Thickness of the Hyperechoic Capsule-like Rim Around Pancreatic Lesions Measured by Ultrasound for Differentiating Between Type 1 Autoimmune Pancreatitis and Pancreatic Adenocarcinoma

Background: Autoimmune pancreatitis (AIP) is often misdiagnosed as pancreatic adenocarcinoma (PAC), resulting in unnecessary surgical interventions. On computed tomography (CT) scans, the capsule-like rim is an essential radiological characteristic for differentiating AIP from PAC. It presents as a hypoattenuating halo surrounding the pancreas. However, this characteristic is infrequently observed in ultrasonography. Objectives: The aim of this study was to assess the accuracy of the thickness measurement of the capsule-like structure surrounding lesions during ultrasonography in order to distinguish between AIP and PAC. Patients and Methods: This case-control study was conducted on 19 patients with type 1 AIP (AIP1) as the case group and 37 patients with PAC as the controls. The ultrasound images of these patients were obtained from our institute's database. The thickest part of the hyperechoic capsule-like structure around lesions was identified and measured on the workstation retrospectively. The difference in the thickness of the capsule-like structure between AIP1 and PAC was compared in all lesions and mass lesions, respectively. The optimal cut-off thickness was determined by the maximum Youden index (calculated as sensitivity + specificity - 1). A P-value of < 0.05 (or < 0.05/3 after applying the Bonferroni correction) was considered statistically significant. Results: All lesions appeared hypoechoic, and there were no significant differences in gender, age, abdominal pain symptoms, jaundice, or weight loss between the case and control groups (P > 0.05). However, there was a significant difference regarding the involved pancreatic location (P = 0.008). Among the lesions, 46 were mass lesions. The hyperechoic capsule-like rim was thicker in the case group compared to the control group for all lesions (mean = 0.40 ± 0.12 vs. 0.32 ± 0.09 cm, P = 0.006) and also for mass lesions (mean = 0.41 ± 0.13 vs. 0.31 ± 0.09 cm, P = 0.006). The cut-off thickness for AIP1 was estimated at 0.41 cm, according to the maximum Youden index in both all lesions and mass lesions. The sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and odds ratio for all lesions were 0.58, 0.86, 0.77, 0.69, 0.80, and 8.80 (95% confidence interval [CI]: 2.37 – 32.64), respectively. In mass lesions, the corresponding values were 0.58, 0.88, 0.80, 0.64, 0.86, and 10.50 (95% CI: 2.23 – 49.52), respectively. Conclusion: Patients with a hyperechoic capsule-like rim thickness of ≥0.41 cm during ultrasonography are more likely to have AIP1. This finding holds valuable clinical significance in differentiating between AIP1 and PAC.

Differentiation of autoimmune pancreatitis from pancreatic adenocarcinoma using CT characteristics: a systematic review and meta-analysis

OBJECTIVES

To determine informational CT findings for distinguishing autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC) and to review their diagnostic accuracy.

METHODS

A systematic and detailed literature review was performed through PubMed, EMBASE, and the Cochrane library. Similar descriptors to embody the identical image finding were labeled as a single CT characteristic. We calculated the pooled diagnostic odds ratios (DORs) of each CT characteristic using a bivariate random-effects model.

RESULTS

A total of 145 various descriptors from 15 studies (including 562 AIP and 869 PDAC patients) were categorized into 16 CT characteristics. According to the pooled DOR, 16 CT characteristics were classified into three groups (suggesting AIP, suggesting PDAC, and not informational). Seven characteristics suggesting AIP were diffuse pancreatic enlargement (DOR, 48), delayed homogeneous enhancement (DOR, 46), capsule-like rim (DOR, 34), multiple pancreatic masses (DOR, 16), renal involvement (DOR, 15), retroperitoneal fibrosis (DOR, 13), and bile duct involvement (DOR, 8). Delayed homogeneous enhancement showed a pooled sensitivity of 83% and specificity of 85%. The other six characteristics showed relatively low sensitivity (12-63%) but high specificity (93-99%). Four characteristics suggesting PDAC were discrete pancreatic mass (DOR, 23), pancreatic duct cutoff (DOR, 16), upstream main pancreatic duct dilatation (DOR, 8), and upstream parenchymal atrophy (DOR, 7).

CONCLUSION

Eleven CT characteristics were informational to distinguish AIP from PDAC. Diffuse pancreatic enlargement, delayed homogeneous enhancement, and capsule-like rim suggested AIP with the highest DORs, whereas discrete pancreatic mass suggested PDAC. However, pooled sensitivities of informational CT characteristics were moderate.

CLINICAL RELEVANCE STATEMENT

This meta-analysis underscores eleven distinctive CT characteristics that aid in differentiating autoimmune pancreatitis from pancreatic adenocarcinoma, potentially preventing misdiagnoses in patients presenting with focal/diffuse pancreatic enlargement.

KEY POINTS

• Diffuse pancreatic enlargement (pooled diagnostic odds ratio [DOR], 48), delayed homogeneous enhancement (46), and capsule-like rim (34) were CT characteristics suggesting autoimmune pancreatitis. • The CT characteristics suggesting autoimmune pancreatitis, except delayed homogeneous enhancement, had a general tendency to show relatively low sensitivity (12-63%) but high specificity (93-99%). • Discrete pancreatic mass (pooled diagnostic odds ratio, 23) was the CT characteristic suggesting pancreatic ductal adenocarcinoma with the highest pooled DORs.

A CT based radiomics nomogram for differentiation between focal-type autoimmune pancreatitis and pancreatic ductal adenocarcinoma

Objectives

The purpose of this study was to develop and validate an CT-based radiomics nomogram for the preoperative differentiation of focal-type autoimmune pancreatitis from pancreatic ductal adenocarcinoma.

Methods

96 patients with focal-type autoimmune pancreatitis and pancreatic ductal adenocarcinoma have been enrolled in the study (32 and 64 cases respectively). All cases have been confirmed by imaging, clinical follow-up and/or pathology. The imaging data were considered as: 70% training cohort and 30% test cohort. Pancreatic lesions have been manually delineated by two radiologists and image segmentation was performed to extract radiomic features from the CT images. Independent-sample T tests and LASSO regression were used for feature selection. The training cohort was classified using a variety of machine learning-based classifiers, and 5-fold cross-validation has been performed. The classification performance was evaluated using the test cohort. Multivariate logistic regression analysis was then used to develop a radiomics nomogram model, containing the CT findings and Rad-Score. Calibration curves have been plotted showing the agreement between the predicted and actual probabilities of the radiomics nomogram model. Different patients have been selected to test and evaluate the model prediction process. Finally, receiver operating characteristic curves and decision curves were plotted, and the radiomics nomogram model was compared with a single model to visually assess its diagnostic ability.

Results

A total of 158 radiomics features were extracted from each image. 7 features were selected to construct the radiomics model, then a variety of classifiers were used for classification and multinomial logistic regression (MLR) was selected to be the optimal classifier. Combining CT findings with radiomics model, a prediction model based on CT findings and radiomics was finally obtained. The nomogram model showed a good sensitivity and specificity with AUCs of 0.87 and 0.83 in training and test cohorts, respectively. The areas under the curve and decision curve analysis showed that the radiomics nomogram model may provide better diagnostic performance than the single model and achieve greater clinical net benefits than the CT finding model and radiomics signature model individually.

Conclusions

The CT image-based radiomics nomogram model can accurately distinguish between focal-type autoimmune pancreatitis and pancreatic ductal adenocarcinoma patients and provide additional clinical benefits.

Radiomics based on diffusion-weighted imaging for differentiation between focal-type autoimmune pancreatitis and pancreatic carcinoma

OBJECTIVE

To evaluate the parameters of support vector machine (SVM) using imaging data generated from the apparent diffusion coefficient (ADC) to differentiate between focal-type autoimmune pancreatitis (f-AIP) and pancreatic ductal adenocarcinoma (PDAC) when using SVM based on diffusion-weighted imaging.

METHODS

The 2D-ADCmean and texture parameters (16 texture features × [non-filter+17 filters]) were retrospectively segmented by 2 readers in 28 patients with f-AIP and 77 patients with pathologically proven PDAC. The diagnostic accuracy of the SVM model was evaluated by receiver operating characteristic curve analysis and calculation of the area under the curve (AUC). Interreader reliability was assessed by intraclass correlation coefficient (ICC).

RESULTS

The 2D-ADCmean and 3D-ADCmean were significantly lower in cases of f-AIP (1.10-1.15 × 10-3 mm2/s and 1.21-1.23× 10-3 mm2/s, respectively) vs PDAC (1.29-1.33 × 10-3 mm2/s and 1.41-1.43 × 10-3 mm2/s, respectively), with excellent and good interreader reliability, respectively (ICC = 0.909 and 0.891, respectively). Among the texture parameters, energy with exponential filtering yielded the highest AUC (Reader 1: 74.7%, Reader 2: 81.5%), with fair interreader reliability (ICC = 0.707). The non-linear SVM, a combination of 2D-ADCmean, object volume and exponential-energy showed an AUC value of 96.2% in the testing cohorts.

CONCLUSION

Our results suggest that non-linear SVM using a combination of 2D-ADCmean, object volume, and exponential-energy may assist in differentiating f-AIP from PDAC.

ADVANCES IN KNOWLEDGE

The radiomics based on an apparent diffusion coefficient value may assist in differentiating f-AIP from PDAC.

The effect of CT texture-based analysis using machine learning approaches on radiologists' performance in differentiating focal-type autoimmune pancreatitis and pancreatic duct carcinoma

PURPOSE

To develop a support vector machine (SVM) classifier using CT texture-based analysis in differentiating focal-type autoimmune pancreatitis (AIP) and pancreatic duct carcinoma (PD), and to assess the radiologists' diagnostic performance with or without SVM.

MATERIALS AND METHODS

This retrospective study included 50 patients (20 patients with focal-type AIP and 30 patients with PD) who underwent dynamic contrast-enhanced CT. Sixty-two CT texture-based features were extracted from 2D images of the arterial and portal phase CTs. We conducted data compression and feature selections using principal component analysis (PCA) and produced the SVM classifier. Four readers participated in this observer performance study and the statistical significance of differences with and without the SVM was assessed by receiver operating characteristic (ROC) analysis.

RESULTS

The SVM performance indicated a high performance in differentiating focal-type AIP and PD (AUC = 0.920). The AUC for all 4 readers increased significantly from 0.827 to 0.911 when using the SVM outputs (p = 0.010). The AUC for inexperienced readers increased significantly from 0.781 to 0.905 when using the SVM outputs (p = 0.310). The AUC for experienced readers increased from 0.875 to 0.912 when using the SVM outputs, however, there was no significant difference (p = 0.018).

CONCLUSION

The use of SVM classifier using CT texture-based features improved the diagnostic performance for differentiating focal-type AIP and PD on CT.

Clinical Usefulness of [18F]-Fluoro-2-Deoxy-d-Glucose-Positron Emission Tomography/Computed Tomography for Distinguishing Between Autoimmune Pancreatitis and Pancreatic Cancer

OBJECTIVES

We investigated the [18F]-fluoro-2-deoxy-d-glucose (FDG)-positron emission tomography (PET)/computed tomography (CT) findings of pancreatic and extrapancreatic lesions in patients with autoimmune pancreatitis (AIP) and pancreatic cancer (PC) and evaluated the usefulness of 18F-FDG-PET/CT for differentiating between AIP and PC.

METHODS

Eighty-five patients, 19 with AIP and 66 with PC, who underwent 18F-FDG-PET/CT were studied retrospectively. We evaluated the maximum standardized uptake value (SUVmax), patterns and distributions of FDG activity in pancreatic lesions, as well as FDG uptake in extrapancreatic lesions.

RESULTS

The levels of SUVmax of pancreatic lesions in PC patients were significantly higher than those in AIP patients (P < 0.05). Focal/segmental distribution of FDG activity was found in 61.1% of the AIP patients and 98.4% of the PC patients. Heterogeneous FDG activity patterns were found in 61.1% of the AIP patients and 18.7% of the PC patients. Activities of FDG in pancreatic lesions were significantly different between AIP and PC. Extrapancreatic activities of salivary glands, extraperitoneal lymph nodes, prostate, retroperitoneum, and kidneys in the AIP patients were significantly higher than those in the PC patients (P < 0.05). Multivariate analysis revealed that SUVmax (>7.08) and focal/segmental FDG distribution were independent predictors of PC (P < 0.05).

CONCLUSIONS

The 18F-FDG-PET/CT findings are useful for differentiating between AIP and PC.

Comparison of five-phase computed tomography images of type 1 autoimmune pancreatitis and pancreatic cancer: Emphasis on cases with atypical images

BACKGROUND/OBJECTIVES

International consensus diagnostic criteria (ICDC) include characteristic images of autoimmune pancreatitis (AIP); however, reports on atypical cases are increasing. The aims of this study were to compare CT findings between AIP and pancreatic cancer (PC), and to analyze type 1 AIPs showing atypical images.

METHODS

Five-phase CT images were compared between 80 type 1-AIP lesions and 80 size- and location-matched PCs in the case-control study. Atypical AIPs were diagnosed based on the four ICDC items.

RESULTS

ICDC items were recognized in most AIP lesions; pancreatic enlargement (87.7%), narrowing of the main pancreatic duct (98.8%), delayed enhancement (100%), and no marked upstream-duct dilation (97.5%). CT values of AIPs increased rapidly until the pancreatic phase and decreased afterward, while those of PCs gradually increased until the delayed phase (P < 0.0001). Atypical images were recognized in 14.8% of AIPs, commonly without pancreatic enlargement (18.5 mm) and sometimes mimicking intraductal neoplasms. The CT values and their ratios were different between atypical AIPs and size-matched PCs most significantly in the pancreatic phase, but similar in the delayed phase.

CONCLUSIONS

Ordinary type 1 AIPs can be diagnosed with the ICDC, but atypical AIPs represented a small fraction. "Delayed enhancement" is characteristic to ordinary AIPs, however, "pancreatic-phase enhancement" is more diagnostic for atypical AIPs.

Differentiation of Focal-Type Autoimmune Pancreatitis From Pancreatic Ductal Adenocarcinoma Using Radiomics Based on Multiphasic Computed Tomography

OBJECTIVES

The aim of this study was to develop a radiomics model for a differential diagnosis of focal-type autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma.

METHODS

A total of 96 patients, 45 with AIP and 51 with pancreatic ductal adenocarcinoma, were retrospectively evaluated. All patients underwent pretreatment abdominal computed tomography imaging acquired at noncontrast, arterial, and venous phases. Furthermore, 1160 radiomics features were extracted from each phasic image to build radiomics models. The performance of radiomics model was evaluated by sensitivity, specificity, and accuracy. The results of radiomics model were also compared with those of radiologists' visual assessments.

RESULTS

The sensitivity, specificity, and accuracy of the optimal radiomics model were 93.3%, 96.1%, and 94.8%, respectively. They were higher than those of the radiologists' assessments with sensitivity of 57.78% and 73.33%, specificity of 88.24% and 90.20%, and accuracy of 75.00% and 81.25%, respectively.

CONCLUSION

Radiomics is helpful for a differential diagnosis of AIP in clinical practice as a noninvasive and quantitative method.

MRI in acute pancreatitis

Computed tomography (CT) is the most commonly performed imaging test for acute pancreatitis. Nevertheless, magnetic resonance (MRI) imaging is useful in many specific situations. These include evaluating patients with acute pancreatitis who cannot receive iodinated CT contrast, elucidating the underlying cause of acute pancreatitis, assessing ductal disconnection and for guiding intervention of necrotic collections. Non-contrast MRI is superior to non-contrast CT and MRI for the diagnosis of acute pancreatitis. We discuss these specific uses of MRI in acute pancreatitis. We highlight the future advances in MRI including faster, free-breathing scans that allow MRI to be completed within 10 min.

Differentiation of focal autoimmune pancreatitis from pancreatic ductal adenocarcinoma

Autoimmune pancreatitis (AIP) is an inflammatory process of the pancreas that occurs most commonly in elderly males and clinically can mimic pancreatic adenocarcinoma and present with jaundice, weight loss, and abdominal pain. Mass-forming lesions in the pancreas are seen in the focal form of AIP and both clinical and imaging findings can overlap those of pancreatic cancer. The accurate distinction of AIP from pancreatic cancer is of utmost importance as it means avoiding unnecessary surgery in AIP cases or inaccurate steroid treatment in patients with pancreatic cancer. Imaging concomitantly with serological examinations (IgG4 and Ca 19-9) plays an important role in the distinction between these entities. Characteristic extra-pancreatic manifestations as well as favorable good response to treatment with steroids are characteristic of AIP. This paper will review current diagnostic parameters useful in differentiating between focal AIP and pancreatic adenocarcinoma.

Type 2 Autoimmune Pancreatitis (Idiopathic Duct-Centric Pancreatitis) Highlighting Patients Presenting as Clinical Acute Pancreatitis: A Single-Center Experience

Background/Aims

Type 2 autoimmune pancreatitis (AIP) has been considered extremely rare in East Asia. This study aimed to clarify the prevalence, clinical characteristics and radiological findings of type 2 AIP highlighting patients presenting as acute pancreatitis in a single center.

Methods

Type 2 AIP patients were classified according to International Consensus Diagnostic Criteria. Radiological findings were compared between type 2 AIP presenting as acute pancreatitis and gallstone pancreatitis.

Results

Among 244 patients with AIP, 27 (11.1%) had type 2 AIP (definite, 15 [55.5%] and probable 12 [44.5%]). The median age of patients with type 2 AIP was 29 years (interquartile range, 20 to 39 years). Acute pancreatitis was the most common initial presentation (n=17, 63%) while obstructive jaundice was present in only one patient. Ulcerative colitis (UC) was associated with type 2 AIP in 44.4% (12/27) of patients. Radiological pancreatic imaging such as delayed enhancement of diffusely enlarged pancreas, homogeneous enhancement of focal enlargement/mass, absent/minimal peripancreatic fat infiltration or fluid collection, and multifocal main pancreatic duct narrowings were helpful for differentiating type 2 AIP from gallstone pancreatitis. During follow-up (median, 32.3 months), two patients (2/25, 8%) experienced relapse.

Conclusions

In South Korea, type 2 AIP is not as rare as previously thought. Overall, the clinical profile of type 2 AIP was similar to that of Western countries. Type 2 AIP should be considered in young UC patients with acute pancreatitis of uncertain etiology.

The use of magnetic resonance elastography in differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma: A preliminary study

PURPOSE

To assess the value of magnetic resonance elastography (MRE) in patients with autoimmune pancreatitis (AIP) and in the differentiation of AIP from pancreatic ductal adenocarcinoma (PDAC).

METHOD AND MATERIALS

This prospective study included 14 AIP patients, 26 PDAC patients, and 14 healthy volunteers. All participants underwent pancreatic MRE (40-Hz; 3 T scanner) at enrollment, and 7 AIP patients underwent a second MRE after initiation of steroid therapy. Pancreatic stiffness values were obtained by MRE and a new logistic regression model (the calculated Rad score) was used to combine pancreatic stiffness and the distribution and shape of high-stiffness areas for differentiation of AIP and PDAC. The area under the curve (AUC) was calculated for all parameters using receiver operating characteristic (ROC) analysis.

RESULTS

Pancreatic stiffness was significantly higher (2.67 kPa [interquartile range, 2.24-3.56 kPa]) in AIP than in healthy pancreas (1.24 kPa [1.18-1.24 kPa]) and significantly lower in AIP than in PDAC (3.78 kPa [3.22-5.11 kPa]; both P < 0.05). Diffuse (n = 4 vs 1; P = 0.043) and multiple (n = 3 vs 0; P = 0.037) lesions were more common in AIP, while solitary (n = 25 vs 7; P = 0.001) and nodular lesions (n = 18 vs 2; P =  0.002) were more frequent in PDAC. Rad scores outperformed individual imaging parameters in distinguishing AIP from PDAC (AUC, 0.948 vs 0.607 to 0.782; all P < 0.05), with 84.6% specificity and 92.9% sensitivity. Pancreatic stiffness in AIP decreased significantly, from 2.66 kPa [2.29 to 3.05 kPa] to 1.55 kPa [1.43 to 1.67 kPa] (P = 0.016), during treatment.

CONCLUSIONS

MRE shows promise as a quantitative imaging method for differentiating AIP from PDAC and for monitoring the treatment response in AIP.

Management of Autoimmune Pancreatitis

Type 1 autoimmune pancreatitis (AIP) is an IgG-4-related systemic disease that can manifest as a pancreatic disorder or another disorder of presumed autoimmune origin. Type 2 disease is typically characterized by absent IgG-4-positive cells. As patients often present with acute pancreatitis, obstructive jaundice, or pancreatic mass, it is imperative to exclude malignancy, a more common diagnosis. AIP may respond to corticosteroids, and has a strong association with other immune-mediated diseases. Recent literature suggests the benefit of immune-modulating therapy, including rituximab, although no consensus exists. This review covers the essentials of diagnosis, but focuses primarily on management of AIP.

Subspecialized radiology review at multidisciplinary pancreas conference: impact on patient management

PURPOSE

At our tertiary medical center, multidisciplinary subspecialists meet twice a week during a CME-accredited conference to discuss oncologic and non-oncologic patients with pancreatic diseases at which time a subspecialized abdominal staff radiologist reinterprets the patient's relevant imaging studies. This study assesses the changes in patient management due to imaging reinterpretation during multidisciplinary pancreas conference (MPC).

MATERIALS AND METHODS

In this retrospective, IRB-approved, HIPAA-compliant study, imaging studies of all patients discussed at MPC between July 1 and December 31, 2015 were assessed for technical adequacy, and original reports analyzed for congruency with reinterpretation. Management measures included change in diagnosis, clinical stage, treatment, or workup. Additional data were obtained on referring services affected and their resultant change in practice. Changes in surgical resectability, surgical approach, or delayed operative dates were noted for surgeons. Changes in chemotherapeutic or radiation oncology regimens as well as decisions for additional imaging, laboratory workup, or histologic evaluation were also recorded.

RESULTS

A total of 252 patients were included (54.4% males, 45.6% females, mean age 63.71 years). Relevant imaging consisted of 142 abdominal CT scans, 112 abdominal MRI scans, 1 abdominal ultrasound, and 1 nuclear medicine octreotide study of which 69.4% were performed in-house. Image quality was deemed appropriate in 95.2%. Cases presented included solid pancreatic malignancies (n = 140; 55.6%), cystic pancreatic lesions (n = 41; 16.3%), acute and chronic inflammatory conditions (n = 52; 20.6%), and miscellaneous entities (n = 10; 4.0%); 9 (3.6%) cases were normal. Image reinterpretation was congruent with original reports in 56.7%, with minor, moderate, and major discrepancies occurring in 9.5, 26.2%, and 7.5% of cases, respectively. Incongruent reinterpretation was predominantly due to perceptional errors (false-negative reports due to missed findings) and interpretative errors (false-positive results due to over-reporting or misclassification of diagnoses). Services most commonly affected included surgical oncology, radiology, and gastroenterology at 16.7%, 13.1%, and 12.7% of cases, respectively. Management changes included a change in diagnosis in 8.7%, change in clinical stage in 8.7%, change in treatment in 17.9%, and further workup needed in 19.0% of patients, respectively. No change in management occurred in the remaining 61.5% of cases.

CONCLUSIONS

Subspecialized abdominal radiologist reinterpretation in the context of more comprehensive patient information heavily impacts the multidisciplinary management of patients with pancreatic disorders. Further efforts are needed to solidify the abdominal radiologist's role in the multidisciplinary clinical setting.

Diagnostic value of targeted next-generation sequencing in patients with suspected pancreatic or periampullary cancer

Aims

Radiological imaging and morphological assessment of cytology material have limitations for preoperative classification of pancreatic or periampullary lesions, often resulting in surgical resection without definitive diagnosis. Our prospective study aims to define the diagnostic value of targeted next-generation sequencing (NGS) of DNA from cytology material.

Methods

Patients with a suspect pancreatic or periampullary lesion underwent standard diagnostic evaluation including preoperative morphological cytology assessment. Treatment options for suspect lesions were surgical exploration with possible resection, follow-up or palliation. The cytology samples were analysed with NGS, in which 50 genes were sequenced for the presence of pathogenic variants. The NGS results were integrated with the clinical information during multidisciplinary team meetings, and changes in the treatment plan were scored. Diagnostic accuracy of NGS analysis (malignancy vs benign disease) was calculated.

Results

NGS results of the cytology samples were confirmed in the resection specimens of the first 10 included patients. The integration of the NGS results led to a change in treatment plan in 7 out of 70 patients (from exploration to follow-up, n=4; from follow-up to exploration and resection, n=2; from palliation to resection, n=1). In four patients, the NGS results were contradictory, but did not affect the treatment plan. In the remaining 59 patients, NGS analysis supported the initial treatment plan. The diagnostic accuracy of NGS analysis was 94% (sensitivity=93%; specificity=100%).

Conclusions

NGS can change the treatment plan in a significant portion of patients with suspect pancreatic or periampullary lesions. Application of NGS can optimise treatment selection and diminish unnecessary surgeries.

Contrast-Enhanced Ultrasonography of Pancreatic Carcinoma: Correlation with Pathologic Findings

We concluded that contrast-enhanced ultrasound (CEUS) has clinical value in identifying the pathologic changes of pancreatic carcinomas. Forty-three patients diagnosed with pancreatic carcinoma through surgery were retrospectively investigated. CEUS examinations were performed on all patients before surgery. Enhancement patterns on CEUS were observed. Time-intensity curves of CEUS were generated for the regions of interest in the pancreas, and quantitative parameters were obtained. Resected cancer specimens were stained with hematoxylin and eosin for histologic analysis, and the microvascular density (MVD) of the specimens was determined by CD34 immunohistochemical staining. Enhancement patterns of CEUS were compared with histopathologic findings in pancreatic carcinomas. Correlations between time-intensity curve parameters and microvascular density were analyzed. Twenty cases manifested centripetal enhancement, and 23 cases, global enhancement. The amount of tumor necrosis or mucus in the centripetally enhanced pancreatic carcinomas was greater than that in the globally enhanced pancreatic carcinomas (p = 0.027). Thirty-eight of 43 (88.4%) pancreatic carcinomas manifested hypo-enhancement with a maximum intensity (IMAX) <90%. Contrast arrival time in pancreatic carcinoma was longer than that in adjacent pancreatic tissue (p < 0.05). IMAX was positively correlated with microvascular density (r = 0.577, p < 0.05). We concluded that CEUS manifestations could reflect the histologic changes of pancreatic carcinomas and CEUS can be used to evaluate blood perfusion of tumors, as IMAX is positively correlated with microvascular density.

Autoimmune Pancreatitis: An Update on Diagnosis and Management

There is an evolving understanding that autoimmune pancreatitis (AIP) is an immunoglobulin (Ig) G4 systemic disease. It can manifest as primarily a pancreatic disorder or in association with other disorders of presumed autoimmune cause. Classic clinical characteristics include obstructive jaundice, abdominal pain, and acute pancreatitis. Thus, AIP can be difficult to distinguish from pancreatic malignancy. However, AIP may respond to therapy with corticosteroids, and has a strong association with other immune mediated diseases. Although primarily a pathologic diagnosis, attempts have been made to reliably diagnose AIP clinically. AIP can be classified as either type 1 or type 2.