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Surgical resection is the only potential curative treatment for patients with pancreatic ductal adenocarcinoma (PDAC), but unfortunately most patients recur within 5 years of surgery. This article aims to assess the practice patterns across major academic institutions and develop consensus recommendations for postoperative imaging and interpretation in patients with PDAC.The consensus recommendations for postoperative imaging surveillance following PDAC resection were developed using the Delphi method. Members of the Society of Abdominal Radiology (SAR) PDAC Disease Focused Panel (DFP) underwent three rounds of surveys followed by live webinar group discussions to develop consensus recommendations.Significant variations currently exist in the postoperative surveillance of PDAC, even among academic institutions. Differentiating common postoperative inflammatory and fibrotic changes from tumor recurrence remains a diagnostic challenge, and there is no reliable size threshold or growth rate of imaging findings that can provide differentiation. A new liver lesion or peritoneal nodule should be considered suspicious for tumor recurrence, and the imaging features should be interpreted in the appropriate clinical context (e.g., CA 19-9, clinical presentation, pathologic staging).Postoperative imaging following PDAC resection is challenging to interpret due to the presence of confounding postoperative inflammatory changes. A standardized reporting template for locoregional findings and report impression may improve communication of relaying risk of recurrence with referring providers, which merits validation in future studies.

Mathematical model simulation of low delta tumor growth (lambda = 0.2)

Purpose:Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease with variable presentations and natural histories of disease. We hypothesized that different morphologic characteristics of PDAC tumors on diagnostic computed tomography (CT) scans would reflect their underlying biology.Experimental Design:We developed a quantitative method to categorize the PDAC morphology on pretherapy CT scans from multiple datasets of patients with resectable and metastatic disease and correlated these patterns with clinical/pathologic measurements. We modeled macroscopic lesion growth computationally to test the effects of stroma on morphologic patterns, hypothesizing that the balance of proliferation and local migration rates of the cancer cells would determine tumor morphology.Results:In localized and metastatic PDAC, quantifying the change in enhancement on CT scans at the interface between tumor and parenchyma (delta) demonstrated that patients with conspicuous (high-delta) tumors had significantly less stroma, higher likelihood of multiple common pathway mutations, more mesenchymal features, higher likelihood of early distant metastasis, and shorter survival times compared with those with inconspicuous (low-delta) tumors. Pathologic measurements of stromal and mesenchymal features of the tumors supported the mathematical model's underlying theory for PDAC growth.Conclusions:At baseline diagnosis, a visually striking and quantifiable CT imaging feature reflects the molecular and pathological heterogeneity of PDAC, and may be used to stratify patients into distinct subtypes. Moreover, growth patterns of PDAC may be described using physical principles, enabling new insights into diagnosis and treatment of this deadly disease.

Additional methods

Mathematical model simulation of high delta tumor growth (lambda = 1.5)

Radiomics is a newer approach for analyzing radiological images obtained from conventional imaging modalities such as computed tomography, magnetic resonance imaging, endoscopic ultrasonography, and positron emission tomography. Radiomics involves extracting quantitative data from the images and assessing them to identify diagnostic or prognostic features such as tumor grade, resectability, tumor response to neoadjuvant therapy, and survival. The purpose of this review is to discuss the basic principles of radiomics and provide an overview of the current clinical applications of radiomics in the field of pancreatic tumors.

Evaluate utility of dual energy CT iodine material density images to identify preoperatively nodal positivity in pancreatic cancer patients who underwent neoadjuvant therapy. This IRB approved retrospective study evaluated 62 patients between 2012 and 2016 with proven pancreatic ductal adenocarcinoma, who underwent neoadjuvant therapy, tumor resection and both baseline and preoperative assessment with pancreatic multiphasic rapid switching dual energy CT. Three radiologists in consensus identified on imaging nodes > 0.5 cm in short axis, evaluated nodal morphology, size and on each phase density in HU, and concentrations on iodine material density images normalized to the aorta. Of 62 patients, 33 were N0, 20 N1, and 9 N2. Total of 145 lymph nodes were evaluated, with average number of nodes per anatomic site ranging from 1.3 (body tumors) to 5 (uncinate) versus average of 24 and 30 nodes recovered respectively at surgery. Most (N = 44) were pancreatic head tumors. For all patients, regardless of site of primary tumor, the minimum measured iodine value of all of a patient’s measured nodes taken as a group on preoperative studies, as normalized to the aorta, was significant at P = 0.041 value in differentiating N0 from N1/2 and ROC analysis showed an AUC of 0.67. With a cutoff of 0.2857, sensitivity was 0.78 and specificity was 0.58, with values

ObjectivesTumor size measurement is critical for accurate tumor staging in patients with pancreatic ductal adenocarcinoma (PDAC). However, accurate tumor size measurement is challenging in patients who received neoadjuvant therapy before resection, due to treatment-induced fibrosis and tumor invasion beyond the grossly identified tumor area. In this study, we evaluated the correlation between the tumor size and tumor volume measured on post-therapy computed tomography (CT) scans and the pathological measurement. Also, we investigated the correlation between these measurements and clinicopathological parameters and survival.Materials and methodsRetrospectively, we evaluated 343 patients with PDAC who received neoadjuvant therapy, followed by pancreaticoduodenectomy and had pre-operative pancreatic protocol CT imaging. We measured the longest tumor diameter (RadL) and the radiological tumor volume (RadV) on the post-therapy CT scan, then we categorized RadL into four radiologic tumor stages (RTS) based on the current AJCC staging (8th edition) protocol and RadV based on the median. Pearson correlation or Spearman's coefficient (δ), T-test and ANOVA was used to test the correlation between the radiological and pathological measurement. Chi-square analysis was used to test the correlation with the tumor pathological response, lymph-node metastasis and margin status and Kaplan-Meier and Cox-proportional hazard for survival analysis. P-value < 0.05 was considered significant.ResultsAs a continuous variable, RadL showed a positive linear correlation with the post-therapy pathologic tumor size in the overall patient population (Pearson correlation coefficient: 0.72, P&nbsp

PURPOSE: To study the association between CT-derived textural features of pancreatic cancer and patient outcome. MATERIALS AND METHODS: This retrospective study evaluated 54 patients (median age, 62 years [range, 40–88 years]; 32 men) with pancreatic cancer who underwent chemoradiation followed by surgical resection and lymph node dissection from May 2012 to June 2016. Three-dimensional segmentation of the pancreatic tumor was performed on baseline dual-energy CT images: 70-keV pancreatic parenchymal phase (PPP) images and iodine material density images. Then, 15 and 19 radiomic features were extracted from each phase, respectively. Logistic regression with elastic net regularization was used to select textural features associated with outcome, and receiver operating characteristic analysis evaluated feature performance. Survival curves were generated using the Kaplan-Meier method. RESULTS: The feature of integral total (∫ T), representing the mean intensity in Hounsfield units times the contour volume in milliliters of PPP imaging (hereafter, “∫ T (HU·mL) (PPP)”), is inversely associated with posttherapy pathologic lymph node (ypN) category. A threshold ∫ T (HU·mL) (PPP) less than 507.85 predicted ypN1–2 classification with 96% sensitivity, 34% specificity, and area under the curve of 0.61. Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased overall survival (median, 2.8 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (one event at 3.4 years) (P = .006). Patients with an ∫ T (HU·mL) (PPP) of less than 507.85 had decreased progression-free survival (median, 1.5 years) compared with patients with an ∫ T (HU·mL) (PPP) of 507.85 or greater (median, 2.7 years) (P = .001). CONCLUSION: A CT-based radiomic signature may help predict ypN category in patients with pancreatic cancer. Keywords: CT–Dual Energy, Abdomen/GI, Pancreas, Tumor Response, Outcomes Analysis © RSNA, 2022 Supplemental material is available for this article.

OBJECTIVE. The purpose of this study was to perform quantitative and qualitative evaluation of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic CT of the abdomen...

PURPOSE Effective preoperative regimens and biomarkers for pancreatic ductal adenocarcinoma (PDAC) are lacking. We prospectively evaluated fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX)-based treatment and imaging-based biomarkers for borderline resectable PDAC. METHODS Eligible patients had treatment-naïve, histology-confirmed PDAC and one or more high-risk features: mesenteric vessel involvement, CA 19-9 level of 500 mg/dL or greater, and indeterminate metastatic lesions. Patients received modified FOLFIRINOX and chemoradiation before anticipated pancreatectomy. Tumors were classified on baseline computed tomography as high delta (well-defined interface with parenchyma) or low delta (ill-defined interface). We designated computed tomography interface response after therapy as type I (remained or became well defined) or type II (became ill defined). The study had 80% power to differentiate a 60% from 40% resection rate (α = .10). Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Meier method, and subgroups were compared using log-rank tests. RESULTS Thirty-three patients initiated therapy; 45% underwent pancreatectomy. The median OS was 24 months (95% CI, 16.2 to 29.6 months). For patients who did and did not undergo pancreatectomy, the median OS was 42 months (95% CI, 17.7 months to not estimable) and 14 months (95% CI, 9.0 to 24.8 months), respectively. Patients with high-delta tumors had lower 3-year PFS (4% v 40%) and 3-year OS rates (20% v 60%) than those with low-delta tumors (both P < .05). Patients with type II interface responses had lower 3-year PFS (0% v 29%) and 3-year OS rates (16% v 47%) than those with type I responses (both P < .001). CONCLUSION Preoperative FOLFIRINOX followed by chemoradiation for high-risk borderline resectable PDAC was associated with a resection rate of 45% and median OS of approximately 2 years. Our imaging-based biomarker validation indicates that personalized treatment may be achieved using these biomarkers at baseline and post-treatment.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Its high mortality rate is attributed to its aggressive biology and frequently late presentation. While surgical resection remains the only potentially curative treatment, only 10-20% of patients will present with surgically resectable disease. Over the past several years, development of vascular bypass graft techniques and introduction of neoadjuvant treatment regimens have increased the number of patients who can undergo resection with a curative intent. While the role of conventional imaging in the detection, characterization, and staging of patients with PDAC is well established, its role in monitoring treatment response, particularly following neoadjuvant therapy remains challenging because of the complex anatomic and histological nature of PDAC. Novel morphologic and functional imaging techniques (such as DECT, DW-MRI, and PET/MRI) are being investigated to improve the diagnostic accuracy and the ability to measure response to therapy. There is also a growing interest to detect PDAC and its precursor lesions at an early stage in asymptomatic patients to increase the likelihood of achieving cure. This has led to the development of pancreatic cancer screening programs. This article will review recent updates in imaging techniques and the current status of screening and surveillance of individuals at a high risk of developing PDAC.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Accurate staging of PDAC is an important initial step in the development of a stage-specific treatment plan. Different staging systems/consensus statements convened by different societies and academic practices are currently used. The most recent version of the American Joint Committee on Cancer (AJCC) tumor/node/metastases (TNM) staging system for PDAC has shifted its focus from guiding management to assessing prognosis. In order to preoperatively define the resectability of PDAC and to guide management, additional classification systems have been developed. The National Comprehensive Cancer Network (NCCN) guidelines, one of the most commonly used systems, provide recommendations on the management and the determination of resectability for PDAC. The NCCN divides PDAC into three categories of resectability based on tumor-vessel relationship: 'resectable,' 'borderline resectable,' and 'unresectable'. Among these, the borderline disease category is of special interest given its evolution over time and the resulting variations in the definition and the associated recommendations for management between different societies. It is important to be familiar with the evolving criteria, and treatment and follow-up recommendations for PDAC. In this article, the most current AJCC staging (8th edition), NCCN guidelines (version 2.2019-April 9, 2019), and challenges and controversies in borderline resectable PDAC are reviewed.

PURPOSE: Currently, radiologists use tumor-to-normal tissue contrast across multiphase computed tomography (MPCT) for lesion detection. Here, we developed a novel voxel-based enhancement pattern mapping (EPM) technique and investigated its ability to improve contrast-to-noise ratios (CNRs) in a phantom study and in patients with hepatobiliary cancers. METHODS: The EPM algorithm is based on the root mean square deviation between each voxel and a normal liver enhancement model using patient-specific (EPM-PA) or population data (EPM-PO). We created a phantom consisting of liver tissue and tumors with distinct enhancement signals under varying tumor sizes, motion, and noise. We also retrospectively evaluated 89 patients with hepatobiliary cancers who underwent active breath-hold MPCT between 2016 and 2017. MPCT phases were registered using a three-dimensional deformable image registration algorithm. For the patient study, CNRs of tumor to adjacent tissue across MPCT phases, EPM-PA and EPM-PO were measured and compared. RESULTS: EPM resulted in statistically significant CNR improvement (P < 0.05) for tumor sizes down to 3 mm, but the CNR improvement was significantly affected by tumor motion and image noise. Eighty-two of 89 hepatobiliary cases showed CNR improvement with EPM (PA or PO) over grayscale MPCT, by an average factor of 1.4, 1.6, and 1.5 for cholangiocarcinoma, hepatocellular carcinoma, and colorectal liver metastasis, respectively (P < 0.05 for all). CONCLUSIONS: EPM increases CNR compared with grayscale MPCT for primary and secondary hepatobiliary cancers. This new visualization method derived from MPCT datasets may have applications for early cancer detection, radiomic characterization, tumor treatment response, and segmentation. IMPLICATIONS FOR PATIENT CARE: We developed a voxel-wise enhancement pattern mapping (EPM) technique to improve the contrast-to-noise ratio (CNR) of multiphase CT. The improvement in CNR was observed in datasets of patients with cholangiocarcinoma, hepatocellular carcinoma, and colorectal liver metastasis. EPM has the potential to be clinically useful for cancers with regard to early detection, radiomic characterization, response, and segmentation.

BACKGROUND: There is considerable interest in a neoadjuvant approach for resectable pancreatic ductal adenocarcinoma (PDAC). This study evaluated perioperative gemcitabine + erlotinib (G+E) for resectable PDAC. METHODS: A multicenter, cooperative group, single-arm phase II trial was conducted between April 2009 and November 2013 (ACOSOG Z5041). Patients with biopsy-confirmed PDAC in the pancreatic head without evidence of involvement of major mesenteric vessels (resectable) were eligible. Patients (n=123) received an eight-week cycle of G+E before and after surgery. The primary endpoint was two-year overall survival (OS), and secondary endpoints included toxicity, response, resection rate, and time to progression. Resectability was assessed retrospectively by central review. The study closed early due to slow accrual; no formal hypothesis testing was performed. RESULTS: One hundred fourteen patients were eligible, consented, and initiated protocol treatment. By central radiologic review, 97 (85%) of the 114 patients met protocol resectability criteria. Grade 3+ toxicity was reported in 60% and 79% of patients during the neoadjuvant phase and overall, respectively. Twenty-two of 114 (19%) patients did not proceed to surgery, 83 patients (73%) were successfully resected. R0 and R1 margins were obtained in 67 (81%) and 16 (19%) resected patients, respectively. Fifty-four patients completed postoperative G+E (65%). The two-year OS rate for the entire cohort (n=114) was 40% (95%CI 31–50) with a median OS of 21.3 months (95%CI 17.2–25.9). The two-year OS for resected patients (n=83) was 52% (95%CI 41–63) with a median OS of 25.4 months (95%CI 21.8–29.6). CONCLUSIONS: For resectable PDAC, perioperative G+E is feasible. Further evaluation of neoadjuvant strategies in resectable PDAC is warranted with more active systemic regimens.

Purpose: Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease with variable presentations and natural histories of disease. We hypothesized that different morphologic characteristics of PDAC tumors on diagnostic computed tomography (CT) scans would reflect their underlying biology. Experimental Design: We developed a quantitative method to categorize the PDAC morphology on pretherapy CT scans from multiple datasets of patients with resectable and metastatic disease and correlated these patterns with clinical/pathologic measurements. We modeled macroscopic lesion growth computationally to test the effects of stroma on morphologic patterns, hypothesizing that the balance of proliferation and local migration rates of the cancer cells would determine tumor morphology. Results: In localized and metastatic PDAC, quantifying the change in enhancement on CT scans at the interface between tumor and parenchyma (delta) demonstrated that patients with conspicuous (high-delta) tumors had significantly less stroma, higher likelihood of multiple common pathway mutations, more mesenchymal features, higher likelihood of early distant metastasis, and shorter survival times compared with those with inconspicuous (low-delta) tumors. Pathologic measurements of stromal and mesenchymal features of the tumors supported the mathematical model's underlying theory for PDAC growth. Conclusions: At baseline diagnosis, a visually striking and quantifiable CT imaging feature reflects the molecular and pathological heterogeneity of PDAC, and may be used to stratify patients into distinct subtypes. Moreover, growth patterns of PDAC may be described using physical principles, enabling new insights into diagnosis and treatment of this deadly disease.

Radiomics is a newer approach for analyzing radiological images obtained from conventional imaging modalities such as computed tomography, magnetic resonance imaging, endoscopic ultrasonography, and positron emission tomography. Radiomics involves extracting quantitative data from the images and assessing them to identify diagnostic or prognostic features such as tumor grade, resectability, tumor response to neoadjuvant therapy, and survival. The purpose of this review is to discuss the basic principles of radiomics and provide an overview of the current clinical applications of radiomics in the field of pancreatic tumors.

Previously, we characterized qualitative imaging-based subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed tomography (CT) scans. Conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we developed a quantitative classification of this imaging-based subtype (quantitative delta, q-delta). Retrospectively, baseline pancreatic protocol CT scans of three cohorts (cohort#1 = 101, cohort#2 = 90 and cohort#3 = 16 [external validation]) of patients with PDAC were qualitatively classified into high and low delta. We used a voxel-based method to volumetrically quantify tumor enhancement while referencing normal-pancreatic-parenchyma and used machine learning-based analysis to build a predictive model. In addition, we quantified the stromal content using hematoxylin- and eosin-stained treatment-na&iuml, ve PDAC sections. Analyses revealed that PDAC quantitative enhancement values are predictive of the qualitative delta scoring and were used to build a classification model (q-delta). Compared to high q-delta, low q-delta tumors were associated with improved outcomes, and the q-delta class was an independent prognostic factor for survival. In addition, low q-delta tumors had higher stromal content and lower cellularity compared to high q-delta tumors. Our results suggest that q-delta classification provides a clinically and biologically relevant tool that may be integrated into ongoing and future clinical trials.

Evaluate utility of dual energy CT iodine material density images to identify preoperatively nodal positivity in pancreatic cancer patients who underwent neoadjuvant therapy.This IRB approved retrospective study evaluated 62 patients between 2012 and 2016 with proven pancreatic ductal adenocarcinoma, who underwent neoadjuvant therapy, tumor resection and both baseline and preoperative assessment with pancreatic multiphasic rapid switching dual energy CT. Three radiologists in consensus identified on imaging nodes 0.5 cm in short axis, evaluated nodal morphology, size and on each phase density in HU, and concentrations on iodine material density images normalized to the aorta.Of 62 patients, 33 were N0, 20 N1, and 9 N2. Total of 145 lymph nodes were evaluated, with average number of nodes per anatomic site ranging from 1.3 (body tumors) to 5 (uncinate) versus average of 24 and 30 nodes recovered respectively at surgery. Most (N = 44) were pancreatic head tumors. For all patients, regardless of site of primary tumor, the minimum measured iodine value of all of a patient's measured nodes taken as a group on preoperative studies, as normalized to the aorta, was significant at P = 0.041 value in differentiating N0 from N1/2 and ROC analysis showed an AUC of 0.67. With a cutoff of 0.2857, sensitivity was 0.78 and specificity was 0.58, with values 0.2857 indicative of N1/2. Node morphology and changes in nodal size weren't statistically significant.The dual energy based minimum normalized iodine value of all nodes in the surgical field on preoperative studies has modest utility in differentiating N0 from N1/2, and generally outperformed conventional features for identifying nodal metastases.

BackgroundPreviously, we characterized subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed-tomography (CT) scans, whereby conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we hypothesized that these imaging-based subtypes would exhibit different growth-rates and distinctive metabolic effects in the period prior to PDAC diagnosis.Materials and methodsRetrospectively, we evaluated 55 patients who developed PDAC as a second primary cancer and underwent serial pre-diagnostic (T0) and diagnostic (T1) CT-scans. We scored the PDAC tumors into high and low delta on T1 and, serially, obtained the biaxial measurements of the pancreatic lesions (T0-T1). We used the Gompertz-function to model the growth-kinetics and estimate the tumor growth-rate constant (α) which was used for tumor binary classification, followed by cross-validation of the classifier accuracy. We used maximum-likelihood estimation to estimate initiation-time from a single cell (10-6 mm3) to a 10 mm3 tumor mass. Finally, we serially quantified the subcutaneous-abdominal-fat (SAF), visceral-abdominal-fat (VAF), and muscles volumes (cm3) on CT-scans, and recorded the change in blood glucose (BG) levels. T-test, likelihood-ratio, Cox proportional-hazards, and Kaplan-Meier were used for statistical analysis and p-value ResultsCompared to high delta tumors, low delta tumors had significantly slower average growth-rate constants (0.024 month−1 vs. 0.088 month−1, p−1. Leave-one-out-cross-validation showed 80% accuracy in predicting the delta-class (AUC=0.84). High delta tumors exhibited accelerated SAF, VAF, and muscle wasting (p ConclusionImaging-based subtypes of PDAC exhibit distinct growth, metabolic, and clinical profiles during the pre-diagnostic period. Our results suggest that heterogeneous disease biology may be an important consideration in early detection strategies for PDAC.

Pancreatic ductal adenocarcinoma (PDA) is the third leading cause of cancer-related death in the United States and is projected to be the second by 2030. Systemic combination chemotherapy is considered an essential first-line treatment for the majority of patients with PDA, in both the neoadjuvant and palliative settings. In addition, a number of novel therapies are being tested in clinical trials for patients with advanced PDA. In all cases, accurate and timely assessment of treatment response is critical to guide therapy, reduce drug toxicities and cost from a failing therapy, and aid adaptive clinical trials. Conventional morphological imaging has significant limitations, especially in the context of determining primary tumor response and resectability following neoadjuvant therapies. In this article, we provide an overview of current therapy options for PDA, highlight several morphological imaging findings that may be helpful to reduce over-staging following neoadjuvant therapy, and discuss a number of emerging imaging, and non-imaging, tools that have shown promise in providing a more precise quantification of disease burden and treatment response in PDA.

To evaluate the quantitative attenuation and reliability of virtual non-contrast (VNC) images of the abdomen acquired from multiphasic scans with a dual-energy computed tomography (DECT) system and compare it with that of true non-enhanced images (TNC) on second- (Flash) and third- (Force) generation DECT scanners. This retrospective study was approved by the institutional review board and included 123 patients with pancreatic cancer who had undergone routine clinical multiphasic DECT examinations at our institution using Flash and Force scanners between March and August 2017. VNC images of the abdomen were reconstructed from late arterial phase images. For every patient, regions-of-interest were defined in the aorta, fluid-containing structures (gallbladder, pleural effusion, and renal cysts > 10 mm), paravertebral muscles, subcutaneous fat, spleen, pancreas, renal cortex, and liver (eight locations) on TNC and VNC images. The mean attenuation of VNC was compared with TNC by organ for each CT scanner using an equivalence test and the Bland–Altman plot. The mean attenuations for TNC or VNC were compared between the Force and Flash CT scanners using a two-sample t test. The VNC attenuation of organs on the Force scanner was lower than was that on the Flash, and the mean attenuation difference in different organs on the Force was closer to 0. The estimated means of TNC and VNC were equivalent for an equivalence margin of 10 on the Force scanner. VNC images in DECT are a promising alternative to TNC images. In clinical scenarios in which non-enhanced CT images are required but are not available for accurate diagnosis, VNC images can potentially serve as an alternative to TNC images without the radiation exposure risks.

Preoperative chemotherapy provides early treatment of micro-metastases and guaranteed delivery of all components of multimodality therapy for localized pancreatic ductal adenocarcinoma (PDAC). For locally advanced (LA) PDAC, induction chemotherapy is the standard of care. This study evaluated the use of gemcitabine and nab-paclitaxel (Gem/nab-P) as first-line therapy for localized PDAC. Clinicopathologic features, treatment, and outcomes were evaluated for 99 patients with localized PDAC. The patients were staged using previously published criteria as follows: potentially resectable (PR), borderline type A (BR-A) (anatomy amenable to vascular resection), BR-B (biology suspicious for metastatic disease including high CA19-9), BR–C (comorbidities requiring medical optimization), and LA. The 99 patients (PR/BR/LA: 45/14/40) were treated with Gem/nab-P. Clinical staging showed that 20 patients had PR or BR-A disease, whereas 39 patients had BR-B or BR-C disease. The BR-B+C cases included one or more of the following: age of 80 years or older (13%), Eastern Cooperative Oncology Group performance status (ECOG PS) of 2 or more (13%), moderate to severe comorbidities (55%), CA19-9 of 1000 or higher (28%), and suspicion for metastases (21%). The majority of the patients received biweekly Gem/nab-P dosing, which was well tolerated. Pancreatectomy was performed for 12 (60%) of 20 patients with PR+BR-A, 2 (5%) of 39 patients with BR-B+C, and 1 (3%) of 40 patients with LA disease. During a median follow-up period of 26 months, the median overall survival (OS) period was 18 months (95% confidence interval [CI], 15.6–20.5 months) for all the patients, 17 months (95% CI, 14.6–19.5 months) for the unresected patients, and not reached for the resected patients (p = 0.028 for resected vs unresected patients). A significant number of patients with radiographically resectable PDAC albeit aggressive biology (BR-B), medically inoperable conditions (BR-C), or both received biweekly first-line Gem/nab-P. The resection rates were lower for the BR-B/BR-C patients than for the PR/BR-A patients (hazard ratio [HR], 0.43; 95% CI, 0.19–1.00; p = 0.05).

Mucinous cystic neoplasm (MCN) of pancreas is one of the precursor lesions of pancreatic ductal adenocarcinoma. The 5-year disease-specific survival for noninvasive MCNs was 100% and 20% to 60% for those with pancreatic ductal adenocarcinoma arising in a MCN. However, the significance of T1a (≤0.5 cm) and T1b (>0.5 and

Purpose To determine the accuracy of dual-energy computed tomographic (CT) quantitation in a phantom system comparing fast kilovolt peak-switching, dual-source, split-filter, sequential-scanning, and dual-layer detector systems. Materials and Methods A large elliptical phantom containing iodine (2, 5, and 15 mg/mL), simulated contrast material-enhanced blood, and soft-tissue inserts with known elemental compositions was scanned three to five times with seven dual-energy CT systems and a total of 10 kilovolt peak settings. Monochromatic images (50, 70, and 140 keV) and iodine concentration images were created. Mean iodine concentration and monochromatic attenuation for each insert and reconstruction energy level were recorded. Measurement bias was assessed by using the sum of the mean signed errors measured across relevant inserts for each monochromatic energy level and iodine concentration. Iodine and monochromatic errors were assessed by using the root sum of the squared error of all measurements. Results At least one acquisition paradigm per scanner had iodine biases (range, -2.6 to 1.5 mg/mL) with significant differences from zero. There were no significant differences in iodine error (range, 0.44-1.70 mg/mL) among the top five acquisition paradigms (one fast kilovolt peak switching, three dual source, and one sequential scanning). Monochromatic bias was smallest for 70 keV (-12.7 to 15.8 HU) and largest for 50 keV (-80.6 to 35.2 HU). There were no significant differences in monochromatic error (range, 11.4-52.0 HU) among the top three acquisition paradigms (one dual source and two fast kilovolt peak switching). The lowest accuracy for both measures was with a split-filter system. Conclusion Iodine and monochromatic accuracy varies among systems, but dual-source and fast kilovolt-switching generally provided the most accurate results in a large phantom. © RSNA, 2017 Online supplemental material is available for this article.

Background The assessment of pancreatic ductal adenocarcinoma (PDAC) response to therapy remains challenging. The objective of this study was to investigate whether changes in the tumor/parenchyma interface are associated with response. Methods Computed tomography (CT) scans before and after therapy were reviewed in 4 cohorts: cohort 1 (99 patients with stage I/II PDAC who received neoadjuvant chemoradiation and surgery); cohort 2 (86 patients with stage IV PDAC who received chemotherapy), cohort 3 (94 patients with stage I/II PDAC who received protocol-based neoadjuvant gemcitabine chemoradiation), and cohort 4 (47 patients with stage I/II PDAC who received neoadjuvant chemoradiation and were prospectively followed in a registry). The tumor/parenchyma interface was visually classified as either a type I response (the interface remained or became well defined) or a type II response (the interface became poorly defined) after therapy. Consensus (cohorts 1-3) and individual (cohort 4) visual scoring was performed. Changes in enhancement at the interface were quantified using a proprietary platform. Results In cohort 1, type I responders had a greater probability of achieving a complete or near-complete pathologic response (21% vs 0%; P = .01). For cohorts 1, 2, and 3, type I responders had significantly longer disease-free and overall survival, independent of traditional covariates of outcomes and of baseline and normalized cancer antigen 19-9 levels. In cohort 4, 2 senior radiologists achieved a κ value of 0.8, and the interface score was associated with overall survival. The quantitative method revealed high specificity and sensitivity in classifying patients as type I or type II responders (with an area under the receiver operating curve of 0.92 in cohort 1, 0.96 in cohort 2, and 0.89 in cohort 3). Conclusions Changes at the PDAC/parenchyma interface may serve as an early predictor of response to therapy. Cancer 2018;124:1701-9. © 2018 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

OBJECTIVE The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). METHODS AND MATERIALS Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. RESULTS Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P < 0.05). Adaptive statistical iterative reconstruction-V 90% showed superior LCD and had the highest CNR in the liver, aorta, and, pancreas, measuring 7.32 ± 3.22, 11.60 ± 4.25, and 4.60 ± 2.31, respectively, compared with the next best series of ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P

Pancreatic adenocarcinoma is associated with poor overall prognosis. Complete surgical resection is the only possible option for cure. As such, increasingly complex surgical techniques including sophisticated vascular reconstruction are being used. Continued advances in surgical techniques, in conjunction with use of combination systemic therapies, and radiation therapy have been suggested to improve outcomes. A key aspect to surgical success is reporting of pivotal findings beyond absence of distant metastases, such as tumor size, location, and degree of tumor involvement of specific vessels associated with potential perineural tumor spread. Multiphase contrast-enhanced multidetector CT and MRI are the imaging modalities of choice for pretreatment staging and presurgical determination of resectability. Imaging modalities such as endoscopic ultrasound and fluorine-18-2-fluoro-2-deoxy-D-glucose imaging with PET/CT are indicated for specific scenarios such as biopsy guidance and confirmation of distant metastases, respectively. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Dual-energy CT imaging has many potential uses in abdominal imaging. It also has unique requirements for protocol creation depending on the dual-energy scanning technique that is being utilized. It also generates several new types of images which can increase the complexity of image creation and image interpretation. The purpose of this article is to review, for rapid switching and dual-source dual-energy platforms, methods for creating dual-energy protocols, different approaches for efficiently creating dual-energy images, and an approach to navigating and using dual-energy images at the reading station all using the example of a pancreatic multiphasic protocol. It will also review the three most commonly used types of dual-energy images: "workhorse" 120kVp surrogate images (including blended polychromatic and 70 keV monochromatic), high contrast images (e.g., low energy monochromatic and iodine material decomposition images), and virtual unenhanced images. Recent developments, such as the ability to create automatically on the scanner the most common dual-energy images types, namely new "Mono+" images for the DSDECT (dual-source dual-energy CT) platform will also be addressed. Finally, an approach to image interpretation using automated "hanging protocols" will also be covered. Successful dual-energy implementation in a high volume practice requires careful attention to each of these steps of scanning, image creation, and image interpretation.

To qualitatively and quantitatively compare abdominal computed tomography (CT) images reconstructed with a new version of model-based iterative reconstruction (Veo 3.0; GE Healthcare) to those created with Veo 2.0.This retrospective study was approved by our institutional review board and was Health Insurance Portability and Accountability Act compliant. The raw data from 29 consecutive patients who had undergone CT abdomen scanning was used to reconstruct 4 sets of 3.75-mm axial images: Veo 2.0, Veo 3.0 standard, Veo 3.0 5% resolution preference (RP), and Veo 3.0 20% RP. A slice thickness optimization of 3.75 mm and texture feature was selected for Veo 3.0 reconstructions.The images were reviewed by 3 independent readers in a blinded, randomized fashion using a 5-point Likert scale and 5-point comparative scale.Multiple 2-dimensional circular regions of interest were defined for noise and contrast-to-noise ratio measurements. Line profiles were drawn across the 7 lp/cm bar pattern of the CatPhan 600 phantom for spatial resolution evaluation.The Veo 3.0 standard image set was scored better than Veo 2.0 in terms of artifacts (mean difference, 0.43; 95% confidence interval [95% CI], 0.25-0.6; P0.0001), overall image quality (mean difference, 0.87; 95% CI, 0.62-1.13; P0.0001) and qualitative resolution (mean difference, 0.9; 95% CI, 0.69-1.1; P0.0001). Although the Veo 3.0 standard and RP05 presets were preferred across most categories, the Veo 3.0 RP20 series ranked best for bone detail. Image noise and spatial resolution increased along a spectrum with Veo 2.0 the lowest and RP20 the highest.Veo 3.0 enhances imaging evaluation relative to Veo 2.0; readers preferred Veo 3.0 image appearance despite the associated mild increases in image noise. These results provide suggested parameters to be used clinically and as a basis for future evaluations, such as focal lesion detection, in the oncology setting.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Its high mortality rate is attributed to its aggressive biology and frequently late presentation. While surgical resection remains the only potentially curative treatment, only 10-20% of patients will present with surgically resectable disease. Over the past several years, development of vascular bypass graft techniques and introduction of neoadjuvant treatment regimens have increased the number of patients who can undergo resection with a curative intent. While the role of conventional imaging in the detection, characterization, and staging of patients with PDAC is well established, its role in monitoring treatment response, particularly following neoadjuvant therapy remains challenging because of the complex anatomic and histological nature of PDAC. Novel morphologic and functional imaging techniques (such as DECT, DW-MRI, and PET/MRI) are being investigated to improve the diagnostic accuracy and the ability to measure response to therapy. There is also a growing interest to detect PDAC and its precursor lesions at an early stage in asymptomatic patients to increase the likelihood of achieving cure. This has led to the development of pancreatic cancer screening programs. This article will review recent updates in imaging techniques and the current status of screening and surveillance of individuals at a high risk of developing PDAC.

The discrimination of mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) is a central diagnostic dilemma. It is important to differentiate these entities since they have markedly different prognoses and management. Importantly, the appearance of these two entities significantly overlaps on a variety of imaging modalities. However, there are imaging features that may be suggestive of one entity more than the other. MFCP and PDAC may show different enhancement patterns on perfusion computed tomography (CT) and/or dynamic contrast-enhanced MRI (DCE-MRI). The duct-penetrating sign on magnetic resonance cholangiopancreatography (MRCP) is more often associated with MFCP, whereas abrupt cutoff with upstream dilatation of the main pancreatic duct and the double-duct sign (obstruction/cutoff of both the common bile duct and pancreatic duct) are more often associated with PDAC. Nevertheless, tissue sampling is the most reliable method to differentiate between these entities and is currently generally necessary for management.

Current treatment options for patients with unresectable locally advanced pancreatic cancer (LAPC) include chemotherapy alone or followed by chemoradiation or stereotactic body radiotherapy. However, the prognosis for these patients remains poor, with a median overall survival

Background Assessments of the quantitative limitations among the six commercially available dual-energy (DE) CT acquisition schemes used by major CT manufacturers could aid researchers looking to use iodine quantification as an imaging biomarker. Purpose To determine the limits of detection and quantification of DE CT in phantoms by comparing rapid peak kilovoltage switching, dual-source, split-filter, and dual-layer detector systems in six different scanners. Materials and Methods Seven 50-mL iohexol solutions were used, with concentrations of 0.03-2.0 mg iodine per milliliter. The solutions and water sample were scanned five times each in two phantoms (small, 20-cm diameter; large, 30 × 40-cm diameter) with six DE CT systems and a total of 10 peak kilovoltage settings or combinations. Iodine maps were created, and the mean iodine signal in each sample was recorded. The limit of blank (LOB) was defined as the upper limit of the 95% confidence interval of the water sample. The limit of detection (LOD) was defined as the concentration with a 95% chance of having a signal above the LOB. The limit of quantification (LOQ) was defined as the lowest concentration where the coefficient of variation was less than 20%. Results The LOD range was 0.021-0.26 mg/mL in the small phantom and 0.026-0.55 mg/mL in the large phantom. The LOQ range was 0.07-0.50 mg/mL in the small phantom and 0.20-1.0 mg/mL in the large phantom. The dual-source and rapid peak kilovoltage switching systems had the lowest LODs, and the dual-layer detector systems had the highest LODs. Conclusion The iodine limit of detection using dual-energy CT systems varied with scanner and phantom size, but all systems depicted iodine in the small and large phantoms at or below 0.3 and 0.5 mg/mL, respectively, and enabled quantification at concentrations of 0.5 and 1.0 mg/mL, respectively. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Hindman in this issue.

Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.

Pancreatic ductal adenocarcinoma and cystic neoplasms of the pancreas account for the majority of all pancreatic neoplasms. However, there is a subset of rare and unusual conditions of the pancreas that have been increasingly identified over the past two decades, in part by increased use of computed tomography. These conditions can often be challenging to clinicians because the presentation and diagnostic findings can often mimic pancreatic ductal adenocarcinoma. This chapter will focus on these less appreciated lesions and will discuss the optimal diagnostic and therapeutic approaches to their management.

The purpose of this study was to evaluate a single-institution experience with delivery of preoperative therapy to patients with pancreatic ductal adenocarcinoma (PDAC) prior to pancreatoduodenectomy (PD). Consecutive patients (622) with PDAC who underwent PD following chemotherapy and/or chemoradiation between 1990 and 2014 were retrospectively reviewed. Preoperative treatment regimens, clinicopathologic characteristics, operative details, and long-term outcomes in four successive time periods (1990–1999, 2000–2004, 2005–2009, 2010–2014) were evaluated and compared. The average number of patients per year who underwent PD following preoperative therapy as well as the proportion of operations performed for borderline resectable and locally advanced (BR/LA) tumors increased over time. The use of induction systemic chemotherapy, as well as postoperative adjuvant chemotherapy, also increased over time. Throughout the study period, the mean EBL decreased while R0 margin rates and vascular resection rates increased overall. Despite the increase in BR/LA resections, locoregional recurrence (LR) rates remained similar over time, and overall survival (OS) improved significantly (median 24.1, 28.1, 37.3, 43.4 months, respectively, p < 0.0001). Despite increases in case complexity, relatively low rates of LR have been maintained while significant improvements in OS have been observed. Further improvements in patient outcomes will likely require disruptive advances in systemic therapy.

// Alexander N. Hanania 1,2 , Leonidas E. Bantis 3 , Ziding Feng 3 , Huamin Wang 4 , Eric P. Tamm 5 , Matthew H. Katz 6 , Anirban Maitra 4 and Eugene J. Koay 2 1 University of Texas Medical School, Houston, TX, USA 2 Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA 3 Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, USA 4 Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA 5 Department of Diagnostic Radiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA 6 Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA Correspondence to: Eugene J. Koay, email: // Keywords : IPMN, quantitative imaging, radiomics, fukuoka, pancreatic cyst Received : July 06, 2016 Accepted : August 18, 2016 Published :August 31, 2016 Abstract Objective: To investigate using quantitative imaging to assess the malignant potential of intraductal papillary mucinous neoplasms (IPMNs) in the pancreas. Background: Pancreatic cysts are identified in over 2% of the population and a subset of these, including intraductal papillary mucinous neoplasms (IPMNs), represent pre-malignant lesions. Unfortunately, clinicians cannot accurately predict which of these lesions are likely to progress to pancreatic ductal adenocarcinoma (PDAC). Methods: We investigated 360 imaging features within the domains of intensity, texture and shape using pancreatic protocol CT images in 53 patients diagnosed with IPMN (34 “high-grade” [HG] and 19 “low-grade” [LG]) who subsequently underwent surgical resection. We evaluated the performance of these features as well as the Fukuoka criteria for pancreatic cyst resection. Results: In our cohort, the Fukuoka criteria had a false positive rate of 36%. We identified 14 imaging biomarkers within Gray-Level Co-Occurrence Matrix (GLCM) that predicted histopathological grade within cyst contours. The most predictive marker differentiated LG and HG lesions with an area under the curve (AUC) of .82 at a sensitivity of 85% and specificity of 68%. Using a cross-validated design, the best logistic regression yielded an AUC of 0.96 (σ = .05) at a sensitivity of 97% and specificity of 88%. Based on the principal component analysis, HG IPMNs demonstrated a pattern of separation from LG IPMNs. Conclusions: HG IPMNs appear to have distinct imaging properties. Further validation of these findings may address a major clinical need in this population by identifying those most likely to benefit from surgical resection.

Pancreatic neuroendocrine tumors are rare tumors that present many imaging challenges, from detecting small functional tumors to fully staging large nonfunctioning tumors, including identifying all sites of metastatic disease, particularly nodal and hepatic, and depicting vascular involvement. The correct choice of imaging modality requires knowledge of the tumor type (eg, gastrinoma versus insulinoma), and also the histology (well vs poorly differentiated). Evolving techniques in computed tomography (CT), MRI, endoscopic ultrasonography, and nuclear medicine, such as dual-energy CT, diffusion-weighted MRI, liver-specific magnetic resonance contrast agents, and new nuclear medicine agents, offer new ways to visualize, and ultimately manage, these tumors.