Journal of Computer Assisted Tomography最新文献

Objective: The purpose of this study is to explore the impact of deep learning image reconstruction (DLIR) algorithm on the quantification of radiomic features in ultra-low-dose computed tomography (ULD-CT) compared with adaptive statistical iterative reconstruction-Veo (ASIR-V).

Methods: One hundred eighty-three patients with pulmonary nodules underwent standard-dose computed tomography (SDCT) (4.30 ± 0.36 mSv) and ULD-CT (UL-A, 0.57 ± 0.09 mSv or UL-B, 0.33 ± 0.04 mSv). SDCT was the reference standard using (ASIR-V) at 50% strength (50%ASIR-V). ULD-CT was reconstructed with 50%ASIR-V, DLIR at medium and high strength (DLIR-M, DLIR-H). Radiomics analysis extracted 102 features, and the intraclass correlation coefficient (ICC) quantified reproducibility between ULD-CT and SDCT reconstructed by 50%ASIR-V, DLIR-M, and DLIR-H for each feature.

Results: Among 102 radiomic features, the percentages of reproducibility of 50%ASIR-V, DLIR-M, and DLIR-H were 48.04% (49/102), 49.02% (50/102), and 52.94% (54/102), respectively. Shape and first order features demonstrated high reproducibility across different reconstruction algorithms and radiation doses, with mean ICC values exceeding 0.75. In texture features, DLIR-M and DLIR-H showed improved mean ICC values for pure ground glass nodules (pGGNs) from 0.69 ± 0.23 to 0.75 ± 0.18 and 0.81 ± 0.12, respectively, compared with 50%ASIR-V. Similarly, the mean ICC values for solid nodules (SNs) increased from 0.60 ± 0.19 to 0.66 ± 0.14 and 0.69 ± 0.13, respectively. Additionally, the mean ICC values of texture features for pGGNs and SNs in both ULD-CT groups decreased with reduced radiation dose.

Conclusions: DLIR can improve the reproducibility of radiomic features at ultra-low doses compared with ASIR-V. In addition, pGGNs showed better reproducibility at ultra-low doses than SNs.

Objective: To investigate the relationship between craniocervical morphology and the presence and level of cervical facet joint degeneration (FJD).

Methods: A total of 108 consecutive female patients aged 45-55 years who had undergone neck + brain CT angiography were included in this retrospective sectional study. Only patients of a certain age and of the same gender were included in order to eliminate the differences that create a disposition to the development of spinal degeneration. The presence of facet joint (FJ) arthritis (grade ≥2 degeneration in at least one affected facet joint) and the grade of the facet joint degeneration for each patient were recorded. A total of 20 lengths and 3 angles of craniocervical morphology were measured. The differences between the individuals with and without FJ arthritis were investigated with the independent-sample t test, and the relationship between the FJD grade and craniocervical morphology was investigated using the Spearman correlation test.

Results: Individuals with FJ arthritis were found to have longer Grabb-Oakes measurement, shorter FM AP length, lower ADI, lower EOP thickness, higher clivus length, higher crista gall-ATS distance, lower CCA angle, lower distance between the C1 vertebra lateral masses, and higher BAI than those without FJ arthritis (P ˂ 0.05). Besides, we found that the FJD grade increased as the Grabb-Oakes measurement increased, ADI distance decreased, FM AP length decreased, EOP thickness decreased, clivus length increased, basal angle increased, distance between the C1 vertebra lateral masses decreased, and BAI increased (P ˂ 0.05).

Conclusions: Differences in craniocervical morphology are statistically associated with degenerative processes that result in degenerative changes in the facet joint. Therefore, some morphological changes in craniocervical anatomy cause changes in the momentum and distribution of the load on the facet joints, predisposing the patient to facet arthropathy and osteoarthritis.

Objective: To evaluate the image quality and diagnostic performance of pulmonary subsolid nodules on conventional iterative algorithms, virtual monoenergetic images (VMIs), and electron density mapping (EDM) using a dual-layer detector spectral CT (DLSCT).

Methods: This retrospective study recruited 270 patients who underwent DLSCT scan for lung nodule screening or follow-up. All CT examinations with subsolid nodules (pure ground-glass nodules [GGNs] or part-solid nodules) were reconstructed with hybrid and model-based iterative reconstruction, VMI at 40, 70, 100, and 130 keV levels, and EDM. The CT number, objective image noise, signal-to-noise ratio, contrast-to-noise ratio, diameter, and volume of subsolid nodules were measured for quantitative analysis. The overall image quality, image noise, visualization of nodules, artifact, and sharpness were subjectively rated by 2 thoracic radiologists on a 5-point scale (1 = unacceptable, 5 = excellent) in consensus. The objective image quality measurements, diameter, and volume were compared among the 7 groups with a repeated 1-way analysis of variance. The subjective scores were compared with Kruskal-Wallis test.

Results: A total of 198 subsolid nodules, including 179 pure GGNs, and 19 part-solid nodules were identified. Based on the objective analysis, EDM had the highest signal-to-noise ratio (164.71 ± 133.60; P < 0.001) and contrast-to-noise ratio (227.97 ± 161.96; P < 0.001) among all image sets. Furthermore, EDM had a superior mean subjective rating score (4.80 ± 0.42) for visualization of GGNs compared to other reconstructed images (all P < 0.001), although the model-based iterative reconstruction had superior subjective scores of overall image quality. For pure GGNs, the measured diameter and volume did not significantly differ among different reconstructions (both P > 0.05).

Conclusions: EDM derived from DLSCT enabled improved image quality and lesion conspicuity for the evaluation of lung subsolid nodules compared to conventional iterative reconstruction algorithms and VMIs.

Background: The present study aims to evaluate the postprocessing image quality of a deep-learning (DL)-based automatic bone removal algorithm in the real clinical practice for cervical computed tomography angiography (CTA).

Materials and methods: A total of 100 patients (31 females, 61.4 ± 12.4 years old) who had performed cervical CTA from January 2022 to July 2022 were included retrospectively. Three different types of scanners were used. Ipsilateral cervical artery was divided into 10 segments. The performance of the DL algorithm and conventional algorithm in terms of bone removal and vascular integrity was independently evaluated by two radiologists for each segment. The difference in the performance between the two algorithms was compared. Inter- and intrarater consistency were assessed, and the correlation between the degree of carotid artery stenosis and the rank of bone removal and vascular integrity was analyzed.

Results: Significant differences were observed in the rankings of bone removal and vascular integrity between the two algorithms on most segments on both sides. Compared to DL algorithm, the conventional algorithm showed a higher correlation between the degree of carotid artery stenosis and vascular integrity (r = -0.264 vs r = -0.180). The inter- and intrarater consistency of DL algorithm were found to be higher than or equal to those of conventional algorithm.

Conclusions: The DL algorithm for bone removal in cervical CTA demonstrated significantly better performance than conventional postprocessing method, particularly in the segments with complex anatomical structures and adjacent to bone.

Objective: The objectives of this research were to assess the effectiveness of computer-assisted detection reading (CADR) and structured reports in monitoring patients with multiple sclerosis (MS) and to evaluate the role of radiology technicians in this context.

Methods: Eighty-seven patients with MS who underwent at least 2 sequential magnetic resonance imaging (MRI) follow-ups analyzed by 2 radiologists and a technician. Progression of disease (POD) was identified through the emergence of T2 fluid-attenuated inversion recovery white matter hyperintensities or contrast enhancements and evaluated both qualitatively (progression vs stability) and quantitatively (count of new white matter hyperintensities).

Results: CADR increased the accuracy by 11%, enhancing interobserver consensus on qualitative progression and saving approximately 2 minutes per examination. Although structured reports did not improve these metrics, it may improve clinical communication and permit technicians to achieve approximately 80% accuracy in MRI readings.

Conclusions: The use of CADR improves the accuracy, agreement, and interpretation time in MRI follow-ups of MS. With the help of computer tools, radiology technicians could represent a significant aid in the follow-up of these patients.

Purpose: Clinical research has shown unique tumor behavioral characteristics of BRCA-associated protein-1- (BAP1-) and fibroblast growth factor receptor (FGFR)-mutated intrahepatic cholangiocarcinomas (CCAs), with BAP1-mutated tumors demonstrating more aggressive forms of disease and FGFR-altered CCAs showing more indolent behavior. We performed a retrospective case-control study to evaluate for unique imaging features associated with BAP1 and FGFR genomic markers in intrahepatic CCA (iCCA).

Methods: Multiple imaging features of iCCA at first staging were analyzed by 2 abdominal radiologists blinded to genomic data. Growth and development of metastases at available follow-up imaging were also recorded, as were basic clinical cohort data. Types of iCCA analyzed included those with BAP1, FGFR, or both alterations, as well as cases with low mutational burden or mutations with low clinical impact, which served as a control or "wild-type" group. There were 18 cases in the FGFR group, 10 with BAP1 mutations, and 31 wild types (controls).

Results: Cases with BAP1 mutations showed significantly larger growth at first year of follow-up (P = 0.03) and more frequent tumor-associated biliary ductal dilatation (P = 0.04) compared with controls. FGFR-altered cases showed more infiltrative margins compared with controls (P = 0.047) and demonstrated less enhancement between arterial to portal venous phases (P = 0.02). BAP1 and FGFR groups had more cases with stage IV disease at presentation than controls (P = 0.025, P = 0.006).

Conclusion: Compared with wild-type iCCAs, FGFR-mutated tumors often demonstrate infiltrative margins, and BAP1 tumors show increased biliary ductal dilatation at presentation. BAP1-mutated cases had significantly larger growth at first-year restaging.

Objective: To evaluate the effect of volumetric analysis on the diagnosis and management of indeterminate solid pulmonary nodules in routine clinical practice.

Methods: This was a retrospective study with 107 computed tomography (CT) cases of solid pulmonary nodules (range, 6-15 mm), 57 pathology-proven malignancies (lung cancer, n = 34; metastasis, n = 23), and 50 benign nodules. Nodules were evaluated on a total of 309 CT scans (average number of CTs/nodule, 2.9 [range, 2-7]). CT scans were from multiple institutions with variable technique. Nine radiologists (attendings, n = 3; fellows, n = 3; residents, n = 3) were asked their level of suspicion for malignancy (low/moderate or high) and management recommendation (no follow-up, CT follow-up, or care escalation) for baseline and follow-up studies first without and then with volumetric analysis data. Effect of volumetry on diagnosis and management was assessed by generalized linear and logistic regression models.

Results: Volumetric analysis improved sensitivity (P = 0.009) and allowed earlier recognition (P < 0.05) of malignant nodules. Attending radiologists showed higher sensitivity in recognition of malignant nodules (P = 0.03) and recommendation of care escalation (P < 0.001) compared with trainees. Volumetric analysis altered management of high suspicion nodules only in the fellow group (P = 0.008). κ Statistics for suspicion for malignancy and recommended management were fair to substantial (0.38-0.66) and fair to moderate (0.33-0.50). Volumetric analysis improved interobserver variability for identification of nodule malignancy from 0.52 to 0.66 (P = 0.004) only on the second follow-up study.

Conclusions: Volumetric analysis of indeterminate solid pulmonary nodules in routine clinical practice can result in improved sensitivity and earlier identification of malignant nodules. The effect of volumetric analysis on management recommendations is variable and influenced by reader experience.

Objective: This study aimed to investigate whether virtual monoenergetic images (VMIs) can aid radiologists and surgeons in better identifying the arc of Riolan (AOR) and to determine the optimal kilo electron volt (keV) level.

Methods: Thirty-three patients were included. Conventional images (CIs) and VMI (40-100 keV) were reconstructed using arterial phase spectral-based images. The computed tomography (CT) attenuation and noise of the AOR, the CT attenuation of the erector spinal muscle, and the background noise on VMI and CI were measured, respectively. The signal-to-noise ratio, contrast-to-noise ratio (CNR), and signal intensity ratio were calculated. The image quality of the AOR was evaluated according to a 4-point Likert grade.

Results: The CT attenuation, noise, CNR, and signal intensity ratio of the AOR were significantly higher in VMI at 40 and 50 keV compared with CI ( P < 0.001); VMI at 40 keV was significantly higher than 50 keV ( P < 0.05). No significant difference in signal-to-noise ratio, background noise, and CT attenuation of the spinal erector muscle was observed between VMI and CI ( P > 0.05). virtual monoenergetic image at 40 keV produced the best subjective scores.

Conclusions: Virtual monoenergetic image at 40 keV makes it easier to observe the AOR with optimized subjective and objective image quality. This may prompt radiologists and surgeons to actively search for it and encourage surgeons to preserve it during splenic flexure takedown.

Abstract: Neuroendocrine tumors (NETs) are relatively uncommon heterogeneous neoplasms arising from endocrine and neuronal origin cells showing highly variable clinical behavior. By the time these tumors are discovered, up to 14% of patients with histologically proven NETs have metastasis, with the liver as the most frequently affected organ. Sometimes, no known primary site can be identified via routine imaging. Neuroendocrine tumors of unknown origin carry a poorer prognosis (compared with metastatic NETs with a known primary site) because of a lack of tailored surgical intervention and appropriate medical therapy (eg, chemotherapy or targeted therapy). A multimethod approach is frequently used in the trial to accurately determine the primary site for NETs of unknown primary sites and may include clinical, laboratory, radiological, histopathological, and surgical data. New molecular techniques using the genomic approach to identify the molecular signature have shown promising results. Various imaging modalities include ultrasound, computed tomography (CT), dual-energy CT, magnetic resonance imaging, and functional and hybrid imaging (positron emission tomography/CT, positron emission tomography/magnetic resonance imaging); somatostatin receptor imaging with new tracers is frequently used in an attempt for localization of the primary site.