Iodine Material Density Images Research Articles

Baseline CT-based Radiomic Features Aid Prediction of Nodal Positivity after Neoadjuvant Therapy in Pancreatic Cancer.

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.

CT features predictive of nodal positivity at surgery in pancreatic cancer patients following neoadjuvant therapy in the setting of dual energy CT.

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 > 0.5cm 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.

Dual-Energy CT Images: Pearls and Pitfalls.

Dual-energy CT (DECT) is a tremendous innovation in CT technology that allows creation of numerous imaging datasets by enabling discrete acquisitions at more than one energy level. The wide range of images generated from a single DECT acquisition provides several benefits such as improved lesion detection and characterization, superior determination of material composition, reduction in the dose of iodine, and more robust quantification. Technological advances and the proliferation of various processing methods have led to the availability of diverse vendor-based DECT approaches, each with a different acquisition and image reconstruction process. The images generated from various DECT scanners differ from those from conventional single-energy CT because of differences in their acquisition techniques, material decomposition methods, image reconstruction algorithms, and postprocessing methods. DECT images such as virtual monochromatic images, material density images, and virtual unenhanced images have different imaging appearances, texture features, and quantitative capabilities. This heterogeneity creates challenges in their routine interpretation and has certain associated pitfalls. Some artifacts such as residual iodine on virtual unenhanced images and an appearance of pseudopneumatosis in a gas-distended bowel loop on material-density iodine images are specific to DECT, while others such as pseudoenhancement seen on virtual monochromatic images are also observed at single-energy CT. Recognizing the potential pitfalls associated with DECT is necessary for appropriate and accurate interpretation of the results of this increasingly important imaging tool. Online supplemental material is available for this article. ©RSNA, 2021.

Rapid kVp-switching DECT portal venous phase abdominal CT scans in patients with large body habitus: image quality considerations.

To assess the diagnostic image quality and material decomposition characteristics of portal venous phase abdominal CT scans performed on rapid kVp-switching DECT (rsDECT) in patients with large body habitus. We retrospectively included consecutive patients with large body habitus (≥ 90kg) undergoing portal venous phase abdominal CT scans on rsDECT scanners between Sep 2014 and March 2018. Qualitative and quantitative assessment of the DECT data sets [65keV monoenergetic, material density iodine (MD-I) and material density water (MD-W) images] was performed for determination of image quality (IQ) and image noise. Correlation of qualitative assessment scores with weight, BMI and patients' diameter were calculated using Pearson correlation test. Optimal thresholds were calculated using AUC and Youden index to define most appropriate size cut off, below which the IQ of material density images is largely acceptable. The 65 keV monoenergetic images were of diagnostic quality (diagnostic acceptability, DA ≥ 3) in 97.8% of patients (n = 91/93). However, there was significant IQ degradation of MD-I images in 20.4% (n = 19/93, DA < 3) of patients. Similarly, there was significant degradation (DA < 3) of MD-W images in 26.9% (25/92). Clinically significant artifacts (PA ≥ 3/4) were seen in 31% (n = 29/93) and 32.3% (30/93) of MD-I and MD-W images respectively. Optimal threshold for diagnostic acceptability of MD-I images were 110kg for weight and 33.5kg/m2 for BMI. Rapid kVp-switching DECT provides diagnostically acceptable monoenergetic images for patients with large body habitus (≥ 90kg). There is degradation of IQ in the material density specific images particularly in patients weighing > 110kg and with BMI > 33.5kg/m2, due to higher number of artifacts.

Diagnostic performance of dual-energy CT and subtraction CT for renal lesion detection and characterization.

To compare the effect of dual-energy CT (DECT) material density datasets on diagnostic performance, readers' confidence, and interpretation time for renal lesion detection and characterization in comparison to subtraction CT (SCT). One hundred fourteen patients (69/45 = M/F, mean age=67years) who underwent contrast-enhanced DECT between January 2015 and February 2018 for suspected renal mass were included retrospectively. For each patient, three radiologists assessed three image datasets: group A, material density iodine (MDI) + material density water (MDW); group B, SCT only; and group C, SCT + true unenhanced phase + virtual monochromatic images at 65keV. Readers evaluated image quality (4-point scale), the number of lesions, and likely diagnosis. Reading times were recorded. Quantitatively, iodine concentration (IC from MDI) and delta Hounsfield units (ΔHU) for all lesions were measured. Diagnostic accuracy was compared using the area under the receiver operating characteristic curve (AUC). Image quality and interpretation time were compared with Kruskal-Wallis and t tests. Study cohort (230 lesions; mean size=23.63mm (5-116mm)) consisted of 60 enhancing, 158 non-enhancing, and 12 lipid-dominant angiomyolipoma lesions. Significantly higher image quality was demonstrated for MDI compared to SCT (mean score=3.82 vs. 3; p< 0.05). Comparable diagnostic accuracy was observed for group A (AUC=0.88) and group C (AUC=0.87) and was higher compared to that for group B (AUC=0.75). Group A was read faster than group C (41.49s vs. 71.45s per exam; p< 0.05). Both IC and ΔHU values had high accuracy (AUC=0.97) for differentiating enhancing vs. non-enhancing lesions; however, IC enabled differentiation of clear cell renal cell carcinoma from other enhancing lesions with moderate accuracy (AUC=0.73). MDI images increase readers' confidence for renal lesion detection and characterization while providing a more efficient radiologist workflow, irrespective of readers' experience. • Material density iodine (MDI) images enable faster interpretation due to high image quality and potentially reduced need for quantitation. • MDI images increase diagnostic confidence of readers, irrespective of radiologists' experience. • High accuracy with dual-energy CT (DECT) can potentially reduce healthcare costs by eliminating the need for additional investigations.

Iodine material density images in dual-energy CT: quantification of contrast uptake and washout in HCC.

To determine the diagnostic potential of Material Density (MD) iodine images in dual-energy CT(DECT) for visualization and quantification of arterial phase hyperenhancement and washout in hepatocellular carcinomas compared to magnetic resonance imaging (MRI). The study complied with HIPAA guidelines and was approved by the ethics committee of the institutional review board. Thirty-one patients (23 men, 8 women; age range, 36-87years) with known or suspected Hepatocellular Carcinoma (HCC) were included. All of them underwent both single-source DECT and MRI within less than 3months. Late arterial phase and portal venous phase CT imaging was performed with dual energies of 140 and 80 kVp, and virtual monoenergetic images (at 65keV) and MD-iodine images were generated. We determined the contrast-to-noise ratio (CNR) for HCC in arterial phase and portal venous phase images. In addition, we introduced a new parameter which combines information of CNR in arterial and portal venous phase images into a single ratio (combined CNR). All parameters were assessed on monoenergetic 65keV images, MD-iodine images, and MRI. Paired t test was used to compare CNR values in Mono-65keV, MD-iodine, and MR images. CNR was significantly higher in the MD-iodine images in both the arterial (81.87 ± 40.42) and the portal venous phases (33.31 ± 27.86), compared to the Mono-65keV (6.34 ± 4.23 and 1.89 ± 1.87) and MRI (30.48 ± 25.52 and 8.27 ± 8.36), respectively. Combined CNR assessment from arterial and portal venous phase showed higher contrast ratios for all imaging modalities (Mono-65keV, 8.73 ± 4.03; MD-iodine, 119.87 ± 52.94; MRI, 34.87 ± 27.34). In addition, highest contrast ratio was achieved in MD-iodine images with combined CNR evaluation (119.87 ± 52.94, P < 0.001). MD-iodine images in DECT allow for a quantitative assessment of contrast enhancement andwashout, with improved CNR in hepatocellular carcinoma in comparison to MRI.

Quantification of Iodine Concentration Using Single-Source Dual-Energy Computed Tomography in a Calf Liver

To evaluate the accuracy of single-source dual-energy computed tomography (ssDECT) in iodine quantification using various segmentation methods in an ex vivo model. Ten sausages, injected with variable quantities of iodinated contrast, were inserted into 2 livers and scanned with ssDECT. Material density iodine images were reconstructed. Three radiologists segmented each sausage. Iodine concentration, volume, and absolute quantity were measured. Agreement between the measured and injected iodine was assessed with the concordance correlation coefficient (CCC). Intrareader agreement was assessed using the intraclass correlation coefficient (ICC). Air bubbles were observed in sausage (IX). Sausage (X) was within the same view as hyper-attenuating markers used for localization. With IX and X excluded, CCC and ICC were greater than 0.98 and greater than 0.88. When included, CCC and ICC were greater than 0.94 and greater than 0.79. Iodine quantification was reproducible and precise. However, accuracy reduced in sausages consisting of air filled cavities and within the same view as hyperattenuating markers.

Material density iodine images in dual-energy CT: Detection and characterization of hypervascular liver lesions compared to magnetic resonance imaging

PurposeTo determine the diagnostic potential of Material Density (MD) iodine images in dual-energy CT (DECT) for the detection and characterization of hypervascular liver lesions compared to monenergetic 65keV images, using MRI as the standard. Materials and methodsThe study complied with HIPAA guidelines and was approved by the institutional review board. Fifty-two patients (36 men, 16 women; age range, 29–87 years) with 236 hypervascular liver lesions (benign, n=31; malignant, n=205; mean diameter, 29.4mm; range: 6–90.6mm) were included. All of them underwent both contrast-enhanced single-source DECT and contrast-enhanced abdominal MRI within three months. Late arterial phase CT imaging was performed with dual energies of 140 and 80kVp. Protocol A showed monoenergetic 65keV images, and protocol B presented MD-iodine images. Three radiologists qualitatively evaluated randomized images, and lesion detection, characterization, and reader confidence were recorded. Liver-to-lesion ratio (LLR) and contrast-to-noise ratio (CNR) were assessed on protocol A, protocol B, and MRI. Paired t-tests were used to compare LLR, CNR, and the number of detected lesions. ResultsLLR was significantly increased in protocol B (2.8±2.33) compared to protocol A (0.77±0.55) and MRI (0.61±0.66). CNR was significantly higher in protocol B (0.08±0.04) compared to protocol A (0.01±0.01) and MRI (0.01±0.01). All three observers correctly identified more liver lesions using protocol B vs protocol A: 83.13% vs 63.64%, 84.57% vs 68.09%, and 79.37% vs 65.52%. There was no significant difference between the three observers in classification of a lesion as benign or malignant. However, higher diagnostic confidence was reported more frequently by the experienced radiologist when using protocol B vs protocol A (84.6% vs 75%). ConclusionMD-iodine images in DECT help to increase the conspicuity and detection of hypervascular liver lesions.

Multireader evaluation of lesion conspicuity in small pancreatic adenocarcinomas: complimentary value of iodine material density and low keV simulated monoenergetic images using multiphasic rapid kVp-switching dual energy CT.

Perform multireader analysis of objective and subjective lesion conspicuity for small pancreatic adenocarcinomas using rapid switching dual energy CT (rsDECT). With IRB approval, 51 abdominal multiphasic rsDECT scans in 46 subjects with small (<3 cm) pancreatic adenocarcinomas were retrospectively reviewed by three independent readers for objective and subjective lesion conspicuity. Measured variables during individual, blinded interpretive sessions of separate low (52) keV, PACS-equivalent (70) keV, and iodine material density (MD) image sets included Hounsfield units (HU) and mg/cc iodine for tumor, nontumoral pancreas, and subcutaneous fat. Objective measures included absolute lesion contrast (LC) and contrast to noise ratios (CNR). Subjective measures included image quality, lesion conspicuity, and reader confidence. Reader agreement was measured with kappa statistic; correlation with truth by Pearson coefficient, CNR with repeated mANOVA; subjective quality measures utilized Tukey-Cramer corrections for multiple testing, p < 0.05 considered significant. Demographics: 26 F, 20 M, mean age 68 years, weight 75 kg, tumor size of 2.3 cm. LC was highest on 52 keV images for all three readers (mean 90.1 HU). Mean CNR for iodine MD images (4.87) was significantly higher than 52 keV (4.13) or 70 keV (3.9). Very high to near-perfect kappa values were observed for all individual measured objective variables but were best for 52 keV images (52 keV 0.89-0.95, 70 keV 0.76-0.83, iodine 0.87-0.92). 70 keV images scored best for subjective image quality; iodine MD images scored best for lesion conspicuity and reader confidence. We observed very high reader agreement for independent objective rsDECT image variables and subjective rsDECT image scores in patients with small pancreatic adenocarcinomas. Maximal objective tumor to nontumoral LC was depicted on 52 keV and highest CNR on iodine MD images; readers scored the iodine MD images best for lesion conspicuity and confidence.