Laparoscopic-assisted treatment for diospyrobezoar-induced intestinal obstruction after distal gastrectomy and cholecystectomy.

Diospyrobezoar is a relatively uncommon cause of small bowel obstruction. Here we report successful treatment in a patient with small bowel obstruction due to diospyrobezoar by laparoscopic-assisted surgery. A 93-year-old woman who had undergone distal gastrectomy and laparoscopic cholecystectomy presented with nausea and anorexia. An intestinal obstruction and an intestinal intraluminal mass were discovered on abdominal enhanced computed tomography. Following a transnasal ileus tube placement, the patient underwent laparoscopic surgery to remove the diospyrobezoar from the small intestine. The postoperative course of the patient was uneventful. Laparoscopic-assisted surgery following the transnasal ileus tube was beneficial for the patient's small bowel obstruction caused by diospyrobezoar.

Unenhanced Dual-Layer Spectral-Detector CT for Characterizing Indeterminate Adrenal Lesions.

Background Unenhanced dual-layer spectral-detector CT may facilitate adrenal lesion characterization; however, no studies have evaluated its incremental diagnostic yield for indeterminate lesions (unenhanced attenuation >10 HU) in comparison to that with conventional unenhanced CT. Purpose To determine whether spectral attenuation analysis improves characterization of lipid-poor adrenal adenomas from nonadenomas compared to that with mean attenuation and histogram analysis of conventional CT images. Materials and Methods This retrospective study included patients with indeterminate adrenal lesions who underwent unenhanced dual-layer spectral-detector CT between March 2018 and June 2020. Mean attenuation on conventional 120-kVp images (HUconv), histogram-based percentage negative pixels (proportion of all pixels <0 HU) on conventional 120-kVp images, and mean attenuation on virtual monoenergetic images (VMIs) at 40-140 keV were measured for each lesion. The attenuation difference between virtual monoenergetic 140- and 40-keV images (ΔHU; ie, Hounsfield unit at 140 keV - Hounsfield unit at 40 keV) and ΔHU indexed with HUconv (ΔHU index; ie, ΔHU/HUconv × 100) were calculated. Conventional and virtual monoenergetic imaging parameters were compared between lipid-poor adenomas and nonadenomas by using the Mann-Whitney U test. Receiver operating characteristic analysis was performed to determine the sensitivity for attaining at least 95% specificity in characterizing adenomas from nonadenomas; sensitivity was compared by using the McNemar test. Results A total of 232 patients (mean age ± standard deviation, 67 years ± 11; 145 men) with 129 lipid-poor adenomas and 103 nonadenomas were evaluated. HUconv and mean attenuation on VMIs at 40-140 keV were lower and the percentage negative pixels, ΔHU, and ΔHU index higher in lipid-poor adenomas than in nonadenomas (P < .001 for all). Attenuation differences between adenomas and nonadenomas on VMIs were maximal at 40 keV (23 HU at 40 keV vs 5 HU at 140 keV). The highest sensitivities for differentiating adenomas and nonadenomas were achieved for virtual monoenergetic ΔHU index (77% [99 of 129 adenomas]), attenuation on 40-keV images (71% [91 of 129 adenomas]), and ΔHU (67% [87 of 129 adenomas]) compared to HUconv (35% [45 of 129 adenomas]) and percentage negative pixels (30% [39 of 129 adenomas]) (P < .001 for all; specificity, 95% [98 of 103 nonadenomas]). Conclusion Spectral attenuation analysis enabled differentiation of lipid-poor adenomas from nonadenomas with higher sensitivity than mean attenuation or histogram analysis of conventional CT images. © RSNA, 2021 Online supplemental material is available for this article.

Relative Enhancement Ratio of Portal Venous Phase to Unenhanced CT in the Diagnosis of Lipid-poor Adrenal Adenomas.

Background The development of an accurate, practical, noninvasive, and widely available diagnostic approach to characterize lipid-poor adrenal lesions (greater than 10 HU at unenhanced CT) remains an ongoing demand. Purpose To investigate whether combined assessment of unenhanced and portal venous phase CT allows for the differentiation of lipid-poor adrenal adenomas from nonadenomas. Materials and Methods Patients with lipid-poor adrenal lesions who underwent unenhanced and portal venous phase CT with a single-energy scanner between January 2016 and March 2020 were identified retrospectively. For each lesion, the unenhanced and contrast-enhanced attenuation were measured; the absolute enhancement (contrast-enhanced minus unenhanced attenuation [HU]) and relative enhancement ratio ([absolute enhancement divided by unenhanced attenuation] × 100%) were calculated. The sensitivity achieved at 95% specificity to distinguish adenomas from nonadenomas was determined with receiver operating characteristic curve analysis and compared among parameters with use of the McNemar test. Results A total of 220 patients (mean age ± standard deviation, 66 years ± 12; 134 men) with 131 lipid-poor adenomas and 89 nonadenomas were analyzed. The sensitivity (achieved at 95% specificity) of the relative enhancement ratio (86% [113 of 131 adenomas; 95% CI: 79, 92] at a threshold of >210%) was higher than that of unenhanced attenuation (50% [66 of 131 adenomas; 95% CI: 42, 59] at a threshold of ≤21 HU), contrast-enhanced attenuation (3% [four of 131 adenomas; 95% CI: 1, 8] at a threshold of >120 HU), and absolute enhancement (24% [32 of 131 adenomas; 95% CI: 17, 33] at a threshold of >74 HU; all P < .001). The sensitivities of the relative enhancement ratio were 100% (58 of 58 adenomas; 95% CI: 94, 100), 83% (52 of 63 adenomas; 95% CI: 71, 91), and 30% (three of 10 adenomas; 95% CI: 7, 65) for adenomas measuring unenhanced attenuation of more than 10 HU up to 20 HU, 21-30 HU, and more than 30 HU, respectively. Conclusion A relative enhancement ratio threshold of greater than 210%, measured at unenhanced and portal venous phase CT, accurately differentiated lipid-poor adenomas from nonadenomas, particularly for lesions with unenhanced attenuation of 10-30 HU. © RSNA, 2021 Online supplemental material is available for this article.

Adrenal Adenomas versus Metastases: Diagnostic Performance of Dual-Energy Spectral CT Virtual Noncontrast Imaging and Iodine Maps.

Background Dual-energy CT allows virtual noncontrast (VNC) attenuation and iodine density measurements from contrast material-enhanced examination, potentially enabling adrenal lesion characterization. However, data regarding diagnostic performance remain limited, and combined diagnostic values have never been investigated. Purpose To determine whether VNC attenuation, iodine density, and combination of the two allow reliable differentiation between adrenal adenomas and metastases. Materials and Methods This retrospective study included patients with adrenal lesions who underwent unenhanced and portal venous phase dual-energy CT between January 2017 and December 2018. Unenhanced, contrast-enhanced, and VNC attenuation, as well as iodine density, were measured for each lesion. Agreement between unenhanced and VNC attenuation was assessed by using Wilcoxon rank-sum test, Pearson correlation coefficient, and Bland-Altman plot. The ratio of iodine density to VNC attenuation was calculated for lesions with positive VNC attenuation. Each parameter was compared between adenomas and metastases; diagnostic performance was evaluated by using the area under the receiver operating characteristic curve (AUC) with sensitivity and specificity. Results A total of 149 patients (mean age, 65 years ± 13 [standard deviation]; 89 men; 98 patients with 104 adenomas; 51 patients with 56 metastases) were evaluated. VNC attenuation showed strong positive correlation with unenhanced attenuation (r = 0.92) but resulted in overestimates of adenoma attenuation (mean bias, +11 HU; P < .001) and was less sensitive (P = .03) in the diagnosis of adenomas compared with unenhanced attenuation (sensitivity of 79% [81 of 102] [95% confidence interval {CI}: 70%, 87%] and specificity of 95% [53 of 56] [95% CI: 85%, 99%] versus sensitivity of 85% [87 of 102] [95% CI: 77%, 92%] and specificity of 96% [54 of 56] [95% CI: 88%, 100%], with thresholds of ≤29 HU and ≤22 HU, respectively). Contrast-enhanced attenuation had no discriminatory ability (AUC, 0.54; 95% CI: 0.45, 0.62). Iodine density yielded moderate performance (sensitivity of 78% [80 of 102] [95% CI: 69%, 86%] and specificity of 71% [40 of 56] [95% CI: 58%, 83%], with a threshold of ≥1.82 mg/mL). The iodine-to-VNC ratio was higher in adenomas than in metastases (mean, 14.5 vs 4.6; P < .001), with sensitivity of 95% (97 of 102; 95% CI: 89%, 98%) and specificity of 95% (53 of 56; 95% CI: 85%, 99%), with a threshold of 6.7 or greater. Conclusion Contrast-enhanced dual-energy CT during the portal venous phase enabled accurate differentiation between adrenal adenomas and metastases by combining virtual noncontrast attenuation and iodine density. Virtual noncontrast imaging alone led to overestimates of adenoma attenuation, and iodine density alone had limited discriminatory utility. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Hindman and Megibow in this issue.

Usefulness of Virtual Monochromatic Dual-Layer Computed Tomographic Imaging for Breast Carcinoma.

OBJECTIVE: This study aimed to evaluate virtual monochromatic images (VMIs) obtained using dual-layer dual-energy computed tomography (CT) for breast carcinoma. METHODS: We retrospectively enrolled 28 patients with breast cancer who were pathologically diagnosed using dual-layer dual-energy CT. Virtual monochromatic images (40-200 keV) were generated. We compared CT number, image noise, contrast, and contrast-to-noise ratio (CNR) between VMIs with the highest CNR and conventional CT images. We performed qualitative image analysis between VMIs at optimized energy and conventional CT images. RESULTS: Image noise of VMIs was not significantly different from that of the conventional CT images. As the x-ray energy decreased, CNR increased. The 40-keV VMIs were highest CNR and higher than that of the conventional CT images. In qualitative image analysis, the 40-keV images were significantly higher than conventional CT images. CONCLUSION: Both qualitative and quantitative analyses showed that the image quality of VMIs at 40 keV was significantly higher than that of conventional CT images.

Dual-layer spectral CT improves image quality of multiphasic pancreas CT in patients with pancreatic ductal adenocarcinoma.

OBJECTIVES: To evaluate the image quality and optimal energies of virtual monoenergetic images (VMIs) from dual-layer spectral detector computed tomography (DLCT) in multiphasic pancreatic CT and investigate whether low-keV VMI at the portal venous phase (PVP) provides sufficient tumor conspicuity and arterial depiction relative to conventional pancreatic parenchymal phase (PPP) images. METHODS: Forty-eight patients with pancreatic ductal adenocarcinoma (PDAC) underwent contrast-enhanced DLCT during PPP and PVP. Conventional polyenergetic images (PEIs) and VMI at 40-100 keV (VMI40-100, 10-keV increments) were reconstructed at each enhancement phase. Image noise and the contrast-to-noise ratio (CNR) of the pancreas, tumors, arteries, and veins were quantified. Two radiologists independently assessed tumor conspicuity, margin delineation, image noise, sharpness of pancreatic duct, and depiction of arteries and veins on a five-point scale. Size-specific dose estimate (SSDE) was calculated. RESULTS: Image noise for VMI40-100 was significantly lower than that for PEI (p < 0.01). The CNR in VMI increased gradually with decreasing energy; CNRs for VMI40-60 were significantly greater than that for PEI (p < 0.01). All subjective VMI scores were maximized at VMI40, followed by VMI50-60, all of which were significantly better than of PEI (p < 0.01). Objective and subjective image qualities of VMI40-50 at the PVP were equivalent to or even better compared with conventional PPP images. No significant difference in SSDE was observed between phases (p = 0.10). CONCLUSIONS: DLCT-VMI improved the subjective and objective image quality in multiphasic pancreatic CT for patients with PDAC. Low-keV PVP imaging may yield diagnostically adequate tumor conspicuity and arterial assessment compared with polyenergetic PPP images. KEY POINTS: • Low-keV VMI from DLCT yields better subjective and objective image quality of multiphasic pancreas CT in comparison with conventional PEI for the assessment of pancreatic ductal adenocarcinoma. • Tumor conspicuity and depiction of peripancreatic vasculature were maximized at VMI 40without an increase in the image noise. • Low-keV VMI of the portal venous phase provides sufficient tumor conspicuity and arterial depiction, potentially allowing the early detection and local staging of PDAC on routine abdominal CT performed for various clinical indications.

An initial experience of machine learning based on multi-sequence texture parameters in magnetic resonance imaging to differentiate glioblastoma from brain metastases.

PURPOSE: To evaluate the performance of a machine learning method based on texture parameters in conventional magnetic resonance imaging (MRI) in differentiating glioblastoma (GB) from brain metastases (METs). MATERIALS AND METHODS: In this retrospective study conducted between November 2008 and July 2017, we included 73 patients diagnosed with GB (n = 73) and METs (n = 53) who underwent contrast-enhanced 3 T brain MRI. Twelve histogram and texture parameters were assessed on T2-weighted images (T2WIs), apparent diffusion coefficient maps (ADCs), and contrast-enhanced T1-weighted images (CE-T1WIs). A prediction model was developed for a machine learning method, and the area under the receiver operating characteristic curve of this model was calculated through 5-fold cross-validation. Furthermore, machine learning method's performance was compared with three board-certified radiologists' judgments. RESULTS: Univariate logistic regression model showed that the area under the curve (AUC) was highest with the standard value of T2WIs (0.78), followed by the maximum value of T2WIs (0.764), minimum value of T2WIs (0.738), minimum values of CE-T1WIs and contrast of T2WIs (0.733), and mean value of T2WIs (0.724). AUC calculated using the support vector machine was comparable to that calculated by the three radiologists (0.92 vs. 0.72, p < .01; 0.92 vs. 0.73, p < .01; and 0.92 vs. 0.86, p = .096). CONCLUSION: In differentiating GB from METs on the basis of texture parameters in MRI, the performance of the machine learning method based on convention MRI was superior to that of the univariate method, and comparable to that of the radiologists.

Prevalence of extracardiac findings in patients undergoing coronary computed tomography and additional low-dose whole-body computed tomography.

PURPOSE: In patients with suspected coronary artery disease (CAD), coexisting extracardiac abnormalities have a major impact on the patient management. This study aimed to evaluate the image quality of whole-body computed tomography (CT) immediately after the coronary computed tomography angiography (CTA) and investigate the incidence of extracardiac findings in patients with suspected CAD. MATERIALS AND METHODS: We enrolled 450 patients undergoing whole-body CT at 100 kVp and model-based iterative reconstruction immediately after the coronary CTA (Group A) and retrospectively reviewed 144 control patients who underwent conventional contrast-enhanced CT (120 kVp) with filtered back projection (Group B). We compared the signal-to-noise ratio (SNR) of the aorta and liver and radiation dose between the two groups. Then, we evaluated the prevalence of extracardiac findings in Group A. RESULTS: Compared with Group B, Group A demonstrated significantly higher aorta and liver SNR and lower radiation dose. In Group A, whole-body CT revealed 229 coexisting lesions in 165 patients, including 32 and 106 cases of oncologic and vascular diseases, respectively. CONCLUSION: Additional whole-body CT after coronary CTA may provide adequate image quality. Using additional whole-body CT, 36% of patients with suspected CAD had clinically relevant coexisting findings, including malignancy.