG-coated Fe₃O₄ (Fe₃O₄-PEG-Cy7-EMO). Characteristics including morphology, hydrodynamic size, zeta potentials, stability, and magnetic properties of Fe₃O₄-PEG-Cy7-EMO were evaluated. Fluorescence imaging (FI)/magnetic resonance imaging (MRI) and therapeutic treatment were examined in vitro and in vivo.

RESULTS

Fe₃O₄-PEG-Cy7-EMO nanoparticles had a core size of 9.9 ± 1.2 nm, which showed long-time stability and FI/MRI properties. Bio-transmission electron microscopy (bio-TEM) results showed that Fe₃O₄-PEG-Cy7-EMO nanoparticles were endocytosed into BxPC-3 cells, while few were observed in hTERT-HPNE cells. Prussian blue staining also confirmed that BxPC-3 cells have a stronger phagocytic ability as compared to hTERT-HPNE cells. Additionally, Fe₃O₄-PEG-Cy7-EMO had a stronger inhibition effect on BxPC-3 cells than Fe₃O₄-PEG and EMO. The hemolysis experiment proved that Fe₃O₄-PEG-Cy7-EMO can be used in vivo experiments. In vivo analysis demonstrated that Fe₃O₄-PEG-Cy7-EMO enabled FI/MRI dual-modal imaging and targeted therapy in pancreatic tumor xenografted mice.

CONCLUSION

Fe₃O₄-PEG-Cy7-EMO may serve as a potential theranostic nanoplatform for PC.

Computed Tomography-Based Radiomics Signature for the Preoperative Differentiation of Pancreatic Adenosquamous Carcinoma From Pancreatic Ductal Adenocarcinoma

Purpose

The purpose was to assess the predictive ability of computed tomography (CT)-based radiomics signature in differential diagnosis between pancreatic adenosquamous carcinoma (PASC) and pancreatic ductal adenocarcinoma (PDAC).

Materials and Methods

Eighty-one patients (63.6 ± 8.8 years old) with PDAC and 31 patients (64.7 ± 11.1 years old) with PASC who underwent preoperative CE-CT were included. A total of 792 radiomics features were extracted from the late arterial phase (n = 396) and portal venous phase (n = 396) for each case. Significantly different features were selected using Mann-Whitney U test, univariate logistic regression analysis, and minimum redundancy and maximum relevance method. A radiomics signature was constructed using random forest method, the robustness and the reliability of which was validated using 10-times leave group out cross-validation (LGOCV) method.

Results

Seven radiomics features from late arterial phase images and three from portal venous phase images were finally selected. The radiomics signature performed well in differential diagnosis between PASC and PDAC, with 94.5% accuracy, 98.3% sensitivity, 90.1% specificity, 91.9% positive predictive value (PPV), and 97.8% negative predictive value (NPV). Moreover, the radiomics signature was proved to be robust and reliable using the LGOCV method, with 76.4% accuracy, 91.1% sensitivity, 70.8% specificity, 56.7% PPV, and 96.2% NPV.

Conclusion

CT-based radiomics signature may serve as a promising non-invasive method in differential diagnosis between PASC and PDAC.

Imaging diagnosis and staging of pancreatic ductal adenocarcinoma: a comprehensive review

Pancreatic ductal adenocarcinoma (PDAC) has continued to have a poor prognosis for the last few decades in spite of recent advances in different imaging modalities mainly due to difficulty in early diagnosis and aggressive biological behavior. Early PDAC can be missed on CT due to similar attenuation relative to the normal pancreas, small size, or hidden location in the uncinate process. Tumor resectability and its contingency on the vascular invasion most commonly assessed with multi-phasic thin-slice CT is a continuously changing concept, particularly in the era of frequent neoadjuvant therapy. Coexistent celiac artery stenosis may affect the surgical plan in patients undergoing pancreaticoduodenectomy. In this review, we discuss the challenges related to the imaging of PDAC. These include radiological and clinical subtleties of the tumor, evolving imaging criteria for tumor resectability, preoperative diagnosis of accompanying celiac artery stenosis, and post-neoadjuvant therapy imaging. For each category, the key imaging features and potential pitfalls on cross-sectional imaging will be discussed. Also, we will describe the imaging discriminators of potential mimickers of PDAC.