CT Attenuation Research Articles

The effectiveness of post-processing head and neck CT angiography using contrast enhancement boost technique.

This study aimed to investigate the potential of contrast enhancement (CE)-boost technique in the head and neck computed tomography (CT) angiography in terms of the objective and subjective image quality. Consecutive patients who underwent head and neck CT angiography between May 2022 and July 2022 were included. The CE-boost images were generated by combining the subtracted iodinated image and contrast-enhanced image. The objective image analysis was compared for each image with and without CE-boost technique using the CT attenuation, image noise, signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), and image sharpness (full width at half width maximum, FWHM). The subjective image analysis was evaluated by two independent experienced radiologists in the following aspects: the overall image quality, motion artifact, vascular delineation, and vessel sharpness. A total of 65 patients (mean age, 59.48 ± 13.71 years; range, 24-87 years; 36 women) were included. The CT attenuation of the vertebrobasilar arteries was significantly (p < 0.001) higher in the images obtained using CE-boost technique than in conventional images. Image noise was significantly (p < 0.001) lower for CE-boost images (6.09 ± 1.93) than for conventional images (7.79 ± 1.73). Moreover, CE-boost technique yielded higher SNR (64.43 ± 17.17 vs. 121.37 ± 38.77, p < 0.001) and CNR (56.90 ± 18.79 vs. 116.65 ± 57.44, p < 0.001) than conventional images. CE-boost resulted in shorter FWHM than conventional images (p < 0.001). Higher subjective image quality scores were also demonstrated by the CE-boost than images without CE-boost technique. In both objective and subjective image analysis, the CE-boost technique provided higher image quality without increasing the flow rate and concentration of contrast media in the head and neck CT angiography. Furthermore, the vessel completeness and delineation were superior in CE-boost images than in conventional images.

Diagnostic Accuracy of Ultrasound and Computed Tomography in Differentiating Transudate from Exudate in Patients with Pleural Effusion

Objective: To compare the diagnostic accuracy of Computed Tomography and Ultrasonography in differentiating trans-dative and exudative pleural effusion.&#x0D; Study Design: Cross-sectional study.&#x0D; Place and Duration of Study: Radiology Department of Pakistan Institute of Medical Sciences, Islamabad Pakistan, from Jul to Oct 2021.&#x0D; Methodology: Patients suffering (n=80) from pleural effusion were involved, and all were assessed with ultrasound and computed Tomography along with diagnostic thoracocentesis. In addition, we investigated pleural thickening, pleural nodules, and loculations along with the USG signs and Computed Tomography attenuation values to detect transudate and exudate in individuals suffering from pleural effusion.&#x0D; Results: Participants had a mean age of 36.20±6.67 years, ranging from 25 to 49 years. Out of 80 patients, 50(62.5 %) were males, and 30(37.5%) were females. Of the eighty patients with pleural effusion, 29 were transudative 36(25%), and 51 were exudative 63(75%). Overall, USG showed better results for loculations, while CT showed better results for pleural thickeningand nodules.&#x0D; Conclusion: Attenuation values of Computed Tomography play an essential role in differentiating the type of pleural effusion. In addition, ultrasound is a supporting non-invasive imaging modality that helps define the characteristics of pleural effusion.

Assessing the Effects of Deep Learning Reconstruction on Abdominal CT Without Arm Elevation.

Purpose: To evaluate the effects of deep learning reconstruction (DLR) on image quality of abdominal computed tomography (CT) in patients without arm elevation compared with hybrid-iterative reconstruction (Hybrid-IR) and filtered back projection (FBP). Methods: In this retrospective study, axial images of 26 patients who underwent CT without arm elevation were reconstructed using DLR, Hybrid-IR, and FBP. Streak artifact index (SAI) was calculated by dividing the standard deviation of CT attenuation in the liver or spleen by that in fat. Two other blinded radiologists evaluated streak artifacts on images (in the liver, spleen, and kidney), depiction of liver vessels, subjective image noise, and overall quality. They were also asked to detect space-occupying lesions other than cysts in the liver, spleen, and kidney. Results: The SAI (liver/spleen) in DLR images was significantly reduced compared with Hybrid-IR and FBP. Regarding qualitative image analysis, streak artifacts in the 3 organs, qualitative image noise, and overall quality in DLR images were rated by both readers as significantly improved compared with Hybrid-IR (P ≤ .012) and FBP (P < .001). Both blinded readers detected more lesions on DLR images than on Hybrid-IR and FBP ones. Conclusion: DLR resulted in significantly better-quality abdominal CT images in patients scanned without elevating their arms with reducing streak artifacts compared with Hybrid-IR and FBP.

Integration of coronary artery calcium scoring from CT attenuation scans by machine learning improves prediction of adverse cardiovascular events in patients undergoing SPECT/CT myocardial perfusion imaging

BackgroundMachine learning (ML) has been previously applied for prognostication in patients undergoing SPECT myocardial perfusion imaging (MPI). We evaluated whether including attenuation CT coronary artery calcification (CAC) scoring improves ML prediction of major adverse cardiovascular events (MACE) in patients undergoing SPECT/CT MPI. MethodsFrom the REFINE SPECT Registry 4770 patients with SPECT/CT performed at a single center were included (age: 64 ± 12 years, 45% female). ML algorithm (XGBoost) inputs were clinical risk factors, stress variables, SPECT imaging parameters, and expert-observer CAC scoring using CT attenuation correction scans performed to obtain CT attenuation maps. The ML model was trained and validated using tenfold hold-out validation. Receiver Operator Characteristics (ROC) curves were analyzed for prediction of MACE. MACE-free survival was evaluated with standard survival analyses. ResultsDuring a median follow-up of 24.1 months, 475 patients (10%) experienced MACE. Higher area under the ROC curve for MACE was observed with ML when CAC scoring was included (CAC-ML score, 0.77, 95% confidence interval [CI] 0.75–0.79) compared to ML without CAC (ML score, 0.75, 95% CI 0.73–0.77, P = .005) and when compared to CAC score alone (0.71, 95% CI 0.68–0.73, P < .001). Among clinical, imaging, and stress parameters, CAC score had highest variable importance for ML. On survival analysis patients with high CAC-ML score (> 0.091) had higher event rate when compared to patients with low CAC-ML score (hazard ratio 5.3, 95% CI 4.3–6.5, P < .001). ConclusionIntegration of attenuation CT CAC scoring improves the predictive value of ML risk score for MACE prediction in patients undergoing SPECT MPI.

Opportunistic screening for osteoporosis by abdominal CT in a British population

BackgroundIt has previously been shown that CT scans performed for other indications can be used to identify patients with osteoporosis. This has not yet been tested in a British population. We sought to evaluate the use of vertebral CT attenuation measures for predicting osteoporosis in a British cohort, using dual-energy X-ray absorptiometry (DEXA) as a reference standard.MethodsPatients who underwent abdominal CT in 2018 and concomitantly underwent DEXA within a six-month interval were retrospectively included. CT attenuation values in Hounsfield units (HU) were measured by placement of a region-of-interest at the central portion of the L1 vertebral body and then compared to their corresponding DEXA score. Receiver operating characteristic (ROC) curves were generated to evaluate the performance of a logistic regression model and to determine sensitivity and specificity thresholds.Results536 patients (394 females, mean age 65.8) were included, of which 174 had DEXA-defined osteoporosis. L1 attenuation measures were significantly different (p < 0.01) between the three DEXA-defined groups of osteoporosis (118 HU), osteopenia (143 HU) and normal bone density (178 HU). The area under the ROC curve was 0.74 (95% CI 0.69–0.78). A threshold of 169 HU was 90% sensitive, and a threshold of 104 HU was 90% specific for diagnosing osteoporosis.ConclusionsRoutine abdominal CT can be used to opportunistically screen for osteoporosis without additional cost or radiation exposure. The thresholds identified in this study are comparable with previous studies in other populations. We recommend radiologists engage with primary care and rheumatology providers to determine appropriate cut-off values for further investigation.

MP16-07 A NEW PREDICTOR FOR CALCIUM OXALATE STONES: IMPACT OF LINEAR CALCULUS DENSITY ON NON-CONTRAST COMPUTED TOMOGRAPHY

You have accessJournal of UrologyCME1 Apr 2023MP16-07 A NEW PREDICTOR FOR CALCIUM OXALATE STONES: IMPACT OF LINEAR CALCULUS DENSITY ON NON-CONTRAST COMPUTED TOMOGRAPHY Dae Young Jeon, Yoo Sub Shin, Jae Yong Jeong, Daeho Kim, Young Joon Moon, Dong Hyuk Kang, Won Sik Jeong, Hae Do Jung, Kang Su Cho, Young Deuk Choi, and Joo Yong Lee Dae Young JeonDae Young Jeon More articles by this author , Yoo Sub ShinYoo Sub Shin More articles by this author , Jae Yong JeongJae Yong Jeong More articles by this author , Daeho KimDaeho Kim More articles by this author , Young Joon MoonYoung Joon Moon More articles by this author , Dong Hyuk KangDong Hyuk Kang More articles by this author , Won Sik JeongWon Sik Jeong More articles by this author , Hae Do JungHae Do Jung More articles by this author , Kang Su ChoKang Su Cho More articles by this author , Young Deuk ChoiYoung Deuk Choi More articles by this author , and Joo Yong LeeJoo Yong Lee More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003236.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Non-contrast computed tomography (NCCT) is widely used to evaluate urinary stones. The CT attenuation, measured in Hounsfield units (HU), has been evaluated to predict stone characteristics. We proposed a novel predictor, linear calculus density (LCD), and analyzed variables from NCCT imaging to help diagnose calcium oxalate (CaOx) stones, which are common and challenging to fragment. METHODS: We retrospectively reviewed medical records of patients who had stone-related procedures or whose stone spontaneously passed between Dec 2014 and Feb 2017. Among those, 790 patients were included in the study. Based on the pre-treatment NCCT, the maximal stone length (MSL), mean stone density (MSD), and stone heterogeneity index (SHI) were obtained. In addition, the variation coefficient of stone density (VCSD=SHI/MSD×100) and linear calculus density (LCD= VCSD/MSL) were calculated. In accordance with the stone analysis, the patients were divided into two groups (CaOx and non-CaOx groups). The logistic regression model and ROC curve were used to develop a useful predictive model. This study was approved by the Ethical Committee. RESULTS: The number of patients with CaOx group was 335 and that of patients with non-CaOx group was 455. The mean MSL of CaOx group was shorter (9.8±7.0 vs. 19.5±61.8, p=0.001). In CaOx group, SHI, VCSD and LDS was higher than in non-CaOx group (all p<0.001) (Table 1). SHI (OR 1.002, 95% CI 1.001–1.004, p<0.001), VCSD (OR 1.028, 95% CI 1.016–1.041, p<0.001), and LCD (OR 1.352, 95% CI 1.270–1.444, p<0.001) were significant independent factors for CaOx stones in the logistic regression models. The areas under the ROC curve for predicting CaOx stones were 0.586 for SHI, 0.66 for VCSD, and 0.739 for LCD, with a cut-point of 2.25 (Figure 1). CONCLUSIONS: The LCD can be a useful new parameter to provide additional information to help discriminate CaOx stone before treatment. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e204 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Dae Young Jeon More articles by this author Yoo Sub Shin More articles by this author Jae Yong Jeong More articles by this author Daeho Kim More articles by this author Young Joon Moon More articles by this author Dong Hyuk Kang More articles by this author Won Sik Jeong More articles by this author Hae Do Jung More articles by this author Kang Su Cho More articles by this author Young Deuk Choi More articles by this author Joo Yong Lee More articles by this author Expand All Advertisement PDF downloadLoading ...

Association between High Pericoronary Adipose Tissue Computed Tomography Attenuation and Impaired Flow-Mediated Dilation of the Brachial Artery.

Pericoronary adipose tissue (PCAT) attenuation on coronary computed tomography angiography (CTA) is a noninvasive biomarker for pericoronary inflammation and is associated with cardiac mortality. We aimed to investigate the association between PCAT attenuation and endothelial dysfunction assessed using flow-mediated dilation (FMD). A total of 119 outpatients who underwent both coronary CTA and FMD measurements were examined. PCAT attenuation values were assessed at the proximal 40-mm segments of all three major coronary arteries on coronary CTA. Endothelial function was assessed using FMD. Patients were then classified into two groups: those with endothelial dysfunction (FMD ＜4%, n=44) and those without endothelial dysfunction (FMD ≥ 4%, n=75). In all three coronary arteries, PCAT attenuation was significantly higher in patients with endothelial dysfunction than in those without endothelial dysfunction. Multivariate logistic regression analysis revealed that PCAT attenuation in the right coronary artery (odds ratio [OR]=1.543; 95% confidence interval [CI]=1.004-2.369, p=0.048) and left anterior descending artery (OR=1.525, 95% CI=1.004-2.369, p=0.049) was an independent predictor of endothelial dysfunction. Subgroup analysis of patients with adverse CTA findings (significant stenosis and/or high-risk plaque) and those with coronary artery calcium score ＞100 showed that high PCAT attenuation in all three coronary arteries was a significant predictor of endothelial dysfunction. High PCAT attenuation was significantly associated with FMD-assessed endothelial dysfunction in patients with suspected coronary artery disease. Our results suggest that endothelial dysfunction is one of the pathophysiological mechanisms linking pericoronary inflammation to cardiac mortality.

Creeping mediastinal lymphangioma transgressing anatomical compartments: A rare case in an adult female patient.

Lymphangiomas, also known as lymphatic malformations, are rare non-neoplastic lesions of vascular origin showing lymphatic differentiation. These are most commonly reported in children within the neck and axillary region; however, mediastinum remains the commonest site in adults whereby diagnosis is usually incidental on imaging done for non-specific symptoms. Radiologically, these lesions are well-defined multicystic non-enhancing masses, with CT attenuation values ranging from simple to complex fluid and fat. Being benign, these mostly present clinically either due to mass effect exerted on structures, secondarily infected or developing intra lesion haemorrhage. We present a rare case of mediastinal lymphangioma with secondary hilar and intrapulmonary extension in a middle-aged female presenting with occasional haemoptysis and shortness of breath. The patient underwent thoracotomy with complete dissection of the mediastinal tumour, per operative Bleomycin administration in pulmonary component, and made subsequent uneventful post-operative recovery.

A comparison of the use of contrast media with different iodine concentrations for enhanced computed tomography.

Objective: In this study, we compared the enhancement of blood vessels and liver parenchyma on enhanced computed tomography (CT) of the upper abdomen with two concentrations of contrast media (400 and 300mg I/mL) based on similar iodine delivery rate (IDR) of 0.88 and 0.9g I/s and iodine load of 450mg I/kg. Methods: We randomly assigned 160 patients into two groups: iomeprol 400mg I/mL (A group) and iohexol 300mg I/mL (B group). The CT attenuation values of the main anatomical structures in the two groups with different scanning phases were measured and the image quality of the two groups was analyzed and compared. The peak pressure and local discomfort (including fever and pain) during contrast medium injection were recorded. Results: The mean attenuation value of the abdominal aorta was 313.6 ± 29.6 in the A group and 322.4 ± 30.1 in the B group during the late arterial phase (p = 0.8). Meanwhile, the mean enhancement values of the portal vein were 176.2 ± 19.3 and 165.9 ± 24.5 in the A and B groups, respectively, during the portal venous phase (p = 0.6). The mean CT values of liver parenchyma were 117.1 ± 15.3 and 108.8 ± 18.7 in the A and B groups, respectively, during the portal venous phase (p = 0.9). There was no statistical difference in image quality, peak injection pressure (psi), and local discomfort between the two groups (p > 0.05). Conclusion: When a similar IDR and the same iodine load are used, CT images with different concentrations of contrast media have the same subjective and objective quality, and can meet the diagnostic needs.

Dual-energy CT kidney stone characterization-can diagnostic accuracy be achieved at low radiation dose?

To assess the accuracy of low-dose dual-energy computed tomography (DECT) to differentiate uric acid from non-uric acid kidney stones in two generations of dual-source DECT with stone composition analysis as the reference standard. Patients who received a low-dose unenhanced DECT for the detection or follow-up of urolithiasis and stone extraction with stone composition analysis between January 2020 and January 2022 were retrospectively included. Collected stones were characterized using X-ray diffraction. Size, volume, CT attenuation, and stone characterization were assessed using DECT post-processing software. Characterization as uric acid or non-uric acid stones was compared to stone composition analysis as the reference standard. Sensitivity, specificity, and accuracy of stone classification were computed. Dose length product (DLP) and effective dose served as radiation dose estimates. A total of 227 stones in 203 patients were analyzed. Stone composition analysis identified 15 uric acid and 212 non-uric acid stones. Mean size and volume were 4.7mm × 2.8mm and 114 mm3, respectively. CT attenuation of uric acid stones was significantly lower as compared to non-uric acid stones (p < 0.001). Two hundred twenty-five of 227 kidney stones were correctly classified by DECT. Pooled sensitivity, specificity, and accuracy were 1.0 (95%CI: 0.97, 1.00), 0.93 (95%CI: 0.68, 1.00), and 0.99 (95%CI: 0.97, 1.00), respectively. Eighty-two of 84 stones with a diameter of ≤ 3mm were correctly classified. Mean DLP was 162 ± 57mGy*cm and effective dose was 2.43 ± 0.86mSv. Low-dose dual-source DECT demonstrated high accuracy to discriminate uric acid from non-uric acid stones even at small stone sizes. • Two hundred twenty-five of 227 stones were correctly classified as uric acid vs. non-uric acid stones by low-dose dual-energy CT with stone composition analysis as the reference standard. • Pooled sensitivity, specificity, and accuracy for stone characterization were 1.0, 0.93, and 0.99, respectively. • Low-dose dual-energy CT for stone characterization was feasible in the majority of small stones < 3mm.

Cationic Carrier Mediated Delivery of Anionic Contrast Agents in Low Doses Enable Enhanced Computed Tomography Imaging of Cartilage for Early Osteoarthritis Diagnosis.

Cartilage tissue exhibits early degenerative changes with onset of osteoarthritis (OA). Early diagnosis is critical as there is only a narrow time window during which therapeutic intervention can reverse disease progression. Computed tomography (CT) has been considered for cartilage imaging as a tool for early OA diagnosis by introducing radio-opaque contrast agents like ioxaglate (IOX) into the joint. IOX, however, is anionic and thus repelled by negatively charged cartilage glycosaminoglycans (GAGs) that hinders its intra-tissue penetration and partitioning, resulting in poor CT attenuation. This is further complicated by its short intra-tissue residence time owing to rapid clearance from joints, which necessitates high doses causing toxicity concerns. Here we engineer optimally charged cationic contrast agents based on cartilage negative fixed charge density by conjugating cartilage targeting a cationic peptide carrier (CPC) and multi-arm avidin nanoconstruct (mAv) to IOX, such that they can penetrate through the full thickness of cartilage within 6 h using electrostatic interactions and elicit similar CT signal with about 40× lower dose compared to anionic IOX. Their partitioning and distribution correlate strongly with spatial GAG distribution within healthy and early- to late-stage arthritic bovine cartilage tissues at 50-100× lower doses than other cationic contrast agents used in the current literature. The use of contrast agents at low concentrations also allowed for delineation of cartilage from subchondral bone as well as other soft tissues in rat tibial joints. These contrast agents are safe to use at current doses, making CT a viable imaging modality for early detection of OA and staging of its severity.

Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.

To evaluate image quality, diagnostic acceptability, and lesion conspicuity in abdominal dual-energy CT (DECT) using deep learning image reconstruction (DLIR) compared to those using adaptive statistical iterative reconstruction-V (Asir-V) at 50% blending (AV-50), and to identify potential factors impacting lesion conspicuity. The portal-venous phase scans in abdominal DECT of 47 participants with 84 lesions were prospectively included. The raw data were reconstructed to virtual monoenergetic image (VMI) at 50keV using filtered back-projection (FBP), AV-50, and DLIR at low (DLIR-L), medium (DLIR-M), and high strength (DLIR-H). A noise power spectrum (NPS) was generated. CT number and standard deviation values of eight anatomical sites were measured. Signal-to-noise (SNR), and contrast-to-noise ratio (CNR) values were calculated. Five radiologists assessed image quality in terms of image contrast, image noise, image sharpness, artificial sensation, and diagnostic acceptability, and evaluated the lesion conspicuity. DLIR further reduced image noise (p < 0.001) compared to AV-50 while better preserved the average NPS frequency (p < 0.001). DLIR maintained CT number values (p > 0.99) and improved SNR and CNR values compared to AV-50 (p < 0.001). DLIR-H and DLIR-M showed higher ratings in all image quality analyses than AV-50 (p < 0.001). DLIR-H provided significantly better lesion conspicuity than AV-50 and DLIR-M regardless of lesion size, relative CT attenuation to surrounding tissue, or clinical purpose (p < 0.05). DLIR-H could be safely recommended for routine low-keV VMI reconstruction in daily contrast-enhanced abdominal DECT to improve image quality, diagnostic acceptability, and lesion conspicuity. • DLIR is superior to AV-50 in noise reduction, with less shifts of the average spatial frequency of NPS towards low frequency, and larger improvements of NPS noise, noise peak, SNR, and CNR values. • DLIR-M and DLIR-H generate better image quality in terms of image contrast, noise, sharpness, artificial sensation, and diagnostic acceptability than AV-50, while DLIR-H provides better lesion conspicuity than AV-50 and DLIR-M. • DLIR-H could be safely recommended as a new standard for routine low-keV VMI reconstruction in contrast-enhanced abdominal DECT to provide better lesion conspicuity and better image quality than the standard AV-50.

Machine Learning for Opportunistic Screening for Osteoporosis and Osteopenia Using Knee CT Scans.

To predict whether a patient has osteoporosis/osteopenia using the attenuation of trabecular bone obtained from knee computed tomography (CT) scans. Retrospective analysis of 273 patients who underwent contemporaneous knee CT scans and dual-energy X-ray absorptiometry (DXA) within 1year. Volumetric segmentation of the trabecular bone of the distal femur, proximal tibia, patella, and proximal fibula was performed to obtain the bone CT attenuation. The data was randomly split into training/validation (78%) and test (22%) datasets and the performance in the test dataset were evaluated. The predictive properties of the CT attenuation of each bone to predict osteoporosis/osteopenia were assessed. Multivariable support vector machines (SVM) and random forest classifiers (RF) were used to predict osteoporosis/osteopenia. Patients with a mean age (range) of 67.9 (50-87) years, 85% female were evaluated. Seventy-seven (28.2%) of patients had normal bone mineral density (BMD), 140 (51.3%) had osteopenia, and 56 (20.5%) had osteoporosis. The proximal tibia had the best predictive ability of all bones and a CT attenuation threshold of 96.0 Hounsfield Units (HU) had a sensitivity of .791, specificity of .706, and area under the curve (AUC) of .748. The AUC for the SVM with cubic kernel classifier (AUC = .912) was better than the RF classifier (AUC = .683, P < .001) and better than using the CT attenuation threshold of 96.0 HU at the proximal tibia (AUC = .748, P = .025). Opportunistic screening for osteoporosis/osteopenia can be performed using knee CT scans. Multivariable machine learning models are more predictive than the CT attenuation of a single bone.

CT-measured hernia parameters can predict component separation: a cross-sectional study from China.

Currently, there are no reliable preoperative methods for predicting component separation (CS) during incisional hernia repair. By quantitatively measuring preoperative computed tomography (CT) imaging, we aimed to assess the value of hernia defect size, abdominal wall muscle quality, and hernia volume in predicting CS. The data of 102 patients who underwent open Rives-Stoppa retro-muscular mesh repair for midline incisional hernia between January 2019 and March 2022 were retrospectively analyzed. The patients were divided into two groups: ''CS group'' patients who required CS to attempt fascial closure, and ''non-CS'' group patients who required only Rives-Stoppa retro-muscular release to achieve fascial closure. Hernia defect width, hernia defect angle, rectus width, abdominal wall muscle area and CT attenuation, hernia volume (HV), and abdominal cavity volume (ACV) were measured on CT images. The rectus width to defect width ratio (RDR), HV/ACV, and HV/peritoneal volume (PV; i.e., HV + ACV) were calculated. Differences between the indices of the two groups were compared. Logistic regression models were applied to analyze the relationships between the above CT parameters and CS. Receiver operator characteristic (ROC) curves were generated to evaluate the potential utility of CT parameters in predicting CS. Of the102 patients, 69 were in the non-CS group and 33 were in the CS group. Compared with the non-CS group, hernia defect width (P < 0.001), hernia defect angle (P < 0.001), and hernia volume (P < 0.001) were larger in the CS group, while RDR (P < 0.001) was smaller. The abdominal wall muscle area in the CS group was slightly greater than that in the non-CS group (P = 0.046), and there was no significant difference in the CT attenuation of the abdominal wall muscle between the two groups (P = 0.089). Multivariate logistic regression identified hernia defect width (OR 1.815, 95% CI 1.428-2.308, P < 0.001), RDR (OR 0.018, 95% CI 0.003-0.106, P < 0.001), hernia defect angle (OR 1.077, 95% CI 1.042-1.114, P < 0.001), hernia volume (OR 1.002, 95% CI 1.001-1.003, P < 0.001), and CT attenuation of abdominal wall muscle (OR 0.962, 95% CI 0.927-0.998, P = 0.037) as independent predictors of CS. Hernia defect width was the best predictor for CS, with a cut-off point of 9.2cm and an area under the curve (AUC) of 0.890. The AUCs of RDR, hernia defect angle, hernia volume, and abdominal wall muscle CT attenuation were 0.843, 0.812, 0.747, and 0.572, respectively. Quantitative CT measurements are of great value for preoperative prediction of CS. Hernia defect size, hernia volume, and the CT attenuation of abdominal wall muscle are all preoperative predictive indicators of CS.

Diagnostic accuracy of plain computed tomography in detecting acute cerebral venous sinus thrombosis keeping magnetic resonance venography as gold standard.

To determine the diagnostic accuracy of plain computed tomography using the ratio between hounsfield unit and haematocrit of cerebral venous sinuses in cases of acute cerebral venous sinus thrombosis taking magnetic resonance venography as the gold standard. The cross-sectional validation study was conducted at the Department of Diagnostic Radiology, Combined Military Hospital, Rawalpindi, Pakistan, from March 9 to September 8, 2021, and comprised patients regardless of age and gender presenting with acute neurological and visual signs and symptoms of cerebral venous sinus thrombosis for <5 days. The patients were brain-imaged on 128-slice computed tomography scanner, and the image was assessed and the attenuation values in terms of Hounsfield unit of dural venous sinuses were calculated by taking appropriate region of interest. Haemoglobin and haematocrit values were noted from blood reports, and then the ratio between Hounsfield unit and haematocrit ratio was calculated. Magnetic resonance venography of the patients were performed and the patients were assessed for dural venous thrombosis. Data was analysed using SPSS 23. Of the 201 patients, 98(48.8%) were males and 103(51.2%) were female. The overall mean age was 35.32±19.707 years (range: 1 month-70 years). According to the Hounsfield unit-haematocrit ratio, acute cerebral venous sinus thrombosis was detected in 173(86.01%) patients, while magnetic resonance venography detected 178(88.6%). The Hounsfield unit-haematocrit ratio had sensitivity 91.01%, specificity 52.17% and diagnostic accuracy 86.57%. Computed tomography attenuation value and Hounsfield unit-haematocrit ratio on unenhanced computed tomography could be used as a reliable method to detect acute cerebral venous sinus thrombosis in emergency settings.

Quantitative parameters in novel spectral computed tomography: Assessment of Ki-67 expression in patients with gastric adenocarcinoma.

The level of Ki-67 expression has served as a prognostic factor in gastric cancer. The quantitative parameters based on the novel dual-layer spectral detector computed tomography (DLSDCT) in discriminating the Ki-67 expression status are unclear. To investigate the diagnostic ability of DLSDCT-derived parameters for Ki-67 expression status in gastric carcinoma (GC). Dual-phase enhanced abdominal DLSDCT was performed preoperatively in 108 patients with gastric adenocarcinoma. Primary tumor monoenergetic CT attenuation value at 40-100 kilo electron volt (kev), the slope of the spectral curve (λHU), iodine concentration (IC), normalized IC (nIC), effective atomic number (Zeff) and normalized Zeff (nZeff) in the arterial phase (AP) and venous phase (VP) were retrospectively compared between patients with low and high Ki-67 expression in gastric adenocarcinoma. Spearman's correlation coefficient was used to analyze the association between the above parameters and Ki-67 expression status. Receiver operating characteristic (ROC) curve analysis was performed to compare the diagnostic efficacy of the statistically significant parameters between two groups. Thirty-seven and 71 patients were classified as having low and high Ki-67 expression, respectively. CT40 kev-VP, CT70 kev-VP, CT100 kev-VP, and Zeff-related parameters were significantly higher, but IC-related parameters were lower in the group with low Ki-67 expression status than the group with high Ki-67 expression status, and other analyzed parameters showed no statistical difference between the two groups. Spearman's correlation analysis showed that CT40 kev-VP, CT70 kev-VP, CT100 kev-VP, Zeff, and nZeff exhibited a negative correlation with Ki-67 status, whereas IC and nIC had positive correlation with Ki-67 status. The ROC analysis demonstrated that the multi-variable model of spectral parameters performed well in identifying the Ki-67 status [area under the curve (AUC) = 0.967; sensitivity 95.77%; specificity 91.89%)]. Nevertheless, the differentiating capabilities of single-variable model were moderate (AUC value 0.630 - 0.835). In addition, the nZeff VP and nICVP (AUC 0.835 and 0.805) showed better performance than CT40 kev-VP, CT70 kev-VP and CT100 kev-VP (AUC 0.630, 0.631 and 0.662) in discriminating the Ki-67 status. Quantitative spectral parameters are feasible to distinguish low and high Ki-67 expression in gastric adenocarcinoma. Zeff and IC may be useful parameters for evaluating the Ki-67 expression.

Quantification of airway wall contrast enhancement on virtual monoenergetic images from spectral computed tomography

ObjectivesQuantitative computed tomography (CT) plays an increasingly important role in phenotyping airway diseases. Lung parenchyma and airway inflammation could be quantified by contrast enhancement at CT, but its investigation by multiphasic examinations is limited. We aimed to quantify lung parenchyma and airway wall attenuation in a single contrast-enhanced spectral detector CT acquisition.MethodsFor this cross-sectional retrospective study, 234 lung-healthy patients who underwent spectral CT in four different contrast phases (non-enhanced, pulmonary arterial, systemic arterial, and venous phase) were recruited. Virtual monoenergetic images were reconstructed from 40–160 keV, on which attenuations of segmented lung parenchyma and airway walls combined for 5th–10th subsegmental generations were assessed in Hounsfield Units (HU) by an in-house software. The spectral attenuation curve slope between 40 and 100 keV (λHU) was calculated.ResultsMean lung density was higher at 40 keV compared to that at 100 keV in all groups (p < 0.001). λHU of lung attenuation was significantly higher in the systemic (1.7 HU/keV) and pulmonary arterial phase (1.3 HU/keV) compared to that in the venous phase (0.5 HU/keV) and non-enhanced (0.2 HU/keV) spectral CT (p < 0.001). Wall thickness and wall attenuation were higher at 40 keV compared to those at 100 keV for the pulmonary and systemic arterial phase (p ≤ 0.001). λHU for wall attenuation was significantly higher in the pulmonary arterial (1.8 HU/keV) and systemic arterial (2.0 HU/keV) compared to that in the venous (0.7 HU/keV) and non-enhanced (0.3 HU/keV) phase (p ≤ 0.002).ConclusionsSpectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition, and may separate arterial and venous enhancement. Further studies are warranted to analyze spectral CT for inflammatory airway diseases.Key Points• Spectral CT may quantify lung parenchyma and airway wall enhancement with a single contrast phase acquisition.• Spectral CT may separate arterial and venous enhancement of lung parenchyma and airway wall.• The contrast enhancement can be quantified by calculating the spectral attenuation curve slope from virtual monoenergetic images.

Comparison of Deep-Learning Image Reconstruction With Hybrid Iterative Reconstruction for Evaluating Lung Nodules With High-Resolution Computed Tomography.

This study aimed to investigate the impact of deep-learning reconstruction (DLR) on the detailed evaluation of solitary lung nodule using high-resolution computed tomography (HRCT) compared with hybrid iterative reconstruction (hybrid IR). This retrospective study was approved by our institutional review board and included 68 consecutive patients (mean ± SD age, 70.1 ± 12.0 years; 37 men and 31 women) who underwent computed tomography between November 2021 and February 2022. High-resolution computed tomography images with a targeted field of view of the unilateral lung were reconstructed using filtered back projection, hybrid IR, and DLR, which is commercially available. Objective image noise was measured by placing the regions of interest on the skeletal muscle and recording the SD of the computed tomography attenuation. Subjective image analyses were performed by 2 blinded radiologists taking into consideration the subjective noise, artifacts, depictions of small structures and nodule rims, and the overall image quality. In subjective analyses, filtered back projection images were used as controls. Data were compared between DLR and hybrid IR using the paired t test and Wilcoxon signed-rank sum test. Objective image noise in DLR (32.7 ± 4.2) was significantly reduced compared with hybrid IR (35.3 ± 4.4) (P < 0.0001). According to both readers, significant improvements in subjective image noise, artifacts, depictions of small structures and nodule rims, and overall image quality were observed in images derived from DLR compared with those from hybrid IR (P < 0.0001 for all). Deep-learning reconstruction provides a better high-resolution computed tomography image with improved quality compared with hybrid IR.

Deep learning reconstruction with single-energy metal artifact reduction in pelvic computed tomography for patients with metal hip prostheses

PurposeThe aim of this study was to assess the impact of the deep learning reconstruction (DLR) with single-energy metal artifact reduction (SEMAR) (DLR-S) technique in pelvic helical computed tomography (CT) images for patients with metal hip prostheses and compare it with DLR and hybrid iterative reconstruction (IR) with SEMAR (IR-S).Materials and methodsThis retrospective study included 26 patients (mean age 68.6 ± 16.6 years, with 9 males and 17 females) with metal hip prostheses who underwent a CT examination including the pelvis. Axial pelvic CT images were reconstructed using DLR-S, DLR, and IR-S. In one-by-one qualitative analyses, two radiologists evaluated the degree of metal artifacts, noise, and pelvic structure depiction. In side-by-side qualitative analyses (DLR-S vs. IR-S), the two radiologists evaluated metal artifacts and overall quality. By placing regions of interest on the bladder and psoas muscle, the standard deviations of their CT attenuation were recorded, and the artifact index was calculated based on them. Results were compared between DLR-S vs. DLR and DLR vs. IR-S using the Wilcoxon signed-rank test.ResultsIn one-by-one qualitative analyses, metal artifacts and structure depiction in DLR-S were significantly better than those in DLR; however, between DLR-S and IR-S, significant differences were noted only for reader 1. Image noise in DLR-S was rated as significantly reduced compared with that in IR-S by both readers. In side-by-side analyses, both readers rated that the DLR-S images are significantly better than IR-S images regarding overall image quality and metal artifacts. The median (interquartile range) of the artifact index for DLR-S was 10.1 (4.4–16.0) and was significantly better than those for DLR (23.1, 6.5–36.1) and IR-S (11.4, 7.8–17.9).ConclusionDLR-S provided better pelvic CT images in patients with metal hip prostheses than IR-S and DLR.

A quantitative clinical evaluation of simultaneous reconstruction of attenuation and activity in time-of-flight PET

BackgroundThe maximum likelihood activity and attenuation (MLAA) reconstruction algorithm has been proposed to jointly estimate tracer activity and attenuation at the same time, and proven to be a promising solution to the CT attenuation correction (CT-AC) artifacts in PET images. This study aimed to perform a quantitative evaluation and clinical validation of the MLAA method.MethodsA uniform cylinder phantom filled with 18F-FDG solution was scanned to optimize the reconstruction parameters for the implemented MLAA algorithm. 67 patients who underwent whole-body 18F-FDG PET/CT scan were retrospectively recruited. PET images were reconstructed using MLAA and clinical standard OSEM algorithm with CT-AC (CT-OSEM). The mean and maximum standardized uptake values (SUVmean and SUVmax) in regions of interest (ROIs) of organs, high uptake lesions and areas affected by metal implants and respiration motion artifacts were quantitatively analyzed.ResultsIn quantitative analysis, SUVs in patient’s organ ROIs between two methods showed R2 ranging from 0.91 to 0.98 and k ranging from 0.90 to 1.06, and the average SUVmax and SUVmean differences between two methods were within 10% range, except for the lung ROI, which was 10.5% and 16.73% respectively. The average SUVmax and SUVmean differences of a total of 117 high uptake lesions were 7.25% and 7.10% respectively. 20 patients were identified to have apparent respiration motion artifacts in the liver in CT-OSEM images, and the SUVs differences between two methods measured at dome of the liver were significantly larger than measured at middle part of the liver. 10 regions with obvious metal artifacts were identified in CT-OSEM images and the average SUVmean and SUVmax differences in metal implants affected regions were reported to be 52.90% and 56.20% respectively.ConclusionsPET images reconstructed using MLAA are clinically acceptable in terms of image quality as well as quantification and it is a useful tool in clinical practice, especially when CT-AC may cause respiration motion and metal artifacts. Moreover, this study also provides technical reference and data support for the future iteration and development of PET reconstruction technology of SUV accurate quantification.