Iodine concentration and tissue attenuation in dual-energy contrast-enhanced CT as a potential quantitative parameter in early detection of local pancreatic carcinoma recurrence after surgical resection.

PURPOSE: Due to the difficult differentiation from non-specific postoperative soft tissue formation (PSF), early diagnosis of pancreatic carcinoma recurrence remains challenging. Thus, we investigated the diagnostic potential of dual-energy (DE) contrast-enhanced CT. METHOD: After potentially curative pancreatic carcinoma resection, 31 consecutive patients with PSF were examined via DE perfusion CT, acquiring 34 images (80 kVp/140 kVp) every 1.5 s, as the initial purpose of this study was evaluating CT-Perfusion. Corresponding time points of arterial, pancreatic, and early venous phase were calculated from bolus trigger times in prior conventional CT. Iodine and 120 kVp-equivalent images were calculated. Regions of interest were placed in each soft tissue formation. Diagnosis of local recurrence was confirmed by regular follow-up or histopathology. RESULTS: Final diagnosis was local recurrence in 17 patients and non-specific PSF in 14 patients. Iodine concentrations in early venous phase were significantly higher in recurrent carcinoma than in non-specific PSF (1.47 mg/ml vs. 0.96 mg/ml, p = 0.007). In earlier contrast phases iodine concentrations tended to be higher, but not significantly. CT numbers in recurrent carcinoma in 120 kVp-equivalent images in venous phase were significantly higher, too (74HU vs 47HU, p = 0.002). ROC-curve analysis for iodine concentrations in early venous phase suggests a cut-off value of ≥ 1.55 mg/ml for local recurrence (AUC = 0.78, specificity = 1.0, sensitivity = 0.53) and for CT numbers in 120kVp-equivalent images a cut-off value of ≥ 57HU (AUC = 0.82, specificity = 0.82, sensitivity = 0.71). CONCLUSION: In difficult cases, measuring iodine concentrations or CT numbers in PSF in (early) venous phase DECT could be a valuable additional parameter for differentiating local recurrence from non-specific PSF.

VirtualTaste: a web server for the prediction of organoleptic properties of chemical compounds.

Taste is one of the crucial organoleptic properties involved in the perception of food by humans. Taste of a chemical compound present in food stimulates us to take in food and avoid poisons. Bitter taste of drugs presents compliance problems and early flagging of potential bitterness of a drug candidate may help with its further development. Similarly, the taste of chemicals present in food is important for evaluation of food quality in the industry. In this work, we have implemented machine learning models to predict three different taste endpoints-sweet, bitter and sour. The VirtualTaste models achieved an overall accuracy of 90% and an AUC of 0.98 in 10-fold cross-validation and in an independent test set. The web server takes a two-dimensional chemical structure as input and reports the chemical's taste profile for three tastes-using molecular fingerprints along with confidence scores, including information on similar compounds with known activity from the training set and an overall radar chart. Additionally, insights into 25 bitter receptors are also provided via target prediction for the predicted bitter compounds. VirtualTaste, to the best of our knowledge, is the first freely available web-based platform for the prediction of three different tastes of compounds. It is accessible via http://virtualtaste.charite.de/VirtualTaste/without any login requirements and is free to use.

Computed Tomography Perfusion Analysis of Pancreatic Adenocarcinoma using Deconvolution, Maximum Slope, and Patlak Methods - Evaluation of Diagnostic Accuracy and Interchangeability of Cut-Off Values.

PURPOSE: The goal of this study was to evaluate the diagnostic accuracy of perfusion computed tomography (CT) parameters obtained by different mathematical-kinetic methods for distinguishing pancreatic adenocarcinoma from normal tissue. To determine cut-off values and to assess the interchangeability of cut-off values, which were determined by different methods. MATERIALS AND METHODS: Perfusion CT imaging of the pancreas was prospectively performed in 23 patients. 19 patients with histopathologically confirmed pancreatic adenocarcinoma were included in the study. Blood flow (BF), blood volume (BV) and permeability-surface area product (PS) were measured in pancreatic adenocarcinoma and normal tissue with the deconvolution (BF, BV, PS), maximum slope (BF), and Patlak methods (BV, PS). The interchangeability of cut-off values was examined by assessing agreement between BF, BV, and PS measured with different mathematical-kinetic methods. RESULTS: Bland-Altman analysis demonstrated poor agreement between perfusion parameters, measured with different mathematical-kinetic methods. According to receiver operating characteristic (ROC) analysis, PS measured with the Patlak method had the significantly lowest diagnostic accuracy (area under ROC curve = 0.748). All other parameters were of high diagnostic accuracy (area under ROC curve = 0.940-0.997), although differences in diagnostic accuracy were not statistically different. Cut-off values for BF of ≤ 91.83 ml/100 ml/min and for BV of ≤ 5.36 ml/100 ml, both measured with the deconvolution method, appear to be the most appropriate cut-off values to distinguish pancreatic adenocarcinoma from normal tissue. CONCLUSION: Perfusion parameters obtained by different methods are not interchangeable. Therefore, cut-off values, which were determined using different methods, are not interchangeable either. Perfusion parameters can help to distinguish pancreatic adenocarcinoma from normal tissue with high diagnostic accuracy, except for PS measured with the Patlak method. KEY POINTS: · Perfusion CT parameters showed high diagnostic accuracy in differentiating between pancreatic adenocarcinoma and normal tissue.. · Only PS measured with the Patlak method showed a significantly lower diagnostic accuracy.. · Perfusion parameters measured with different mathematical-kinetic methods are not interchangeable.. · A specific cut-off value must be determined for each method and each perfusion parameter.. CITATION FORMAT: · Koell M, Klauss M, Skornitzke S et al. Computed Tomography Perfusion Analysis of Pancreatic Adenocarcinoma with the Deconvolution, Maximum Slope, and Patlak Methods - Evaluation of Diagnostic Accuracy and Interchangeability of Cut-Off Values. Fortschr Röntgenstr 2021; 193: 1062 - 1073.

Assessment of tissue perfusion of pancreatic cancer as potential imaging biomarker by means of Intravoxel incoherent motion MRI and CT perfusion: correlation with histological microvessel density as ground truth.

BACKGROUND/OBJECTIVES: The aim of this study was to compare intravoxel incoherent motion (IVIM) diffusion weighted (DW) MRI and CT perfusion to assess tumor perfusion of pancreatic ductal adenocarcinoma (PDAC). METHODS: In this prospective study, DW-MRI and CT perfusion were conducted in nineteen patients with PDAC on the day before surgery. IVIM analysis of DW-MRI was performed and the parameters perfusion fraction f, pseudodiffusion coefficient D*, and diffusion coefficient D were extracted for tumors, upstream, and downstream parenchyma. With a deconvolution-based analysis, the CT perfusion parameters blood flow (BF) and blood volume (BV) were estimated for tumors, upstream, and downstream parenchyma. In ten patients, intratumoral microvessel density (MVDtumor) and microvessel area (MVAtumor) were analyzed microscopically in resection specimens. Correlation coefficients between IVIM parameters, CT perfusion parameters, and histological microvessel parameters in tumors were calculated. Receiver operating characteristic (ROC) analysis was performed for differentiation of tumors and upstream parenchyma. RESULTS: ftumor significantly positively correlated with BFtumor (r = 0.668, p = 0.002) and BVtumor (r = 0.672, p = 0.002). There were significant positive correlations between ftumor and MVDtumor/ MVAtumor (r ≥ 0.770, p ≤ 0.009) as well as between BFtumor and MVDtumor/ MVAtumor (r ≥ 0.697, p ≤ 0.025). Correlation coefficients between ftumor and MVDtumor/ MVAtumor were not significantly different from correlation coefficients between BFtumor and MVDtumor/ MVAtumor (p ≥ 0.400). Moreover, f, BF, BV, and permeability values (PEM) showed excellent performance in distinguishing tumors from upstream parenchyma (area under the ROC curve ≥0.874). CONCLUSIONS: The study shows that IVIM derived ftumor and CT perfusion derived BFtumor similarly reflect vascularity of PDAC and seem to be comparably applicable for the evaluation of tumor perfusion for tumor characterization and as potential quantitative imaging biomarker. TRIAL REGISTRATION: DRKS, DRKS00022227, Registered 26 June 2020, retrospectively registered. https://www.drks.de/drks_web/navigate.do?navigationId=trial . HTML&TRIAL_ID=DRKS00022227.

Dual-energy CT iodine maps as an alternative quantitative imaging biomarker to abdominal CT perfusion: determination of appropriate trigger delays for acquisition using bolus tracking.

OBJECTIVE: Quantitative evaluation of different bolus tracking trigger delays for acquisition of dual energy (DE) CT iodine maps as an alternative to CT perfusion. METHODS: Prior to this retrospective analysis of prospectively acquired data, DECT perfusion sequences were dynamically acquired in 22 patients with pancreatic carcinoma using dual source CT at 80/140 kVp with tin filtration. After deformable motion-correction, perfusion maps of blood flow (BF) were calculated from 80 kVp image series of DECT, and iodine maps were calculated for each of the 34 DECT acquisitions per patient. BF and iodine concentrations were measured in healthy pancreatic tissue and carcinoma. To evaluate potential DECT acquisition triggered by bolus tracking, measured iodine concentrations from the 34 DECT acquisitions per patient corresponding to different trigger delays were assessed for correlation to BF and intergroup differences between tissue types depending on acquisition time. RESULTS: Average BF measured in healthy pancreatic tissue and carcinoma was 87.6 ± 28.4 and 38.6 ± 22.2 ml/100 ml min-1, respectively. Correlation between iodine concentrations and BF was statistically significant for bolus tracking with trigger delay greater than 0 s (rmax = 0.89; p < 0.05). Differences in iodine concentrations between healthy pancreatic tissue and carcinoma were statistically significant for DECT acquisitions corresponding to trigger delays of 15-21 s (p < 0.05). CONCLUSION: An acquisition window between 15 and 21 s after exceeding bolus tracking threshold shows promising results for acquisition of DECT iodine maps as an alternative to CT perfusion measurements of BF. Advances in knowledge: After clinical validation, DECT iodine maps of pancreas acquired using bolus tracking with appropriate trigger delay as determined in this study could offer an alternative quantitative imaging biomarker providing functional information for tumor assessment at reduced patient radiation exposure compared to CT perfusion measurements of BF.

Correction: Use of Mesh in Laparoscopic Paraesophageal Hernia Repair: A Meta-Analysis and Risk-Benefit Analysis.

[This corrects the article DOI: 10.1371/journal.pone.0139547.].

Fluid collection after distal pancreatectomy: a frequent finding.

BACKGROUND: Fluid collections (FC) at the resection margin of the pancreatic stump after distal pancreatectomy (DP) are common radiological findings in follow-up scans. No recommendations exist regarding the management of such findings. The aim was to characterise incidence, risk factors, clinical impact and therapy of FC. METHOD: Data of 209 patients who underwent DP between 07/2009 and 06/2011 were prospectively collected and analysed, regarding follow-up CT or MRI scan findings of FC at the resection margin. FC was defined as a cyst-like lesion >1 cm in diameter. RESULTS: A follow-up with at least two cross-sectional images was available in 159/209 patients. In the first postoperative control, 68 patients showed an FC (43%). FC size was classified as <5 cm (n = 38 pat.), 5-10 cm (n = 24 pat.) and >10 cm (n = 6 pat.). 20 patients (30%) showed clinical symptoms. Six patients (9%) required specific treatment, all other FC showed spontaneous regression. No correlation with stump closure techniques or preceding postoperative pancreatic fistula was found (4/68 patients, 6%). Multivariate analysis revealed standard resections as the only significant factor for FC. CONCLUSIONS: FCs at the resection margin after DP are frequent and harmless findings. Therapeutic interventions are required in only 9% of all FC patients.

Use of Mesh in Laparoscopic Paraesophageal Hernia Repair: A Meta-Analysis and Risk-Benefit Analysis.

INTRODUCTION: Mesh augmentation seems to reduce recurrences following laparoscopic paraesophageal hernia repair (LPHR). However, there is an uncertain risk of mesh-associated complications. Risk-benefit analysis might solve the dilemma. MATERIALS AND METHODS: A systematic literature search was performed to identify randomized controlled trials (RCTs) and observational clinical studies (OCSs) comparing laparoscopic mesh-augmented hiatoplasty (LMAH) with laparoscopic mesh-free hiatoplasty (LH) with regard to recurrences and complications. Random effects meta-analyses were performed to determine potential benefits of LMAH. All data regarding LMAH were used to estimate risk of mesh-associated complications. Risk-benefit analysis was performed using a Markov Monte Carlo decision-analytic model. RESULTS: Meta-analysis of 3 RCTs and 9 OCSs including 915 patients revealed a significantly lower recurrence rate for LMAH compared to LH (pooled proportions, 12.1% vs. 20.5%; odds ratio (OR), 0.55; 95% confidence interval (CI), 0.34 to 0.89; p = 0.04). Complication rates were comparable in both groups (pooled proportions, 15.3% vs. 14.2%; OR, 1.02; 95% CI, 0.63 to 1.65; p = 0.94). The systematic review of LMAH data yielded a mesh-associated complication rate of 1.9% (41/2121; 95% CI, 1.3% to 2.5%) for those series reporting at least one mesh-associated complication. The Markov Monte Carlo decision-analytic model revealed a procedure-related mortality rate of 1.6% for LMAH and 1.8% for LH. CONCLUSIONS: Mesh application should be considered for LPHR because it reduces recurrences at least in the mid-term. Overall procedure-related complications and mortality seem to not be increased despite of potential mesh-associated complications.

Correlation of quantitative dual-energy computed tomography iodine maps and abdominal computed tomography perfusion measurements: are single-acquisition dual-energy computed tomography iodine maps more than a reduced-dose surrogate of conventional computed tomography perfusion?

OBJECTIVES: Study objectives were the quantitative evaluation of whether conventional abdominal computed tomography (CT) perfusion measurements mathematically correlate with quantitative single-acquisition dual-energy CT (DECT) iodine concentration maps, the determination of the optimum time of acquisition for achieving maximum correlation, and the estimation of the potential for radiation exposure reduction when replacing conventional CT perfusion by single-acquisition DECT iodine concentration maps. MATERIALS AND METHODS: Dual-energy CT perfusion sequences were dynamically acquired over 51 seconds (34 acquisitions every 1.5 seconds) in 24 patients with histologically verified pancreatic carcinoma using dual-source DECT at tube potentials of 80 kVp and 140 kVp. Using software developed in-house, perfusion maps were calculated from 80-kVp image series using the maximum slope model after deformable motion correction. In addition, quantitative iodine maps were calculated for each of the 34 DECT acquisitions per patient. Within a manual segmentation of the pancreas, voxel-by-voxel correlation between the perfusion map and each of the iodine maps was calculated for each patient to determine the optimum time of acquisition topt defined as the acquisition time of the iodine map with the highest correlation coefficient. Subsequently, regions of interest were placed inside the tumor and inside healthy pancreatic tissue, and correlation between mean perfusion values and mean iodine concentrations within these regions of interest at topt was calculated for the patient sample. RESULTS: The mean (SD) topt was 31.7 (5.4) seconds after the start of contrast agent injection. The mean (SD) perfusion values for healthy pancreatic and tumor tissues were 67.8 (26.7) mL per 100 mL/min and 43.7 (32.2) mL per 100 mL/min, respectively. At topt, the mean (SD) iodine concentrations were 2.07 (0.71) mg/mL in healthy pancreatic and 1.69 (0.98) mg/mL in tumor tissue, respectively. Overall, the correlation between perfusion values and iodine concentrations was high (0.77), with correlation of 0.89 in tumor and of 0.56 in healthy pancreatic tissue at topt. Comparing radiation exposure associated with a single DECT acquisition at topt (0.18 mSv) to that of an 80 kVp CT perfusion sequence (2.96 mSv) indicates that an average reduction of Deff by 94% could be achieved by replacing conventional CT perfusion with a single-acquisition DECT iodine concentration map. CONCLUSIONS: Quantitative iodine concentration maps obtained with DECT correlate well with conventional abdominal CT perfusion measurements, suggesting that quantitative iodine maps calculated from a single DECT acquisition at an organ-specific and patient-specific optimum time of acquisition might be able to replace conventional abdominal CT perfusion measurements if the time of acquisition is carefully calibrated. This could lead to large reductions of radiation exposure to the patients while offering quantitative perfusion data for diagnosis.

Computed tomography perfusion analysis of pancreatic carcinoma.

OBJECTIVE: The purpose of this study was to evaluate CT perfusion of pancreatic carcinomas using the Patlak model for assessing perfusion, permeability, and blood volume. METHODS: A total of 25 patients with pancreatic carcinoma were examined prospectively with a 64-slice computed tomography (CT) using a dynamic sequence after intravenous injection of 80-mL contrast material (370 mg/mL; flow rate, 5 mL/s). Eighty-kilovolt (peak) perfusion acquisitions were evaluated for estimating perfusion parameters for carcinoma and healthy tissue using a 2-compartment model (Patlak model). RESULTS: Twenty patients had hypodense tumors; in 5 patients, the tumor could not be delineated in contrast-enhanced CT. All carcinomas could be identified clearly in the color-coded perfusion maps. Perfusion, permeability, and blood volume values were significant lower in pancreatic carcinomas compared to healthy pancreatic tissue (0.27 ± 0.20 vs 0.89 ± 0.19 min, P < 0.0001; 0.43 ± 0.20 vs 0.75 ± 0.16 × 0.5 min, P < 0.0001; and 38.9 ± 20.7 vs 117.8 ± 46.9 mL/100 mL, P < 0.0001). CONCLUSION: Computed tomographic perfusion of the pancreas using a 2-compartment perfusion model is feasible. Color-coded perfusion maps could be a helpful tool to delineate pancreatic carcinomas even if they are not visible in contrast-enhanced CT.