Lean body weight-tailored Iodinated contrast Injection in obese patient. boer versus James Formula

Purpose. To prospectively compare the performance of James and Boer formula in contrast media (CM) administration, in terms of image quality and parenchymal enhancement in obese patients undergoing CT of the abdomen. Materials and Methods. Fifty-five patients with a body mass index (BMI) greater than 35 kg/m2were prospectively included in the study. All patients underwent 64-row CT examination and were randomly divided in two groups: 26 patients in Group A and 29 patients in Group B. The amount of injected CM was computed according to the patient's lean body weight (LBW), estimated using either Boer formula (Group A) or James formula (Group B). Patient's characteristics, CM volume, contrast-to-noise ratio (CNR) of liver, aorta and portal vein, and liver contrast enhancement index (CEI) were compared between the two groups. For subjective image analysis readers were asked to rate the enhancement of liver, kidneys, and pancreas based on a 5-point Likert scale. Results. Liver CNR, aortic CNR, and portal vein CNR showed no significant difference between Group A and Group B (all P ≥ 0.177). Group A provided significantly higher CEI compared to Group B (P = 0.007). Group A and Group B returned comparable overall subjective enhancement values (3.54 and vs 3.20, all P ≥ 0.199). Conclusions. Boer formula should be the method of choice for LBW estimation in obese patients, leading to an accurate CM amount calculation and an optimal liver contrast enhancement in CT

Systematic review and meta-analysis investigating the diagnostic yield of dual-energy CT for renal mass assessment

OBJECTIVE. The objective of our study was to perform a systematic review and meta-analysis to evaluate the diagnostic accuracy of dual-energy CT (DECT) for renal mass evaluation. MATERIALS AND METHODS. In March 2018, we searched MEDLINE, Cochrane Database of Systematic Reviews, Embase, and Web of Science databases. Analytic methods were based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Pooled estimates for sensitivity, specificity, and diagnostic odds ratios were calculated for DECT-based virtual monochromatic imaging (VMI) and iodine quantification techniques as well as for conventional attenuation measurements from renal mass CT protocols. I 2 was used to evaluate heterogeneity. The methodologic quality of the included studies and potential bias were assessed using items from the Quality Assessment Tool for Diagnostic Accuracy Studies 2 (QUADAS-2). RESULTS. Of the 1043 articles initially identified, 13 were selected for inclusion (969 patients, 1193 renal masses). Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for VMI were 87% (95% CI, 80–92%; I 2 , 92.0%), 93% (95% CI, 90–96%; I 2 , 18.0%), and 183.4 (95% CI, 30.7–1093.4; I 2 , 61.6%), respectively. Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for iodine quantification were 99% (95% CI, 97–100%; I 2 , 17.6%), 91% (95% CI, 89–94%; I 2 , 84.2%), and 511.5 (95% CI, 217–1201; I 2 , 0%). No significant differences in AUCs were found when comparing iodine quantification to conventional attenuation measurements (p = 0.79). CONCLUSION. DECT yields high accuracy for renal mass evaluation. Determination of iodine content with the iodine quantification technique shows diagnostic accuracy similar to conventional attenuation measurements from renal mass CT protocols. The iodine quantification technique may be used to characterize incidental renal masses when a dedicated renal mass protocol is not available

Performance of Machine Learning and Texture Analysis for Predicting Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer with 3T MRI

Background: To evaluate the diagnostic performance of a Machine Learning (ML) algorithm based on Texture Analysis (TA) parameters in the prediction of Pathological Complete Response (pCR) to Neoadjuvant Chemoradiotherapy (nChRT) in Locally Advanced Rectal Cancer (LARC) patients. Methods: LARC patients were prospectively enrolled to undergo pre- and post-nChRT 3T MRI for initial loco-regional staging. TA was performed on axial T2-Weighted Images (T2-WI) to extract specific parameters, including skewness, kurtosis, entropy, and mean of positive pixels. For the assessment of TA parameter diagnostic performance, all patients underwent complete surgical resection, which served as a reference standard. ROC curve analysis was carried out to determine the discriminatory accuracy of each quantitative TA parameter to predict pCR. A ML-based decisional tree was implemented combining all TA parameters in order to improve diagnostic accuracy. Results: Forty patients were considered for final study population. Entropy, kurtosis and MPP showed statistically significant differences before and after nChRT in patients with pCR; in particular, when patients with Pathological Partial Response (pPR) and/or Pathological Non-Response (pNR) were considered, entropy and skewness showed significant differences before and after nChRT (all p p = 0.04); 1.87 ± 2.19, in pCR, −0.06 ± 3.78 in pPR/pNR (p = 0.0005); 107.91 ± 274.40, in pCR, −28.33 ± 202.91 in pPR/pNR, (p = 0.004), respectively). According to ROC curve analysis, pre-treatment kurtosis with an optimal cut-off value of ≤3.29 was defined as the best discriminative parameter, resulting in a sensitivity and specificity in predicting pCR of 81.5% and 61.5%, respectively. Conclusions: TA parameters extracted from T2-WI MRI images could play a key role as imaging biomarkers in the prediction of response to nChRT in LARC patients. ML algorithms can be used to efficiently combine all TA parameters in order to improve diagnostic accuracy

Half-dose coronary artery calcium scoring. impact of Iterative reconstruction

Purpose: The purpose of this study was to assess the impact of adaptive statistical iterative reconstruction (ASiR) on half-dose coronary artery calcium scoring (CACS) acquisition protocol. Materials and Methods: Between September 2016 and October 2017, 89 patients (54 male patients, mean age 64.6±10.7 y) with a clinically indicated coronary computed tomography angiography were prospectively enrolled. On a 64-row computed tomography scanner, patients underwent a standard CACS protocol (120 kVp, 170 mAs) reconstructed by filtered-back projection, and a half-dose CACS protocol (120 kVp, 85 mAs) reconstructed by ASiR at different percentages, from 10% to 100%, in 10% increments. CACS determinants (Agatston score, number of plaques, volume, and mass), signal-to-noise ratio, contrast-to-noise ratio, and radiation dose of both protocols were calculated. Patient risk categories based on CACS were determined for each protocol, and analysis of risk reclassification of half-dose protocol was performed. Depending on their body mass index (BMI), patients were divided into nonobese (BMI<30 kg/m2) and obese (BMI≥30 kg/m2) groups to investigate the influence of BMI on CACS determinants and risk reclassification. Results: Half-dose protocol reconstructed with ASiR 70% showed no significant differences in any CACS determinant compared with the standard protocol for both nonobese and obese patients (all P≥0.070 and ≥0.066, respectively) and reclassified 1 (1.7%) and 6 (20.0%) patients, respectively, with excellent (κ=0.91) and good (κ=0.74) agreement with standard protocol, respectively. ASiR 70% also resulted in a higher signal-to-noise ratio (1.88±0.78) and contrast-to-noise ratio (7.10±2.73) compared with standard protocol (all P≤0.001). Half-dose protocol provided 52% less radiation dose than standard acquisition (0.31±0.06 vs. 0.64±0.10 mSv; P<0.001). Conclusions: ASIR 70% coupled with reduction of tube current by 50% allowed for significant dose reduction and no detrimental effects on image quality, with minimal patient reclassification in nonobese patients. In obese patients, excessive noise may lead to a clinically significant reclassification rate

Greeks and Phoenicians in the Western Mediterranean

International audienc