The application value of a vendor-specific deep learning image reconstruction algorithm in "triple low" head and neck computed tomography angiography.

Background: Head and neck computed tomography angiography (CTA) technology has become the noninvasive imaging method of choice for the diagnosis and long-term follow-up of vascular lesions of the head and neck. However, issues of radiation safety and contrast nephropathy associated with CTA examinations remain concerns. In recent years, deep learning image reconstruction (DLIR) algorithms have been increasingly used in clinical studies, demonstrating their potential for dose optimization. This study aimed to investigate the value of using a DLIR algorithm to reduce radiation and contrast doses in head and neck CTA. Methods: A total of 100 patients were prospectively enrolled and randomly divided into two groups. Group A (50 patients) consisted of those who underwent 70-kVp CTA with a low contrast volume and injection rate and who were classified according to the reconstruction algorithm into subgroups A1 [DLIR at high weighting (DLIR-H)], A2 [DLIR at low weighting (DLIR-L)], and A3 [volume-based adaptive statistical iterative reconstruction with 50% weighting (ASIR-V50%)]. Meanwhile, group B (50 patients) consisted of those who underwent standard radiation and contrast doses at 100 kVp with ASIR-V50% reconstruction. The computed tomography (CT) attenuation, background noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective image quality score (SIQS) were statistically compared for several vessels among the four groups. Results: Group A showed significant reductions in contrast dosage, injection rate, and radiation dose of 36.09%, 20.88%, and 47.80%, respectively, compared to group B (all P<0.001). The four groups differed significantly in terms of background noise (all P<0.05) with group A1 having the lowest value. Group A1 also had significantly higher SNR and CNR values compared to group B in all vessels (all P<0.05) except the M1 of the middle cerebral artery for the SNR. Group A1 also had the highest SIQS, followed by the A2, B, and A3 groups. The SIQS showed good agreement between the two reviewers in all groups, with κ values between 0.88 and 1. Conclusions: Compared to the standard-dose protocol using 100 kVp and ASIR-V50%, a protocol of 70 kVp combined with DLIR-H significantly reduces the radiation dose, contrast dose, and injection rate in head and neck CTA while still significantly improving image quality for patients with a standard body size.

Reference values of normal abdominal aortic areas in Chinese population measured by contrast-enhanced computed tomography.

Objective: To generate reference values of the normal areas of the abdominal aorta at various levels among Chinese people and to explore the factors that may promote the expansion of the abdominal aorta. Methods: The areas of normal abdominal aortas were gauged at various levels based on inner-to-inner measurements in 1,066 Chinese adult patients (>18 years) without the abdominal aortic disease. The areas of subphrenic abdominal, suprarenal abdominal, infrarenal abdominal, and distal abdominal aortas were measured. The demographic and clinical characteristics were collected into a specifically designed electronic database. Multivariable linear regression was used to analyze the potential risk factors promoting the expansion of the abdominal aorta. Results: In males, the median areas of the subphrenic abdominal aorta, suprarenal abdominal aorta, infrarenal abdominal aorta, and distal abdominal aorta were 412.1, 308.0, 242.2, and 202.2 mm2, respectively. In females, the median areas of the subphrenic abdominal aorta, suprarenal abdominal aorta, infrarenal abdominal aorta, and distal abdominal aorta were 327.7, 243.4, 185.4, and 159.6 mm2, respectively. The areas of the abdominal aorta at different levels were larger in males than in females and increased with age. Multiple linear stepwise regression analysis showed that the subphrenic abdominal aortic area was significantly related to age (ß = 0.544, p < 0.001), sex (ß = 0.359, p < 0.001), and hypertension (ß = 0.107, p < 0.001). Suprarenal abdominal aortic area was related to age (ß = 0.398, p < 0.001), sex (ß = 0.383, p < 0.001), history of smoking (ß = 0.074, p = 0.005), and hypertension (ß = 0.111, p < 0.001). The infrarenal abdominal aortic area was correlated with age (ß = 0.420, p < 0.001), sex (ß = 0.407, p < 0.001), and history of smoking (ß = 0.055, p = 0.036). The distal abdominal aortic area was correlated with age (ß = 0.463, p < 0.001), sex (ß = 0.253, p < 0.001), and hypertension (ß = 0.073, p = 0.013). Conclusion: The abdominal aortic areas at different levels were larger in males than in females. Aging, hypertension, and smoking prompt the expansion of abdominal aorta.

Apparent diffusion coefficient value of diffusion-weighted imaging for differential diagnosis of ductal carcinoma in situ and infiltrating ductal carcinoma.

PURPOSE: The present meta-analysis investigated the clinical value of apparent diffusion coefficient (ADC) values in diffusion-weighted imaging (DWI) for differential diagnosis of ductal carcinoma in situ (DCIS) and infiltrating ductal carcinoma (IDC). MATERIALS AND METHODS: Electronic databases searches were employed to identify relevant scientific literature, and the search results were screened to selected high-quality studies for this meta-analysis. Methodological quality of the enrolled studies was evaluated by quality evaluation of diagnostic accuracy studies (QUADAS). Summary odds ratios (ORs) and its corresponding 95% confidence interval (95% CI) were calculated for DCIS versus IDC category of ADC value using Z test. RESULTS: Our meta-analysis contained a combined total of 1,097 subjects (928 patients with IDC and 169 patients with DCIS) from 9 relevant high-quality cohort studies. Pooled ORs demonstrated that ADC value in IDC patients was significantly lower than DCIS patients. Subgroup analysis stratified by ethnicity indicated a higher ADC value in DCIS patients compared to IDC, in Asian population, but not in Caucasians. Magnetic resonance imaging (MRI) machine type-stratified analysis revealed that the ADC value of DWI obtained from both non- General Electric Company (GE) 1.5T and GE 1.5T machines were highly reliable in the differential diagnosis of DCIS and IDC. CONCLUSION: Our meta-analysis provides evidence that ADC values in DWI accurately conveys the differences in tumor architecture between IDC and DCIS, which has high clinical value in differentiatal diagnosis of IDC and DCIS. This may lead to improved BC prediction and treatment.