Use of diffusion-weighted MRI to differentiate chronic pancreatitis from pancreatic cancer. AJR Am J Roentgenol. 2013;201:1002-1008. [PMID: 24147470 DOI: 10.2214/ajr.12.10170]

Using machine learning to identify risk factors for pancreatic cancer: a retrospective cohort study of real-world data

Objectives

This study aimed to identify the risk factors for pancreatic cancer through machine learning.

Methods

We investigated the relationships between different risk factors and pancreatic cancer using a real-world retrospective cohort study conducted at West China Hospital of Sichuan University. Multivariable logistic regression, with pancreatic cancer as the outcome, was used to identify covariates associated with pancreatic cancer. The machine learning model extreme gradient boosting (XGBoost) was adopted as the final model for its high performance. Shapley additive explanations (SHAPs) were utilized to visualize the relationships between these potential risk factors and pancreatic cancer.

Results

The cohort included 1,982 patients. The median ages for pancreatic cancer and nonpancreatic cancer groups were 58.1 years (IQR: 51.3-64.4) and 57.5 years (IQR: 49.5-64.9), respectively. Multivariable logistic regression indicated that kirsten rats arcomaviral oncogene homolog (KRAS) gene mutation, hyperlipidaemia, pancreatitis, and pancreatic cysts are significantly correlated with an increased risk of pancreatic cancer. The five most highly ranked features in the XGBoost model were KRAS gene mutation status, age, alcohol consumption status, pancreatitis status, and hyperlipidaemia status.

Conclusion

Machine learning algorithms confirmed that KRAS gene mutation, hyperlipidaemia, and pancreatitis are potential risk factors for pancreatic cancer. Additionally, the coexistence of KRAS gene mutation and pancreatitis, as well as KRAS gene mutation and pancreatic cysts, is associated with an increased risk of pancreatic cancer. Our findings offered valuable implications for public health strategies targeting the prevention and early detection of pancreatic cancer.

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.

Multiparametric detection and outcome prediction of pancreatic cancer involving dual-energy CT, diffusion-weighted MRI, and radiomics

BACKGROUND

The advent of next-generation computed tomography (CT)- and magnetic resonance imaging (MRI) opened many new perspectives in the evaluation of tumor characteristics. An increasing body of evidence suggests the incorporation of quantitative imaging biomarkers into clinical decision-making to provide mineable tissue information. The present study sought to evaluate the diagnostic and predictive value of a multiparametric approach involving radiomics texture analysis, dual-energy CT-derived iodine concentration (DECT-IC), and diffusion-weighted MRI (DWI) in participants with histologically proven pancreatic cancer.

METHODS

In this study, a total of 143 participants (63 years ± 13, 48 females) who underwent third-generation dual-source DECT and DWI between November 2014 and October 2022 were included. Among these, 83 received a final diagnosis of pancreatic cancer, 20 had pancreatitis, and 40 had no evidence of pancreatic pathologies. Data comparisons were performed using chi-square statistic tests, one-way ANOVA, or two-tailed Student's t-test. For the assessment of the association of texture features with overall survival, receiver operating characteristics analysis and Cox regression tests were used.

RESULTS

Malignant pancreatic tissue differed significantly from normal or inflamed tissue regarding radiomics features (overall P < .001, respectively) and iodine uptake (overall P < .001, respectively). The performance for the distinction of malignant from normal or inflamed pancreatic tissue ranged between an AUC of ≥ 0.995 (95% CI, 0.955-1.0; P < .001) for radiomics features, ≥ 0.852 (95% CI, 0.767-0.914; P < .001) for DECT-IC, and ≥ 0.690 (95% CI, 0.587-0.780; P = .01) for DWI, respectively. During a follow-up of 14 ± 12 months (range, 10-44 months), the multiparametric approach showed a moderate prognostic power to predict all-cause mortality (c-index = 0.778 [95% CI, 0.697-0.864], P = .01).

CONCLUSIONS

Our reported multiparametric approach allowed for accurate discrimination of pancreatic cancer and revealed great potential to provide independent prognostic information on all-cause mortality.

Histogram array and convolutional neural network of DWI for differentiating pancreatic ductal adenocarcinomas from solid pseudopapillary neoplasms and neuroendocrine neoplasms

PURPOSE

This study aimed to investigate the diagnostic performance of the histogram array and convolutional neural network (CNN) based on diffusion-weighted imaging (DWI) with multiple b-values under magnetic resonance imaging (MRI) to distinguish pancreatic ductal adenocarcinomas (PDACs) from solid pseudopapillary neoplasms (SPNs) and pancreatic neuroendocrine neoplasms (PNENs).

METHODS

This retrospective study consisted of patients diagnosed with PDACs (n = 132), PNENs (n = 45) and SPNs (n = 54). All patients underwent 3.0-T MRI including DWI with 10 b values. The regions of interest (ROIs) of pancreatic tumor were manually drawn using ITK-SNAP software, which included entire tumor at DWI (b = 1500 s/m²). The histogram array was obtained through the ROIs from multiple b-value data. PyTorch (version 1.11) was used to construct a CNN classifier to categorize the histogram array into PDACs, PNENs or SPNs.

RESULTS

The area under the curves (AUCs) of the histogram array and the CNN model for differentiating PDACs from PNENs and SPNs were 0.896, 0.846, and 0.839 in the training, validation and testing cohorts, respectively. The accuracy, sensitivity and specificity were 90.22%, 96.23%, and 82.05% in the training cohort, 84.78%, 96.15%, and 70.0% in the validation cohort, and 81.72%, 90.57%, and 70.0% in the testing cohort. The performance of CNN with AUC of 0.865 for this differentiation was significantly higher than that of f with AUC = 0.755 (P = 0.0057) and α with AUC = 0.776 (P = 0.0278) in all patients.

CONCLUSION

The histogram array and CNN based on DWI data with multiple b-values using MRI provided an accurate diagnostic performance to differentiate PDACs from PNENs and SPNs.

Two nomograms for differentiating mass-forming chronic pancreatitis from pancreatic ductal adenocarcinoma in patients with chronic pancreatitis

OBJECTIVES

To develop and validate a CT nomogram and a radiomics nomogram to differentiate mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) in patients with chronic pancreatitis (CP).

METHODS

In this retrospective study, the data of 138 patients with histopathologically diagnosed MFCP or PDAC treated at our institution were retrospectively analyzed. Two radiologists analyzed the original cross-sectional CT images based on predefined criteria. Image segmentation, feature extraction, and feature reduction and selection were used to create the radiomics model. The CT and radiomics models were developed using data from a training cohort of 103 consecutive patients. The models were validated in 35 consecutive patients. Multivariable logistic regression analysis was conducted to develop a model for the differential diagnosis of MFCP and PDAC and visualized as a nomogram. The nomograms' performances were determined based on their differentiating ability and clinical utility.

RESULTS

The mean age of patients was 53.7 years, 75.4% were male. The CT nomogram showed good differentiation between the two entities in the training (area under the curve [AUC], 0.87) and validation (AUC, 0.94) cohorts. The radiomics nomogram showed good differentiation in the training (AUC, 0.91) and validation (AUC, 0.93) cohorts. Decision curve analysis showed that patients could benefit from the CT and radiomics nomograms, if the threshold probability was 0.05-0.85 and > 0.05, respectively.

CONCLUSIONS

The two nomograms reasonably accurately differentiated MFCP from PDAC in patients with CP and hold potential for refining the management of pancreatic masses in CP patients.

KEY POINTS

• A CT nomogram and a computed tomography-based radiomics nomogram reasonably accurately differentiated mass-forming chronic pancreatitis from pancreatic ductal adenocarcinoma in patients with chronic pancreatitis (CP). • The two nomograms can monitor the cancer risk in patients with CP and hold promise to optimize the management of pancreatic masses in patients with CP.

Pancreatic Incidentaloma

Pancreatic incidentalomas (PIs) represent a clinical entity increasingly recognized due to advances in and easier access to imaging techniques. By definition, PIs should be detected during abdominal imaging performed for indications other than a pancreatic disease. They range from small cysts to invasive cancer. The incidental diagnosis of pancreatic cancer can contribute to early diagnosis and treatment. On the other hand, inadequate management of PIs may result in overtreatment and unneeded morbidity. Therefore, there is a strong need to evaluate the nature and clinical features of individual PIs. In this review, we summarize the major characteristics related to PIs and present suggestions for their management.

Predicting Factors for Pancreatic Malignancy with Computed Tomography and Endoscopic Ultrasonography in Chronic Pancreatitis

Diagnosing pancreatic malignancy is challenging, especially in patients with chronic pancreatitis (CP). Endoscopic ultrasonography (EUS) is a promising diagnostic procedure for discriminating between malignancy and CP. We aimed to investigate the predictive factors and reliability of computed tomography (CT) and EUS for differentiating pancreatic mass lesions and the diagnostic accuracy of EUS-FNA or FNB in patients with CP. Forty patients with CP, receiving CT and EUS-FNA or FNB for pancreatic mass lesion evaluation, were enrolled in the study. Patients’ data, CT and EUS characteristics, image-based diagnosis, cytopathology, and final diagnosis were recorded. EUS was superior to CT in terms of diagnostic accuracy (92.5% vs. 82.5%, p = 0.02). Both CT and EUS showed significant predictive factors (all p < 0.05) with the tumor image hypoattenuation pattern or vessel invasion on CT and pancreatic duct dilatation, or distal pancreatic atrophy on EUS. EUS imaging is a reliable modality for evaluating pancreatic lesions, even with a CP background. The EUS image has a higher diagnostic accuracy than CT. Predicting factors, including hypoechoic pattern, pancreatic duct dilatation, and distal pancreas atrophy, may help to differentiate benign or malignant in patients with CP.

Development and validation of a novel model incorporating MRI-based radiomics signature with clinical biomarkers for distinguishing pancreatic carcinoma from mass-forming chronic pancreatitis

PURPOSE

It is difficult to make a clear differential diagnosis of pancreatic carcinoma (PC) and mass-forming chronic pancreatitis (MFCP) via conventional examinations. We aimed to develop a novel model incorporating an MRI-based radiomics signature with clinical biomarkers for distinguishing the two lesions.

METHODS

A total of 102 patients were retrospectively enrolled and randomly divided into the training and validation cohorts. Radiomics features were extracted from four different sequences. Individual imaging modality radiomics signature, multiparametric MRI (mp-MRI) radiomics signature, and a final mixed model based on mp-MRI and clinically independent risk factors were established to discriminate between PC and MFCP. The diagnostic performance of each model and model discrimination were assessed in both the training and validation cohorts.

RESULTS

ADC had the best predictive performance among the four individual radiomics models, but there were no significant differences between the pairs of models (all p > 0.05). Six potential radiomics features were finally selected from the 960 texture features to formulate the radiomics score (rad-score) of the mp-MRI model. In addition, the boxplot results of the distributions of rad-scores identified the rad-score as an independent predictive factor for the differentiation of PC and MFCP (p< 0.001). Notably, the nomogram integrating rad-score and clinically independent risk factors had a better diagnostic performance than the mp-MRI and clinical models. These results were further confirmed by the validation group.

CONCLUSION

The mixed model was developed and preliminarily validated to distinguish PC from MFCP, which may benefit the formulation of treatment strategies and nonsurgical procedures.

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

Accuracy of quantitative diffusion-weighted imaging for differentiating benign and malignant pancreatic lesions: a systematic review and meta-analysis

BACKGROUND

A variety of imaging techniques can be used to evaluate diffusion characteristics to differentiate malignant and benign pancreatic lesions. The diagnostic performance of diffusion parameters has not been systematic assessed.

PURPOSE

We aimed to investigate the diagnostic efficacy of quantitative diffusion-weighted imaging (DWI) for pancreatic lesions.

METHODS

A literature search was conducted using the PubMed, Embase, and Cochrane Library databases for studies from inception to March 30, 2020, which involves the quantitative diagnostic performance of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in the pancreas. Studies were reviewed according to inclusion and exclusion criteria. The quality of articles was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUATAS-2). A bivariate random-effects model was used to evaluate pooled sensitivities and specificities. Univariable meta-regression analysis was used to test the effects of factors that contributed to the heterogeneity.

RESULTS

A total of 31 studies involving 1558 patients were ultimately eligible for data extraction. The lowest heterogeneity was found in specificity of perfusion fraction (f) with the I2 value was 17.97% and Cochran p value was 0.28. However, high heterogeneities were found for the other parameters (all I2 > 50%). There was no publication bias found in funnel plot (p = 0.30) for the apparent diffusion coefficient (ADC) parameter. The pooled sensitivities for ADC, f, pure diffusion coefficient (D), and pseudo diffusivity coefficient (D*) were 83%, 81%, 76%, and 84%, respectively. The pooled specificities for ADC, f, D, and D* were 87%, 83%, 69%, and 81% respectively. The areas under the curves for ADC, f, D, and D* were 0.92, 0.87, 0.79, and 0.87 respectively.

CONCLUSION

Quantitative DWI and IVIM have a good diagnostic performance for differentiating malignant and benign pancreatic lesions.

KEY POINTS

• IVIM has high sensitivity and specificity (84% and 83%, respectively) for differential diagnosis of pancreatic lesions, which is comparable to that of the ADC (83% and 87%, respectively). • The ADC has an excellent diagnostic performance for differentiating malignant from benign IPMNs (sensitivity, 0.83; specificity, 0.92); the f has the best diagnostic performance for differentiating pancreatic carcinoma from PNET (sensitivity, 0.85; specificity, 0.85). • For the ADC, using a maximal b value < 800 s/mm2 has a higher diagnostic accuracy than ≥ 800 s/mm2; performing in a high field strength (3.0 T) system has a higher diagnostic accuracy than a low field strength (1.5 T) for pancreatic lesions.

Deuterium MRSI characterizations of glucose metabolism in orthotopic pancreatic cancer mouse models

Detecting and mapping metabolism in tissues represents a major step in detecting, characterizing, treating and understanding cancers. Recently introduced deuterium metabolic imaging techniques could offer a noninvasive route for the metabolic imaging of animals and humans, based on using ² H magnetic resonance spectroscopic imaging (MRSI) to detect the uptake of deuterated glucose and the fate of its metabolic products. In this study, ² H_6,6' -glucose was administered to mice cohorts that had been orthotopically implanted with two different models of pancreatic ductal adenocarcinoma (PDAC), involving PAN-02 and KPC cell lines. As the tumors grew, ² H_6,6' -glucose was administered as bolii into the animals' tail veins, and ² H MRSI images were recorded at 15.2 T. 2D phase-encoded chemical shift imaging experiments could detect a signal from this deuterated glucose immediately after the bolus injection for both the PDAC models, reaching a maximum in the animals' tumors ~ 20 min following administration, and nearly total decay after ~ 40 min. The main metabolic reporter of the cancers was the ² H_3,3' -lactate signal, which MRSI could detect and localize on the tumors when these were 5 mm or more in diameter. Lactate production time traces varied slightly with the animal and tumor model, but in general lactate peaked at times of 60 min or longer following injection, reaching concentrations that were ~ 10-fold lower than those of the initial glucose injection. This ² H_3,3' -lactate signal was only visible inside the tumors. ² H-water could also be detected as deuterated glucose's metabolic product, increasing throughout the entire time course of the experiment from its ≈10 mM natural abundance background. This water resonance could be imaged throughout the entire abdomen of the animals, including an enhanced presence in the tumor, but also in other organs like the kidney and bladder. These results suggest that deuterium MRSI may serve as a robust, minimally invasive tool for the monitoring of metabolic activity in pancreatic tumors, capable of undergoing clinical translation and supporting decisions concerning treatment strategies. Comparisons with in vivo metabolic MRI experiments that have been carried out in other animal models are presented and their differences/similarities are discussed.

Characterization and correction of cardiovascular motion artifacts in diffusion-weighted imaging of the pancreas

PURPOSE

To assess the effects of cardiovascular-induced motion on conventional DWI of the pancreas and to evaluate motion-robust DWI methods in a motion phantom and healthy volunteers.

METHODS

3T DWI was acquired using standard monopolar and motion-compensated gradient waveforms, including in an anatomically accurate pancreas phantom with controllable compressive motion and healthy volunteers (n = 8, 10). In volunteers, highly controlled single-slice DWI using breath-holding and cardiac gating and whole-pancreas respiratory-triggered DWI were acquired. For each acquisition, the ADC variability across volunteers, as well as ADC differences across parts of the pancreas were evaluated.

RESULTS

In motion phantom scans, conventional DWI led to biased ADC, whereas motion-compensated waveforms produced consistent ADC. In the breath-held, cardiac-triggered study, conventional DWI led to heterogeneous DW signals and highly variable ADC across the pancreas, whereas motion-compensated DWI avoided these artifacts. In the respiratory-triggered study, conventional DWI produced heterogeneous ADC across the pancreas (head: 1756 ± 173 × 10^-6 mm² /s; body: 1530 ± 338 × 10^-6 mm² /s; tail: 1388 ± 267 × 10^-6 mm² /s), with ADCs in the head significantly higher than in the tail (P < .05). Motion-compensated ADC had lower variability across volunteers (head: 1277 ± 102 × 10^-6 mm² /s; body: 1204 ± 169 × 10^-6 mm² /s; tail: 1235 ± 178 × 10^-6 mm² /s), with no significant difference (P ≥ .19) across the pancreas.

CONCLUSION

Cardiovascular motion introduces artifacts and ADC bias in pancreas DWI, which are addressed by motion-robust DWI.

Swedish national guidelines for chronic pancreatitis

Chronic pancreatitis (CP) should be suspected in the case of recurrent upper abdominal pain of unknown origin and/or clinical signs of exocrine pancreatic insufficiency (EPI). Alcohol is the most common etiological factor associated with CP, others being smoking, male gender, and hereditary forms. CP is often associated with recurrent episodes of acute exacerbations.As of today, there is no accepted clinical definition of CP. However, irreversible morphological changes within the pancreas often occur, including dilatation of the main and branch pancreatic ducts, calcifications in ducts and parenchyma, parenchymal atrophy, and development of pseudocysts, though less so in the early phase of CP.

Radiomics Model Based on MR Images to Discriminate Pancreatic Ductal Adenocarcinoma and Mass-Forming Chronic Pancreatitis Lesions

BACKGROUND

It is difficult to identify pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP) lesions through conventional CT or MR examination. As an innovative image analysis method, radiomics may possess potential clinical value in identifying PDAC and MFCP. To develop and validate radiomics models derived from multiparametric MRI to distinguish pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP) lesions.

METHODS

This retrospective study included 119 patients from two independent institutions. Patients from one institution were used as the training cohort (51 patients with PDAC and 13 patients with MFCP), and patients from the other institution were used as the testing cohort (45 patients with PDAC and 10 patients with MFCP). All the patients had pathologically confirmed results, and preoperative MRI was performed. Four feature sets were extracted from T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and the artery (A) and portal (P) phases of dynamic contrast-enhanced MRI, and the corresponding radiomics models were established. Several clinical characteristics were used to discriminate PDAC and MFCP lesions, and clinical model was established. The results of radiologists' evaluation were compared with pathology and radiomics models. Univariate analysis and the least absolute shrinkage and selection operator algorithm were performed for feature selection, and a support vector machine was used for classification. The receiver operating characteristic (ROC) curve was applied to assess the model discrimination.

RESULTS

The areas under the ROC curves (AUCs) for the T1WI, T2WI, A and, P and clinical models were 0.893, 0.911, 0.958, 0.997 and 0.516 in the primary cohort, and 0.882, 0.902, 0.920, 0.962 and 0.649 in the validation cohort, respectively. All radiomics models performed better than clinical model and radiologists' evaluation both in the training and testing cohorts by comparing the AUC of various models, all P<0.050. Good calibration was achieved.

CONCLUSIONS

The radiomics models based on multiparametric MRI have the potential ability to classify PDAC and MFCP lesions.

Diagnostic performance of diffusion MRI for pancreatic ductal adenocarcinoma characterisation: A meta-analysis

PURPOSE

To assess the diagnostic performance of intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) for characterising pancreatic ductal adenocarcinoma (PDAC).

METHOD

A literature search was performed through PubMed, Web of Science, the Cochrane Library, and Embase databases. The search date was updated to extend until 28 October 2020, with no starting time limitation. The pooled sensitivity and specificity were calculated using a bivariate random effects model. Summary receiver operating characteristic curves were constructed, and area under the curve (AUC) of each diffusion parameter was calculated. Subgroup and meta-regression analyses were performed to assess for heterogeneity. Study quality was assessed.

RESULTS

Twenty-nine studies involving 1579 participants were included, of which 26 evaluated the apparent diffusion coefficient (ADC) and eight evaluated IVIM, with five evaluating both ADC and IVIM. Pooled sensitivity and specificity of ADC were 83 % (95 % CI, 76 %-88 %, I² = 86 %) and 85 % (95 % CI, 79 %-90 %, I² = 77 %), respectively, and AUC was 0.91 (95 % CI, 0.88-0.93). The perfusion fraction had the highest diagnostic accuracy in the IVIM model; the pooled sensitivity, specificity, and AUC were 87 % (95 % CI, 81 %-92 %, I² = 45 %), 88 % (95 % CI, 77 %-94 %, I² = 57 %), and 0.93 (95 % CI, 0.91-0.95), respectively. The pooled sensitivity, specificity and AUC for the tissue diffusion coefficient were 74 % (95 % CI, 55 %-87 %, I² = 87 %), 69 % (95 % CI, 52 %-82 %, I² = 73 %), and 0.77 (95 % CI, 0.73-0.81), respectively. And the pooled sensitivity, specificity, and AUC for the pseudodiffusion coefficient were 89 % (95 % CI, 77 %-96 %, I² = 79 %), 74 % (95 % CI, 60 %-84 %, I² = 78 %), and 0.88(95 %CI,0.85-0.91), respectively. Meta-regression analyses revealed that study design (specificity, P＜0.01), region-of-interest delineation (sensitivity, P = 0.02;specificity, P = 0.03), field strength (sensitivity, P＜0.01), and thickness (sensitivity, P＜0.01; specificity, P = 0.01) were sources of ADC heterogeneity.

CONCLUSIONS

DWI and IVIM have comparable diagnostic power and good diagnostic performance for characterising PDAC.

Identification of variable stages in murine pancreatic tumors by a multiparametric approach employing hyperpolarized 13 C MRSI, 1 H diffusivity and 1 H T1 MRI

This study explored the usefulness of multiple quantitative MRI approaches to detect pancreatic ductal adenocarcinomas in two murine models, PAN-02 and KPC. Methods assayed included 1 H T1 and T2 measurements, quantitative diffusivity mapping, magnetization transfer (MT) 1 H MRI throughout the abdomen and hyperpolarized 13 C spectroscopic imaging. The progress of the disease was followed as a function of its development; studies were also conducted for wildtype control mice and for mice with induced mild acute pancreatitis. Customized methods developed for scanning the motion- and artifact-prone mice abdomens allowed us to obtain quality 1 H images for these targeted regions. Contrasts between tumors and surrounding tissues, however, were significantly different. Anatomical images, T2 maps and MT did not yield significant contrast unless tumors were large. By contrast, tumors showed statistically lower diffusivities than their surroundings (≈8.3 ± 0.4 x 10-4 for PAN-02 and ≈10.2 ± 0.6 x 10-4 for KPC vs 13 ± 1 x 10-3 mm2 s-1 for surroundings), longer T1 relaxation times (≈1.44 ± 0.05 for PAN-02 and ≈1.45 ± 0.05 for KPC vs 0.95 ± 0.10 seconds for surroundings) and significantly higher lactate/pyruvate ratios by hyperpolarized 13 C MR (0.53 ± 0.2 for PAN-02 and 0.78 ± 0.2 for KPC vs 0.11 ± 0.04 for control and 0.31 ± 0.04 for pancreatitis-bearing mice). Although the latter could also distinguish early-stage tumors from healthy animal controls, their response was similar to that in our pancreatitis model. Still, this ambiguity could be lifted using the 1 H-based reporters. If confirmed for other kinds of pancreatic tumors this means that these approaches, combined, can provide a route to an early detection of pancreatic cancer.

Pancreas Solid Tumors

Solid tumors of the pancreas encompass a variety of diagnoses with treatments ranging from observation to major abdominal surgery. Pancreatic ductal adenocarcinoma remains one of the most common and most lethal of these differential of diagnoses and requires a multimodality approach through a multidisciplinary team of specialists. This article reviews the classification, clinical presentation, and workup in differentiating solid tumors of the pancreas and serves as an additional tool for general surgeons faced with such a clinical finding, from a surgical oncology perspective.

Differential diagnosis of solid pancreatic masses

Solid pancreatic lesions include mainly adenocarcinoma, neuroendocrine tumors pancreatic cystic neoplasms with solid component, solid pseudopapillary tumor, pancreatoblastoma, pancreatic lymphoma, and pancreatic metastasis. The most frequent pancreatic lesion is the adenocarcinoma, representing between 70% and 95% of all solid pancreatic neoplasm. The diagnosis of these lesions can be a challenge and currently, there are different imaging techniques such as CT scan, EUS and MRI with high sensitivity and specificity. The most widely used technique for the initial evaluation is the CT scan with a sensitivity between 76% and 92% for the diagnosis of pancreatic cancer. The EUS has a sensitivity for the detection of pancreatic lesions of around 98% and is accepted to be the most sensitive technique for the detection of small pancreatic tumors (<2 cm). The MRI, with a very high soft-tissue contrast resolution, provides an accuracy in the detection and staging of adenocarcinoma of 90-100%. A multimodality approach is usually necessary in patients with clinical suspicion of pancreatic lesion. The EUS is required for the local evaluation of the relation of the lesion with vessels and for tissue acquisition and the CT scan and/or MRI is usually required for the local and distance staging in case of pancreatic cancer. The purpose of this review is to provide an overview of solid pancreatic lesions and the role of the different imaging techniques in their evaluation.

CT and MR features that can help to differentiate between focal chronic pancreatitis and pancreatic cancer

Diagnosis of a focal pancreatic mass in routine clinical practice can be a challenge because patients with chronic pancreatitis may present with symptoms and imaging findings that can be difficult to distinguish from pancreatic cancer. Markers, such as cancer antigen 19-9 and carcinoembryonic antigen, are helpful if abnormal, but normal values do not rule out pancreatic cancer. One of the strongest complicating factors is that chronic pancreatitis is a risk factor for pancreatic cancer. Transition of chronic pancreatitis to pancreatic cancer is relatively rare, but it normally has a poor prognosis because diagnosis is often delayed. From a radiologic diagnosis perspective, the classic so-called double-duct sign is helpful. This sign is considered a hallmark sign of pancreatic cancer on magnetic resonance cholangiopancreatography, but it can also be identified in patients with chronic pancreatitis or with other conditions. A number of additional imaging findings or signs are, therefore, necessary. The aim of this article was to describe the strong CT and MR imaging features or integrated imaging features that can help to differentiate between pancreatic cancer and focal chronic pancreatitis.

Evaluation of Texture Analysis for the Differential Diagnosis of Mass-Forming Pancreatitis From Pancreatic Ductal Adenocarcinoma on Contrast-Enhanced CT Images

Purpose: To investigate the potential of computed tomography (CT) imaging features and texture analysis to differentiate between mass-forming pancreatitis (MFP) and pancreatic ductal adenocarcinoma (PDAC). Materials and Methods: Thirty patients with pathologically proved MFP and 79 patients with PDAC were included in this study. Clinical data and CT imaging features of the two lesions were evaluated. Texture features were extracted from arterial and portal phase CT images using commercially available software (AnalysisKit). Multivariate logistic regression analyses were used to identify relevant CT imaging and texture parameters to discriminate MFP from PDAC. Receiver operating characteristic curves were performed to determine the diagnostic performance of predictions. Results: MFP showed a larger size compared to PDAC (p = 0.009). Cystic degeneration, pancreatic ductal dilatation, vascular invasion, and pancreatic sinistral portal hypertension were more frequent and duct penetrating sign was less frequent in PDAC compared to MFP. Arterial CT attenuation, arterial, and portal enhancement ratios of MFP were higher than PDAC (p < 0.05). In multivariate analysis, arterial CT attenuation and pancreatic duct penetrating sign were independent predictors. Texture features in arterial phase including SurfaceArea, Percentile40, InverseDifferenceMoment_angle90_offset4, LongRunEmphasis_angle45_offset4, and uniformity were independent predictors. Texture features in portal phase including LongRunEmphasis_angle135_offset7, VoxelValueSum, LongRunEmphasis_angle135_offset4, and GLCMEntropy_angle45_offset1 were independent predictors. Areas under the curve of imaging feature-based, texture feature-based in arterial and portal phases, and the combined models were 0.84, 0.96, 0.93, and 0.98, respectively. Conclusions: CT texture analysis demonstrates great potential to differentiate MFP from PDAC.

Imaging of Tropical Chronic Pancreatitis—A Unique Clinico-Radiological Entity

Tropical chronic pancreatitis (TCP) is a unique juvenile nonalcoholic form of chronic pancreatitis prevalent in tropical developing countries. TCP is characterized by the younger age of onset, rapid progression, higher prevalence of diabetes and pancreatic calculi, and greater propensity to develop pancreatic malignancy. Identifying the distinct imaging features is critical for the diagnosis of TCP. Awareness of this condition will not only enable the radiologist to recognize it early but also help in better management. In this article, we review the etiopathogenesis, distinct imaging features, and complications of TCP.

Diffusion-weighted magnetic resonance imaging in the pancreas of fulminant type 1 diabetes

Abrupt disease onset and severe metabolic disorders are main characteristics of fulminant type 1 diabetes. Diffusion-weighted magnetic resonance imaging (DWI) is an imaging technique that reflects restricted diffusion in organs and can detect mononuclear cell infiltration into the pancreas at the onset of the disease. Fourteen patients with fulminant type 1 diabetes who underwent abdominal magnetic resonance imaging were recruited for the measurement of apparent diffusion coefficient (ADC) values of the pancreas that were compared with those of 21 non-diabetic controls. The ADC values of all parts of the pancreas were significantly lower in fulminant type 1 diabetes than in controls (head, 1.424 ± 0.382 × 10^-3 vs. 1.675 ± 0.227 × 10^-3 mm²/s; body, 1.399 ± 0.317 × 10^-3 vs. 1.667 ± 0.170 × 10^-3 mm²/s; tail, 1.336 ± 0.247 × 10^-3 vs. 1.561 ± 0.191 × 10^-3 mm²/s; mean, 1.386 ± 0.309 × 10^-3 vs. 1.634 ± 0.175 × 10^-3 mm²/s) (p < 0.01). The best cut-off value indicated that the sensitivity was 86% and the specificity was 71% when using DWI, which was also efficient in two atypical patients with fulminant type 1 diabetes without elevated levels of exocrine pancreatic enzymes or with high HbA1c levels due to the preexistence of type 2 diabetes. The ADC values were significantly correlated to plasma glucose levels and arterial pH, and tended to increase with the lapse of time. DWI may be an additional tool for making an efficient diagnosis of fulminant type 1 diabetes.

Comparison of Navigator Triggering Reduced Field of View and Large Field of View Diffusion-Weighted Imaging of the Pancreas

RATIONALE AND OBJECTIVES

The purpose of this study is to compare image quality, presence and grade of artifacts, signal-to-noise ratio, and apparent diffusion coefficient (ADC) values in pancreatic tissue between high-resolution navigator-triggered (NT) restricted field of view (rFOV) FOCUS single-shot (SS) echo-planar imaging (EPI) diffusion-weighted imaging (DWI) and NT large FOV SS-EPI DWI.

MATERIALS AND METHODS

Magnetic resonance imaging examinations were performed with GE 3-T systems using a 32-channel body array coil. Seventeen consecutive patients were imaged. A 5-point scale semiquantitative grading system was used to evaluate image quality and general artifacts. Signal-to-noise ratio and ADC were measured in the head, body, and tail of the pancreas. Statistical analysis was performed using Student t test and Wilcoxon signed rank test, with differences considered significant for P value less than 0.05.

RESULTS

More artifacts were present on large FOV compared with rFOV FOCUS SS-EPI DW images (P < 0.01). Restricted field of view image quality was subjectively better (P < 0.01). No difference in the signal-to-noise ratio was demonstrated between the 2 image datasets. Apparent diffusion coefficient values were significantly lower (P < 0.01) when calculated from rFOV images than large FOV images.

CONCLUSIONS

Our results demonstrate better image quality and reduced artifacts in rFOV images compared with large FOV DWI. Measurements from ADC maps derived from rFOV DWI show significantly lower ADC values when compared with ADC maps derived from large FOV DWI.

PET/MR Imaging of the Pancreas

PET/MR imaging has the potential to markedly alter pancreatic care in both the malignant, and premalignant states with the ability to perform robust, high-resolution, quantitative molecular imaging. The ability of PET/MR imaging to monitor disease processes, potentially correct for motion in the upper abdomen, and provide novel biomarkers that may be a combination of MR imaging and PET biomarkers, offers a unique, precise interrogation of the pancreatic milieu going forward.

Diagnosis and Detection of Pancreatic Cancer

Computed tomography is the first-line imaging modality for suspected pancreatic cancer. Magnetic resonance cholangiopancreatography is a second-line modality for suspected pancreatic cancer and is usually reserved for equivocal cases. Both computed tomography and MR are highly sensitive in the detection of pancreatic cancer, with up to 96% and 93.5% sensitivity, respectively. Computed tomography is superior to MR in the assessment of tumor resectability, with accuracy rates of up to 86.8% and 78.9%, respectively. Close attention to secondary signs of pancreatic cancer, such as pancreatic duct dilatation, abrupt pancreatic duct caliber change, and parenchymal atrophy, are critical in the diagnosis of pancreatic cancer. Emerging techniques such as radiomics and molecular imaging have the potential of identifying malignant precursors and lead to earlier disease diagnosis. The results of these promising techniques need to be validated in larger clinical studies.

Differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma using magnetic resonance imaging: The value of contrast-enhanced and diffusion weighted imaging

Pancreatic neuroendocrine carcinoma (PNEC) is often misdiagnosed as pancreatic ductal adenocarcinoma (PDAC). This retrospective study differentiated PNEC from PDAC using magnetic resonance imaging (MRI), including contrast-enhanced (CE) and diffusion-weighted imaging (DWI). Clinical data and MRI findings, including the T1/T2 signal, tumor boundary, size, enhancement degree, and apparent diffusion coefficient (ADC), were compared between 37 PDACs and 13 PNECs. Boundaries were more poorly defined in PDAC than PNEC (97.3% vs. 61.5%, p<0.01). Hyper-/isointensity was more common in PNEC than PDAC at the arterial (38.5% vs. 0.0), portal (46.2% vs. 2.7%) and delayed phases (46.2% vs. 5.4%) (all p<0.01). Lymph node metastasis (97.3% vs. 61.5%, p<0.01) and local invasion/distant metastasis (86.5% vs. 46.2%, p<0.01) were more common in PDAC than PNEC. Enhancement degree via CE-MRI was higher in PNEC than PDAC at the arterial and portal phases (p<0.01). PNEC ADC values were lower than those of normal pancreatic parenchyma (p<0.01) and PDAC (p<0.01). Arterial and portal phase signal intensity ratios and ADC values showed the largest areas under the receiver operating characteristic curve and good sensitivities (92.1%–97.2%) and specificities (76.9%–92.3%) for differentiating PNEC from PDAC. Thus the enhancement degree at the arterial and portal phases and the ADC values may be useful for differentiating PNEC from PDAC using MRI.

Paraduodenal pancreatitis as a mimicker of pancreatic adenocarcinoma: MRI evaluation

PURPOSE

To evaluate the MRI features of paraduodenal pancreatitis (PDP) and to define useful signs to differentiate PDP from pancreatic ductal adenocarcinoma (PDAC).

MATERIAL AND METHODS

We reviewed the MRI scans of 56 patients, 28 affected by PDP and 28 by PDAC, all pathologically proven. The following parameters were evaluated: signal intensity of the lesion on T1-, T2-WI, DWI (b800) and after contrast medium administration; presence of cysts; dilation of common hepatic duct and main pancreatic duct; focal thickening of the second portion of the duodenum; maximum diameter and volume of the lesion.

RESULTS

Both PDPs and PDACs were more frequently hypointense on T1-WI, iso-hyperintense on T2-WI, hypointense in the pancreatic phase and iso-hypointense in the venous phase (p>0.05); in the delayed phase most PDP were hyperintense (p=0.0031); on DWI 71.4% PDPs were isointense and all PDACs were hyperintense (p=0.0041). Cystic components were present in 85.7% PDPs (p=0.0011); double duct sign was present in 50% PDACs (p=0.0048); focal thickening of the duodenum was depicted in 89.3 PDPs (p=0.0012). PDPs were larger than PDACs (p=0.0003).

CONCLUSION

The most suggestive signs of PDP are: signal hyperintensity in the delayed phase, isointensity on DWI, presence of cysts, focal thickening of the duodenum and large size of the lesion.

Diffusion magnetic resonance imaging: A molecular imaging tool caught between hope, hype and the real world of “personalized oncology”

“Personalized oncology” is a multi-disciplinary science, which requires inputs from various streams for optimal patient management. Humongous progress in the treatment modalities available and the increasing need to provide functional information in addition to the morphological data; has led to leaping progress in the field of imaging. Magnetic resonance imaging has undergone tremendous progress with various newer MR techniques providing vital functional information and is becoming the cornerstone of “radiomics/radiogenomics”. Diffusion-weighted imaging is one such technique which capitalizes on the tendency of water protons to diffuse randomly in a given system. This technique has revolutionized oncological imaging, by giving vital qualitative and quantitative information regarding tumor biology which helps in detection, characterization and post treatment surveillance of the lesions and challenging the notion that “one size fits all”. It has been applied at various sites with different clinical experience. We hereby present a brief review of this novel functional imaging tool, with its application in “personalized oncology”.

Optimized ROI size on ADC measurements of normal pancreas, pancreatic cancer and mass-forming chronic pancreatitis

Objectives

To investigate the effects of region of interest (ROI) sizes on apparent diffusion coefficient (ADC) measurements for the differentiation of normal pancreas (NP), pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP).

Results

There were no significant differences for the mean ADCs measured by 12 different-size ROIs for MFCP, or PDAC and NP (P = 0.858–1.0). With the increase of ROI size (≥ 55 mm²), ADCs of PDAC were significantly lower than those of NP (all P < 0.05), but there was no difference of the accuracy in ADC for differentiating the two groups only at a ROI size of 214 mm². When ROI size was above 99 mm², ADCs of MFCP were significantly lower than those of NP (all P < 0.05). There were no significant differences for any of the mean ADCs measured by 12 different-size ROIs between PDAC and MFCP (P > 0.05).

Materials and Methods

Diffusion-weighted imaging (DWI) was performed on 89 participants: 64 with PDAC, 7 with MFCP, as well as 18 healthy volunteers. ADC maps were created using mono-exponential model. A homemade software was used to measure the mean ADC values of 12 concentric round ROIs (areas: 15, 46, 55, 82, 99, 121, 134, 152, 161, 189, 214, 223, and 245 mm²) for the mass of lesions and the NP tissue.

Conclusions

In ADC measurements, the optimized ROI size is 214 mm² for the differentiation of PDAC and NP; ROI size of ≥ 99 mm² is recommended to differentiate between MFCP and NP. ADC was not useful for the differentiation of PDAC and MFCP.

Perfusion CT - Can it resolve the pancreatic carcinoma versus mass forming chronic pancreatitis conundrum?

OBJECTIVES

To evaluate the utility of perfusion CT (PCT) in differentiating pancreatic adenocarcinoma from mass forming chronic pancreatitis (MFCP).

METHODS

In this ethically approved study, PCT was performed in 122 patients with pancreatic masses of which 42 patients had pancreatic adenocarcinoma and 13 had MFCP on histopathology. Perfusion parameters studied included blood flow (BF), blood volume (BV), permeability surface area product (PS), time to peak (TTP), peak enhancement intensity (PEI) and mean transit time (MTT). Twenty five controls with no pancreatic pathology were also studied.

RESULTS

Amongst the perfusion parameters BF and BV were found to be the most reliable for differentiating between adenocarcinoma and mass forming pancreatitis. Although they were reduced in both pancreatic adenocarcinoma (BF- 16.6 ± 13.1 ml/100 ml/min and BV- 5 ± 3.5 ml/100 ml) and MFCP (BF- 30.4 ± 8.7 ml/100 ml/min and BV- 8.9 ± 3.1 ml/100 ml) as compared to normal controls (BF- 94.1 ± 24 ml/100 ml/min and BV- 36 ± 10.7 ml/100 ml) but the extent of reduction was greater in pancreatic adenocarcinoma than in MFCP. Based on ROC analysis cut off values of 19.1 ml/100 ml/min for BF and 5 ml/100 ml for BV yielded optimal sensitivity and specificity for differentiating pancreatic adenocarcinoma from MFCP.

CONCLUSIONS

PCT may serve as an additional paradigm for differentiating pancreatic adenocarcinoma from mass forming chronic pancreatitis and a useful tool for detecting masses which are isodense on conventional CT.

Surgical approaches to chronic pancreatitis: indications and imaging findings

Chronic pancreatitis (CP) is an irreversible, inflammatory process characterized by progressive fibrosis of the pancreas that can result in abdominal pain, exocrine insufficiency, and diabetes. Inadequate pain relief using medical and/or endoscopic therapies is an indication for surgery. The surgical management of CP is centered around three main operations including pancreaticoduodenectomy (PD), duodenum-preserving pancreatic head resection (DPPHR) and drainage procedures, and total pancreatectomy with islet autotransplantation (TPIAT). PD is the method of choice when there is a high suspicion for malignancy. Combined drainage and resection procedures are associated with pain relief, higher quality of life, and superior short-term and long-term survival in comparison with the PD. TPIAT is a reemerging treatment that may be promising in subjects with intractable pain and impaired quality of life. Imaging examinations have an extensive role in pre-operative and post-operative evaluation of CP patients. Pre-operative advanced imaging examinations including CT and MRI can detect hallmarks of CP such as calcifications, pancreatic duct dilatation, chronic pseudocysts, focal pancreatic enlargement, and biliary ductal dilatation. Post-operative findings may include periportal hepatic edema, pneumobilia, perivascular cuffing and mild pancreatic duct dilation. Imaging can also be useful in the detection of post-operative complications including obstructions, anastomotic leaks, and vascular lesions. Imaging helps identify unique post-operative findings associated with TPIAT and may aid in predicting viability and function of the transplanted islet cells. In this review, we explore surgical indications as well as pre-operative and post-operative imaging findings associated with surgical options that are typically performed for CP patients.

Pancreatic cancer

Pancreatic cancer is a highly lethal disease, for which mortality closely parallels incidence. Most patients with pancreatic cancer remain asymptomatic until the disease reaches an advanced stage. There is no standard programme for screening patients at high risk of pancreatic cancer (eg, those with a family history of pancreatic cancer and chronic pancreatitis). Most pancreatic cancers arise from microscopic non-invasive epithelial proliferations within the pancreatic ducts, referred to as pancreatic intraepithelial neoplasias. There are four major driver genes for pancreatic cancer: KRAS, CDKN2A, TP53, and SMAD4. KRAS mutation and alterations in CDKN2A are early events in pancreatic tumorigenesis. Endoscopic ultrasonography and endoscopic ultrasonography-guided fine-needle aspiration offer high diagnostic ability for pancreatic cancer. Surgical resection is regarded as the only potentially curative treatment, and adjuvant chemotherapy with gemcitabine or S-1, an oral fluoropyrimidine derivative, is given after surgery. FOLFIRINOX (fluorouracil, folinic acid [leucovorin], irinotecan, and oxaliplatin) and gemcitabine plus nanoparticle albumin-bound paclitaxel (nab-paclitaxel) are the treatments of choice for patients who are not surgical candidates but have good performance status.

Diffusion-weighted MR imaging of pancreatic cancer: A comparison of mono-exponential, bi-exponential and non-Gaussian kurtosis models

OBJECTIVES

To compare two Gaussian diffusion-weighted MRI (DWI) models including mono-exponential and bi-exponential, with the non-Gaussian kurtosis model in patients with pancreatic ductal adenocarcinoma.

MATERIALS AND METHODS

After written informed consent, 15 consecutive patients with pancreatic ductal adenocarcinoma underwent free-breathing DWI (1.5T, b-values: 0, 50, 150, 200, 300, 600 and 1000 s/mm²). Mean values of DWI-derived metrics ADC, D, D*, f, K and D_K were calculated from multiple regions of interest in all tumours and non-tumorous parenchyma and compared. Area under the curve was determined for all metrics.

RESULTS

Mean ADC and D_K showed significant differences between tumours and non-tumorous parenchyma (both P < 0.001). Area under the curve for ADC, D, D*, f, K, and D_K were 0.77, 0.52, 0.53, 0.62, 0.42, and 0.84, respectively.

CONCLUSION

ADC and D_K could differentiate tumours from non-tumorous parenchyma with the latter showing a higher diagnostic accuracy. Correction for kurtosis effects has the potential to increase the diagnostic accuracy of DWI in patients with pancreatic ductal adenocarcinoma.

Differentiating Mass-Forming Autoimmune Pancreatitis From Pancreatic Ductal Adenocarcinoma on the Basis of Contrast-Enhanced MRI and DWI Findings

OBJECTIVE

The purpose of this study was to assess value of contrast-enhanced MRI, MRCP, and DWI for differentiating mass-forming autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

This study included 15 patients with mass-forming AIP and 79 with PDAC who underwent gadoxetic acid-enhanced MRI with DWI and MRCP. Two radiologists evaluated the MRI findings in consensus. Statistically significant imaging findings were identified through univariate and multivariate analyses, and their diagnostic performance for predicting mass-forming AIP was analyzed.

RESULTS

In the univariate analysis, multiplicity, similar or high signal intensity on portal phase and 3- and 20-minute delayed phase images, homogeneous enhancement, no peripancreatic fat infiltration, no internal cystic or necrotic portion, capsulelike rim, no upstream pancreatitis, no vascular invasion, and duct penetrating sign were more frequently observed (p < 0.05) in mass-forming AIP. The apparent diffusion coefficient (ADC) value was also significantly lower for mass-forming AIP than for PDAC (0.96 ± 0.14 versus 1.13 ± 0.23 × 10(-3) mm(2)/s; p < 0.001). The optimal cutoff value of ADC for differentiating mass-forming AIP from PDAC was 0.9407 × 10(-3) mm(2)/s. In multivariate analysis, homogeneous enhancement (p = 0.001), duct penetrating sign (p < 0.001), and ADC value less than 0.9407 × 10(-3) mm(2)/s (p < 0.001) were significant for differentiating mass-forming AIP from PDAC. When two of these three criteria were combined, 80% (12/15) of mass-forming AIPs were identified with specificity of 98.7%. When all three criteria were satisfied, specificity was 100%.

CONCLUSION

Contrast-enhanced MRI with MRCP and DWI may be helpful for differentiating mass-forming AIP from PDAC.

Reduced Field-of-View Diffusion-Weighted Magnetic Resonance Imaging of the Pancreas: Comparison with Conventional Single-Shot Echo-Planar Imaging

Objective

To investigate the image quality (IQ) and apparent diffusion coefficient (ADC) of reduced field-of-view (FOV) di-ffusion-weighted imaging (DWI) of pancreas in comparison with full FOV DWI.

Materials and Methods

In this retrospective study, 2 readers independently performed qualitative analysis of full FOV DWI (FOV, 38 × 38 cm; b-value, 0 and 500 s/mm²) and reduced FOV DWI (FOV, 28 × 8.5 cm; b-value, 0 and 400 s/mm²). Both procedures were conducted with a two-dimensional spatially selective radiofrequency excitation pulse, in 102 patients with benign or malignant pancreatic diseases (mean size, 27.5 ± 14.4 mm). The study parameters included 1) anatomic structure visualization, 2) lesion conspicuity, 3) artifacts, 4) IQ score, and 5) subjective clinical utility for confirming or excluding initially considered differential diagnosis on conventional imaging. Another reader performed quantitative ADC measurements of focal pancreatic lesions and parenchyma. Wilcoxon signed-rank test was used to compare qualitative scores and ADCs between DWI sequences. Mann Whitney U-test was used to compare ADCs between the lesions and parenchyma.

Results

On qualitative analysis, reduced FOV DWI showed better anatomic structure visualization (2.76 ± 0.79 at b = 0 s/mm² and 2.81 ± 0.64 at b = 400 s/mm²), lesion conspicuity (3.11 ± 0.99 at b = 0 s/mm² and 3.15 ± 0.79 at b = 400 s/mm²), IQ score (8.51 ± 2.05 at b = 0 s/mm² and 8.79 ± 1.60 at b = 400 s/mm²), and higher clinical utility (3.41 ± 0.64), as compared to full FOV DWI (anatomic structure, 2.18 ± 0.59 at b = 0 s/mm² and 2.56 ± 0.47 at b = 500 s/mm²; lesion conspicuity, 2.55 ± 1.07 at b = 0 s/mm² and 2.89 ± 0.86 at b = 500 s/mm²; IQ score, 7.13 ± 1.83 at b = 0 s/mm² and 8.17 ± 1.31 at b = 500 s/mm²; clinical utility, 3.14 ± 0.70) (p < 0.05). Artifacts were significantly improved on reduced FOV DWI (2.65 ± 0.68) at b = 0 s/mm² (full FOV DWI, 2.41 ± 0.63) (p < 0.001). On quantitative analysis, there were no significant differences between the 2 DWI sequences in ADCs of various pancreatic lesions and parenchyma (p > 0.05). ADCs of adenocarcinomas (1.061 × 10^-3 mm²/s ± 0.133 at reduced FOV and 1.079 × 10^-3 mm²/s ± 0.135 at full FOV) and neuroendocrine tumors (0.983 × 10^-3 mm²/s ± 0.152 at reduced FOV and 1.004 × 10^-3 mm²/s ± 0.153 at full FOV) were significantly lower than those of parenchyma (1.191 × 10^-3 mm²/s ± 0.125 at reduced FOV and 1.218 × 10^-3 mm²/s ± 0.103 at full FOV) (p < 0.05).

Conclusion

Reduced FOV DWI of the pancreas provides better overall IQ including better anatomic detail, lesion conspicuity and subjective clinical utility.

Targeted diagnostic magnetic nanoparticles for medical imaging of pancreatic cancer

Highly aggressive cancer types such as pancreatic cancer possess a mortality rate of up to 80% within the first 6months after diagnosis. To reduce this high mortality rate, more sensitive diagnostic tools allowing an early stage medical imaging of even very small tumours are needed. For this purpose, magnetic, biodegradable nanoparticles prepared using recombinant human serum albumin (rHSA) and incorporated iron oxide (maghemite, γ-Fe2O3) nanoparticles were developed. Galectin-1 has been chosen as target receptor as this protein is upregulated in pancreatic cancer and its precursor lesions but not in healthy pancreatic tissue nor in pancreatitis. Tissue plasminogen activator derived peptides (t-PA-ligands), that have a high affinity to galectin-1 have been chosen as target moieties and were covalently attached onto the nanoparticle surface. Improved targeting and imaging properties were shown in mice using single photon emission computed tomography-computer tomography (SPECT-CT), a handheld gamma camera, and magnetic resonance imaging (MRI).

Differential diagnosis of pancreatic cancer by single-shot echo-planar imaging diffusion-weighted imaging

AIM: To investigate the diagnostic ability of single-shot echo-planar imaging (EPI) diffusion-weighted imaging (DWI) to differentiate between malignant and benign pancreatic lesions.

METHODS: A computerized search was performed on PubMed, MEDLINE and EMBASE up to August 2014. Nine studies (10 sets of data) with a total of 304 malignant pancreatic lesions and 188 benign pancreatic lesions were included. The characteristics of each study included the study name, year of publication, magnetic resonance modalities used, patient population, strength of field, pulse time, repetition time, echo time (TE), maximum b factor, mean age, mean body weight, fat suppression, number of benign and malignant lesions, and true positive, true negative, false positive and false negative results. All analyses were performed using Meta-DiSc and Stata 11.0.

RESULTS: The pooled sensitivity and specificity of single-shot EPI DWI were 0.83 (95%CI: 0.79-0.87) and 0.77 (95%CI: 0.70-0.83), respectively. The positive likelihood ratio and negative likelihood ratio were 5.09 (95%CI: 2.19-11.84) and 0.23 (95%CI: 0.15-0.36), respectively. The P value for the χ² heterogeneity for all pooled estimates was < 0.05. From the fitted summary receiver operating characteristic curve, the area under the curve and Q* index were 0.89 and 0.82, respectively. Publication bias was not present (t = 0.58, P = 0.58). Meta-regression analysis indicated that fat suppression, mean age, TE, and maximum b factor were not sources of heterogeneity (all P > 0.05).

CONCLUSION: Single-shot EPI DWI is useful to differentiate between malignant and benign pancreatic lesions. Lesion size ≥ 2 cm is the limit for the diagnosis of early lesions.

Diffusion-weighted magnetic resonance imaging indicates the severity of acute pancreatitis

PURPOSE

To test the use of diffusion-weighted magnetic resonance imaging (DW-MRI) to differentiate between different degrees of severity of acute pancreatitis (AP).

METHOD

Thirty-six patients who underwent DW-MRI and magnetic resonance cholangiopancreatography were divided into patients with mild AP (mAP, n = 15), patients with necrotizing AP (nAP, n = 8), and patients with a normal pancreas (nP, n = 15; controls). The pancreas was divided into head, body, and tail, and each segment was classified according to image features: pattern 1, normal; pattern 2, mild inflammation; and pattern 3, necrosis. Apparent diffusion coefficients (ADCs) were measured in each segment and correlated with clinical diagnoses.

RESULTS

A total of 108 segments was assessed (three segments per patient). Segments classified as pattern 1 in the nP and mAP groups showed similar ADC values (P = 0.29). ADC values calculated for the pancreatic segments grouped according to the different image patterns (1-3) were significantly different (P < 0.001). Comparisons revealed significant differences in signal intensity between all three patterns (P < 0.05).

CONCLUSIONS

DW-MRI was a compatible and safe image option to differentiate tissue image patterns in patients with mAP, nAP, and nP, mainly in those with contraindications to contrast-enhanced MRI (which is classically required for determining the presence of necrosis) or computed tomography. ADC measures allowed precise differentiation between patterns 1, 2, and 3.

Utility of PET/CT in diagnosis, staging, assessment of resectability and metabolic response of pancreatic cancer

Pancreatic cancer is one of the most common gastrointestinal tumors, with its incidence staying at a high level in both the United States and China. However, the overall 5-year survival rate of pancreatic cancer is still extremely low. Surgery remains the only potential chance for long-term survival. Early diagnosis and precise staging are crucial to make proper clinical decision for surgery candidates. Despite advances in diagnostic technology such as computed tomography (CT) and endoscopic ultrasound, diagnosis, staging and monitoring of the metabolic response remain a challenge for this devastating disease. Positron emission tomography/CT (PET/CT), a relatively novel modality, combines metabolic detection with anatomic information. It has been widely used in oncology and achieves good results in breast cancer, lung cancer and lymphoma. Its utilization in pancreatic cancer has also been widely accepted. However, the value of PET/CT in pancreatic disease is still controversial. Will PET/CT change the treatment strategy for potential surgery candidates? What kind of patients benefits most from this exam? In this review, we focus on the utility of PET/CT in diagnosis, staging, and assessment of resectability of pancreatic cancer. In addition, its ability to monitor metabolic response and recurrence after treatment will be emphasis of discussion. We hope to provide answers to the questions above, which clinicians care most about.

Early detection and prevention of pancreatic cancer: Is it really possible today?

Pancreatic cancer is the 4^th leading cause of cancer-related death in Western countries. Considering the low incidence of pancreatic cancer, population-based screening is not feasible. However, the existence of a group of individuals with an increased risk to develop pancreatic cancer has been well established. In particular, individuals suffering from a somatic or genetic condition associated with an increased relative risk of more than 5- to 10-fold seem to be suitable for enrollment in a surveillance program for prevention or early detection of pancreatic cancer. The aim of such a program is to reduce pancreatic cancer mortality through early or preemptive surgery. Considering the risk associated with pancreatic surgery, the concept of preemptive surgery cannot consist of a prophylactic removal of the pancreas in high-risk healthy individuals, but must instead aim at treating precancerous lesions such as intraductal papillary mucinous neoplasms or pancreatic intraepithelial neoplasms, or early cancer. Currently, results from clinical trials do not convincingly demonstrate the efficacy of this approach in terms of identification of precancerous lesions, nor do they define the outcome of the surgical treatment of these lesions. For this reason, surveillance programs for individuals at risk of pancreatic cancer are thus far generally limited to the setting of a clinical trial. However, the acquisition of a deeper understanding of this complex area, together with the increasing request for screening and treatment by individuals at risk, will usher pancreatologists into a new era of preemptive pancreatic surgery. Along with the growing demand to treat individuals with precancerous lesions, the need for low-risk investigation, low-morbidity operation and a minimally invasive approach becomes increasingly pressing. All of these considerations are reasons for preemptive pancreatic surgery programs to be undertaken in specialized centers only.

Functional MR imaging of the abdomen

In this article, functional magnetic resonance (MR) imaging techniques in the abdomen are discussed. Diffusion-weighted imaging (DWI) increases the confidence in detecting and characterizing focal hepatic lesions. The potential uses of DWI in kidneys, adrenal glands, bowel, and pancreas are outlined. Studies have shown potential use of quantitative dynamic contrast-enhanced MR imaging parameters, such as K(trans), in predicting outcomes in cancer therapy. MR elastography is considered to be a useful tool in staging liver fibrosis. A major issue with all functional MR imaging techniques is the lack of standardization of the protocol.