Multimodel magnetic resonance imaging of mass-forming autoimmune pancreatitis: differential diagnosis with pancreatic ductal adenocarcinoma

Proliferative features of IgG4-related disease

IgG4-related disease is an immune-mediated disease that can lead to substantial morbidity and organ damage. Capable of affecting nearly any organ system or anatomic site, and showing considerable overlap in clinical presentation with various other diseases, IgG4-related disease often poses a diagnostic challenge for clinicians. Furthermore, there are no diagnostic biomarkers with high specificity for IgG4-related disease, and histopathological examination is nuanced and requires clinical correlation for accurate diagnosis. Therefore, it is crucial for clinicians to recognise the clinical phenotypes of IgG4-related disease. The disease is generally considered to have predominantly fibrotic and proliferative (or inflammatory) manifestations, with distinct clinical, serological and histopathological findings associated with each manifestation. However, the fibrotic and proliferative manifestations of this disease frequently occur together, thereby blurring this dichotomous distinction. In this Series paper, we provide a detailed overview of the clinical manifestations typical of the proliferative features of IgG4-related disease, with an emphasis on the diagnostic evaluation and differential diagnosis of each proliferative disease manifestation. In addition, we summarise the immune mechanisms underlying IgG4-related disease, suggest a framework for how to approach management and monitoring after the diagnosis is established, and highlight current unmet needs for patient care surrounding this disease.

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.

Late/delayed gadolinium enhancement in MRI after intravenous administration of extracellular gadolinium-based contrast agents: is it worth waiting?

The acquisition of images minutes or even hours after intravenous extracellular gadolinium-based contrast agents (GBCA) administration ("Late/Delayed Gadolinium Enhancement" imaging; in this review, further termed LGE) has gained significant prominence in recent years in magnetic resonance imaging. The major limitation of LGE is the long examination time; thus, it becomes necessary to understand when it is worth waiting time after the intravenous injection of GBCA and which additional information comes from LGE. LGE can potentially be applied to various anatomical sites, such as heart, arterial vessels, lung, brain, abdomen, breast, and the musculoskeletal system, with different pathophysiological mechanisms. One of the most popular clinical applications of LGE regards the assessment of myocardial tissue thanks to its ability to highlight areas of acute myocardial damage and fibrotic tissues. Other frequently applied clinical contexts involve the study of the urinary tract with magnetic resonance urography and identifying pathological abdominal processes characterized by high fibrous stroma, such as biliary tract tumors, autoimmune pancreatitis, or intestinal fibrosis in Crohn's disease. One of the current areas of heightened research interest revolves around the possibility of non-invasively studying the dynamics of neurofluids in the brain (the glymphatic system), the disruption of which could underlie many neurological disorders.

Pancreatic cancer, autoimmune or chronic pancreatitis, beyond tissue diagnosis: Collateral imaging and clinical characteristics may differentiate them

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies and is developing into the 2^nd leading cause of cancer-related death. Often, the clinical and radiological presentation of PDAC may be mirrored by other inflammatory pancreatic masses, such as autoimmune pancreatitis (AIP) and mass-forming chronic pancreatitis (MFCP), making its diagnosis challenging. Differentiating AIP and MFCP from PDAC is vital due to significant therapeutic and prognostic implications. Current diagnostic criteria and tools allow the precise differentiation of benign from malignant masses; however, the diagnostic accuracy is imperfect. Major pancreatic resections have been performed in AIP cases under initial suspicion of PDAC after a diagnostic approach failed to provide an accurate diagnosis. It is not unusual that after a thorough diagnostic evaluation, the clinician is confronted with a pancreatic mass with uncertain diagnosis. In those cases, a re-evaluation must be entertained, preferably by an experienced multispecialty team including radiologists, pathologists, gastroenterologists, and surgeons, looking for disease-specific clinical, imaging, and histological hallmarks or collateral evidence that could favor a specific diagnosis. Our aim is to describe current diagnostic limitations that hinder our ability to reach an accurate diagnosis among AIP, PDAC, and MFCP and to highlight those disease-specific clinical, radiological, serological, and histological characteristics that could support the presence of any of these three disorders when facing a pancreatic mass with uncertain diagnosis after an initial diagnostic approach has been unsuccessful.

Diagnostic accuracy of apparent diffusion coefficient to differentiate intrapancreatic accessory spleen from pancreatic neuroendocrine tumors

BACKGROUND

Intrapancreatic accessory spleen (IPAS) shares similar imaging findings with hypervascular pancreatic neuroendocrine tumors (PNETs), which may lead to unnecessary surgery.

AIM

To investigate and compare the diagnostic performance of absolute apparent diffusion coefficient (ADC) and normalized ADC (lesion-to-spleen ADC ratios) in the differential diagnosis of IPAS from PNETs.

METHODS

A retrospective study consisting of 29 patients (16 PNET patients vs 13 IPAS patients) who underwent preoperative contrast-enhanced magnetic resonance imaging together with diffusion-weighted imaging/ADC maps between January 2017 and July 2020 was performed. Two independent reviewers measured ADC on all lesions and spleens, and normalized ADC was calculated for further analysis. The receiver operating characteristics analysis was carried out for evaluating the diagnostic performance of both absolute ADC and normalized ADC values in the differential diagnosis between IPAS and PNETs by clarifying sensitivity, specificity, and accuracy. Inter-reader reliability for the two methods was evaluated.

RESULTS

IPAS had a significantly lower absolute ADC (0.931 ± 0.773 × 10^-3 mm²/s vs 1.254 ± 0.219 × 10^-3 mm²/s) and normalized ADC value (1.154 ± 0.167 vs 1.591 ± 0.364) compared to PNET. A cutoff value of 1.046 × 10^-3 mm²/s for absolute ADC was associated with 81.25% sensitivity, 100% specificity, and 89.66% accuracy with an area under the curve of 0.94 (95% confidence interval: 0.8536-1.000) for the differential diagnosis of IPAS from PNET. Similarly, a cutoff value of 1.342 for normalized ADC was associated with 81.25% sensitivity, 92.31% specificity, and 86.21% accuracy with an area under the curve of 0.91 (95% confidence interval: 0.8080-1.000) for the differential diagnosis of IPAS from PNET. Both methods showed excellent inter-reader reliability with intraclass correlation coefficients for absolute ADC and ADC ratio being 0.968 and 0.976, respectively.

CONCLUSION

Both absolute ADC and normalized ADC values can facilitate the differentiation between IPAS and PNET.

Role of contrast-enhanced ultrasound with time-intensity curve analysis for differentiating hypovascular solid pancreatic lesions

OBJECTIVES

To evaluate the clinical value of contrast-enhanced ultrasound (CEUS) with time-intensity curve (TIC) in distinguishing different types of hypovascular solid pancreatic lesions.

METHODS

A total of 89 patients with 90 pancreatic lesions (all confirmed by surgery or biopsy pathology) that manifested hypoenhancement on contrast-enhanced ultrasound (CEUS) were included in this study. Six peak enhancement patterns were proposed for differentiating hypovascular pancreatic lesions. CEUS qualitative and TIC-based quantitative parameters were analyzed, and each lesion was scored based on the statistically significant qualitative parameters to evaluate the diagnostic ability of CEUS for hypovascular solid pancreatic lesions.

RESULTS

Qualitative parameters such as peak enhancement pattern II/III/IV, penetrating vessels, centripetal enhancement, and early washout were reliable indicators of malignant lesions, and lesions scored based on these qualitative parameters, with a score ≥ 2, were highly suspected to be malignant lesions. Pattern I had an accuracy of 83.33% for predicting mass-forming pancreatitis (MFP), pattern V had an accuracy of 96.67% for predicting solid pseudopapillary tumors of the pancreas (SPTP), and pattern VI had an accuracy of 81.11% for predicting neuroendocrine tumors/carcinomas (NETs/NECs). For quantitative analysis, nodule/pancreatic parenchyma echo intensity reduction ratio was significantly greater in malignant lesions.

CONCLUSIONS

CEUS qualitative and TIC-based quantitative parameters have clinical value in distinguishing malignant from benign hypovascular pancreatic lesions.

KEY POINTS

• Contrast-enhanced ultrasound helps clinicians assess patients with pancreatic lesions. • Six peak enhancement patterns are proposed for differentiating pancreatic hypovascular lesions. • Qualitative parameters such as peak enhancement pattern II/III/IV, penetrating vessels, centripetal enhancement, early washout, and quantitative parameter nodule/pancreatic parenchyma echo intensity reduction ratio were important characteristics to discriminate malignant from hypovascular benign lesions.

A multidomain fusion model of radiomics and deep learning to discriminate between PDAC and AIP based on 18F-FDG PET/CT images

PURPOSE

To explore a multidomain fusion model of radiomics and deep learning features based on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) images to distinguish pancreatic ductal adenocarcinoma (PDAC) and autoimmune pancreatitis (AIP), which could effectively improve the accuracy of diseases diagnosis.

MATERIALS AND METHODS

This retrospective study included 48 patients with AIP (mean age, 65 ± 12.0 years; range, 37-90 years) and 64 patients with PDAC patients (mean age, 66 ± 11.3 years; range, 32-88 years). Three different methods were discussed to identify PDAC and AIP based on ¹⁸F-FDG PET/CT images, including the radiomics model (RAD_model), the deep learning model (DL_model), and the multidomain fusion model (MF_model). We also compared the classification results of PET/CT, PET, and CT images in these three models. In addition, we explored the attributes of deep learning abstract features by analyzing the correlation between radiomics and deep learning features. Five-fold cross-validation was used to calculate receiver operating characteristic (ROC), area under the roc curve (AUC), accuracy (Acc), sensitivity (Sen), and specificity (Spe) to quantitatively evaluate the performance of different classification models.

RESULTS

The experimental results showed that the multidomain fusion model had the best comprehensive performance compared with radiomics and deep learning models, and the AUC, accuracy, sensitivity, specificity were 96.4% (95% CI 95.4-97.3%), 90.1% (95% CI 88.7-91.5%), 87.5% (95% CI 84.3-90.6%), and 93.0% (95% CI 90.3-95.6%), respectively. And our study proved that the multimodal features of PET/CT were superior to using either PET or CT features alone. First-order features of radiomics provided valuable complementary information for the deep learning model.

CONCLUSION

The preliminary results of this paper demonstrated that our proposed multidomain fusion model fully exploits the value of radiomics and deep learning features based on ¹⁸F-FDG PET/CT images, which provided competitive accuracy for the discrimination of PDAC and AIP.

Radiomics and Its Applications and Progress in Pancreatitis: A Current State of the Art Review

Radiomics involves high-throughput extraction and analysis of quantitative information from medical images. Since it was proposed in 2012, there are some publications on the application of radiomics for (1) predicting recurrent acute pancreatitis (RAP), clinical severity of acute pancreatitis (AP), and extrapancreatic necrosis in AP; (2) differentiating mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC), focal autoimmune pancreatitis (AIP) from PDAC, and functional abdominal pain (functional gastrointestinal diseases) from RAP and chronic pancreatitis (CP); and (3) identifying CP and normal pancreas, and CP risk factors and complications. In this review, we aim to systematically summarize the applications and progress of radiomics in pancreatitis and it associated situations, so as to provide reference for related research.

Nonhypovascular pancreatic ductal adenocarcinomas: CEUS imaging findings and differentiation from other types of solid pancreatic lesions

OBJECTIVES

To observe and assess the diagnostic value of contrast-enhanced ultrasound (CEUS) in patients with iso-/hypervascular solid pancreatic lesions.

METHODS

70 pancreatic lesions (all confirmed by surgery or biopsy pathology) that manifested iso-/hyperenhancement on CEUS were retrospectively studied from January 2018 to January 2022, including 24 pancreatic ductal adenocarcinomas (PDAC), 15 mass-forming pancreatitis (MFP), 24 pancreatic neuroendocrine tumors (PNET) (14 hyper-PNETs, 10 iso-PNETs), and 7 solid pseudopapillary tumors of pancreas (SPTP). 65 pancreatic ductal adenocarcinomas (PDAC) that manifested hypoenhancement on CEUS were retrospectively studied from January 2020 to January 2022. CEUS patterns and the clinical and pathologic features were analyzed, and the diagnostic ability of CEUS for iso/hyperenhanced solid pancreatic lesions was assessed.

RESULTS

Centripetal enhancement, heterogeneous enhancement, early washout, and hypoenhancement in the late phase mostly appeared in iso-/hyper-PDACs (p < 0.05). Heterogeneous enhancement in small lesions (< 3 cm) as the diagnostic criterion for iso-/hyper-PDACs had an accuracy of 74.3% and a specificity of 91.3%. Iso-PNETs more commonly had larger tumor sizes and more often showed heterogeneous enhancement than hyper-PNETs (p = 0.007, p = 0.035, respectively). The characteristics of the combination of isoenhancement, homogeneous enhancement, and synchronous wash-in/out for MFP had a high accuracy of 90%. Capsular enhancement with heterogeneous enhancement inside for SPTP had an accuracy of 97.1%.

CONCLUSION

CEUS enhancement patterns have potentially great value in the differentiation of iso-/hyperenhanced pancreatic lesions.