Detectability of the artery of Adamkiewicz on computed tomography angiography of the aorta by using ultra-high-resolution computed tomography

Improvement of Neurovascular Imaging Using Ultra-High-Resolution Computed Tomography Angiography

OBJECTIVE

To evaluate diagnostic image quality of ultra-high-resolution computed tomography angiography (UHR-CTA) in neurovascular imaging as compared to normal resolution CT-angiography (NR-CTA).

MATERIAL AND METHODS

In this retrospective single-center study brain and neck CT-angiography was performed using an ultra-high-resolution computed tomography scanner (n = 82) or a normal resolution CT scanner (NR-CTA; n = 73). Ultra-high-resolution images were reconstructed with a 1024 × 1024 matrix and a slice thickness of 0.25 mm, whereas NR-CT images were reconstructed with a 512 × 512 matrix and a slice thickness of 0.5 mm. Three blinded neuroradiologists assessed overall image quality, artifacts, image noise, overall contrast and diagnostic confidence using a 4-point Likert scale. Furthermore, the visualization and delineation of supra-aortic arteries with an emphasis on the visualization of small intracerebral vessels was assessed using a cerebral vascular score, also utilizing a 4-point Likert scale. Quantitative analyses included signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), noise and the steepness of gray value transition. Radiation exposure was determined by comparison of computed tomography dose index (CTDIvol), dose length product (DLP) and mean effective dose. Interrater agreement was evaluated via determining Fleiss-Kappa.

RESULTS

Ultra-high-resolution CT-angiography (UHR-CTA) yielded excellent image quality with superior quantitative (SNR: p < 0.001, CNR: p < 0.001, steepness of gray value transition: p < 0.001) and qualitative results (overall image quality: 4 (Inter quartile range (IQR) = 4-4); p < 0.001, diagnostic confidence: 4 (IQR = 4-4); p < 0.001) compared to NR-CT (overall image quality: 3 (IQR = 3-3), diagnostic confidence: 3 (IQR = 3-4)). Furthermore, UHR-CT enabled significantly superior delineation and visualization of all vascular segments, from proximal extracranial vessels to the smallest peripheral cerebral branches (e.g.

, UHR-CTA PICA

4 (3-4) vs. NR-CTA PICA: 3 (2-3); UHR-CTA P4: 4 (IQR = 3-4) vs. NR-CTA P4: 2 (IQR = 2-3); UHR-CTA M4: 4 (IQR = 4-4) vs. NR-CTA M4: 3 (IQR = 2-3); UHR-CTA A4: 4 (IQR = 3-4) vs. NR-CTA A4: 2 (IQR = 2-3); all p < 0.001). Noteworthy, a reduced mean effective dose was observed when applying UHR-CT (NR-CTA: 1.8 ± 0.3 mSv; UHR-CTA: 1.5 ± 0.5 mSv; p < 0.001).

CONCLUSION

Ultra-high-resolution CT-angiography improves image quality in neurovascular imaging allowing the depiction and evaluation of small peripheral cerebral arteries. It may thus improve the detection of pathologies in small cerebrovascular lesions and the resulting diagnosis.

Effect of Low Tube Voltage (100 kV) Combined with ASIR-V on the Visualization and Image Quality of the Adamkiewicz Artery: A Comparison with 120 kV Protocol

OBJECTIVE

To evaluate the effect of low tube voltage (100 kV) combined with adaptive statistical iterative reconstruction-V (ASIR-V) on the visualization and image quality of the Adamkiewicz artery (AKA).

METHODS

One hundred patients were prospectively enrolled and randomly assigned into two groups (both n = 50). Group A (100 kV) was reconstructed with filtered back projection (FBP) and ASIR-V from 10% to 100% with 10% intervals. Group B (120 kV) was only reconstructed with FBP. The objective image quality was evaluated by using CT values of the aorta (CTAorta), background noise, signal-to-noise ratio of the descending aorta (SNRAorta), and contrast-to-noise ratio of the spinal cord (CNRSpinal cord). The subjective image quality and visualization scores of the AKA were assessed on a 5-point scale.

RESULTS

CTAorta was significantly higher in Group A than in Group B (p < 0.001). When ASIR-V weights were ≥60%, significant differences were found in the background noise, SNRAorta, and CNRSpinal cord between the two groups (all p < 0.05). In Group A, compared with FBP, the subjective score gradually increased as ASIR-V increased to 80%, which decreased when ASIR-V exceeded 80%. The visualization scores of the AKA (≥60%) and the ability to detect vessel continuity (≥80%) gradually increased as the ASIR-V weights increased (p < 0.05). The effective radiation dose was reduced by about 40.36% in Group A compared to Group B.

CONCLUSIONS

compared with conventional scanning protocol, using a combination of low tube voltage (100 kV) and 80% ASIR-V protocol could not only increase the visualization of the AKA, but also improve image quality and reduce the radiation doses.

Preoperative Spinal Angiography for Thoracic Neuroblastoma: Impact of Identification of the Adamkiewicz Artery on Gross Total Resection and Neurological Sequelae

BACKGROUND

Patients with thoracic neuroblastoma (TNB) are at high risk of postoperative neurologic complications due to iatrogenic lesions of the artery of Adamkiewicz (AKA). The role of performing a preoperative spinal angiography (POSA) in these patients must be clarified. The present study sought to further understand the relationship between POSA and TNB, as well as the effects of identifying the AKA on surgical excision and neurological consequences.

METHODS

Data from patients with TNB who underwent POSA between November 2015 and February 2022 at our tertiary pediatric center were retrospectively analyzed.

RESULTS

Six patients were identified, five of whom (83%) were considered eligible for surgical excision. Gross total resection (GTR) was achieved in three patients (60%), which included two patients with an AKA contralateral to the tumor, and one with an homolateral AKAl. After a median follow-up of 4.1 years from diagnosis, no patients developed neurological complications; five (83%) were alive and well, and one died from refractory recurrence.

CONCLUSIONS

Among patients with TNB, POSA was useful for identifying the AKA and defining the optimal surgical strategy. POSA should be considered in the preoperative evaluation of TNB to increase the likelihood of GTR and reduce the threats of iatrogenic neurologic sequelae.

Impact of a new deep-learning-based reconstruction algorithm on image quality in ultra-high-resolution CT: clinical observational and phantom studies

OBJECTIVES

To demonstrate the effect of an improved deep learning-based reconstruction (DLR) algorithm on Ultra-High-Resolution Computed Tomography (U-HRCT) scanners.

METHODS

Clinical and phantom studies were conducted. Thirty patients who underwent contrast-enhanced CT examination during the follow-up period were enrolled. Images were reconstructed using improved DLR [termed, New DLR, i.e., Advanced Intelligent Clear-IQ Engine (AiCE) Body Sharp] and conventional DLR (Conv DLR, AiCE Body) algorithms. Two radiologists assessed the overall image quality using a 5-point scale (5 = excellent; 1 = unacceptable). The noise power spectra (NPSs) were calculated to assess the frequency characteristics of the image noise, and the square root of area under the curve (√AUC NPS) between 0.05 and 0.50 cycle/mm was calculated as an indicator of the image noise. Dunnett's test was used for statistical analysis of the visual evaluation score, with statistical significance set at p < 0.05.

RESULTS

The overall image quality of New DLR was better than that of the Conv DLR (4.2 ± 0.4 and 3.3 ± 0.4, respectively; p < 0.0001). All New DLR images had an overall image quality score above the average or excellent. The √AUCNPS value of New DLR was lower than that of Conv DLR (13.8 and 14.2, respectively). The median values of reconstruction time required with New DLR and Conv DLR were 5.0 and 7.8 min, respectively.

CONCLUSIONS

The new DLR algorithm improved the image quality within a practical reconstruction time.

ADVANCES IN KNOWLEDGE

The new DLR enables us to choose whether to improve image quality or reduce the dose.

Postpartum Spinal Cord Infarction: A Case Report and Review of the Literature

Background: Postpartum spinal cord infarction is a very rare disease. Only two cases have been reported in the English literature. Methods: We reported a 26 year old female who received second doses of the mRNA-1273 vaccine 52 days before delivery. She presented as sudden onset of paraplegia, sensory level, and sphincter incontinence at postpartum period. No history of heparin exposure was noted. Imaging findings confirmed the T10-11 level infarction and her anti-human heparin platelet factor 4 (anti-PF4) antibody was positive. After 7 days of dexamethasone therapy, her paraplegia and urinary incontinence gradually improved. Results: The CT angiography (CTA) of the artery of Adamkiewicz (Aka) showed tandem narrowing, most conspicuous at the T10-11 level, which was presumably due to partial occlusion of the arteriolar lumen. The thoracolumbar spine magnetic resonance imaging with contrast medium showed owl's eyes sign at the T10 and T11 levels. We compared our case with two other case reports from the literature. Conclusions: Post-partum spinal cord infarction with positive anti-PF4 antibody and relatively thrombocytopenia are the characteristics of our case.

Influence of monitor display resolution and displayed image size on the spatial resolution of ultra-high-resolution CT images: a phantom study

To determine the optimal display conditions for ultra-high-resolution computed tomography (UHRCT) images in clinical practice, this study investigated the effects of liquid-crystal display (LCD) resolution and displayed image size on the spatial resolution of phantom images acquired using a UHRCT system. A phantom designed to evaluate the high-contrast resolution was scanned. The scan data were reconstructed into four types of UHRCT image series consisting of the following possible combinations: two types of reconstruction kernels on the filtered back-projection method (for the lung and mediastinum) and two types of matrix sizes (1024² and 2048²). These images were displayed under eight types of display conditions: three image sizes displayed on a 2-megapixel (MP) and 3-MP color LCD and two image sizes on an 8-MP color LCD. A total of 32 samples (four image series × eight display conditions) were evaluated by eight observers for high-contrast resolution. The high-contrast resolution of the displayed UHRCT images was significantly affected by the displayed image size, although the largest (full-screen) displayed image size did not necessarily show the maximum high-contrast resolution. When the images were displayed in the full-screen size, LCD resolution affected the high-contrast resolution of only the 2048²-matrix-size images reconstructed using the lung kernel. In conclusion, the spatial resolution of UHRCT images may be affected by LCD resolution and displayed image size. To optimize the clinical display conditions for UHRCT images, it is necessary to adopt an LCD with an adequate resolution for each viewing situation.

Novel Intraoperative Navigation Using Ultra-High-Resolution CT in Robot-Assisted Partial Nephrectomy

Simple Summary

Successful surgery in robot-assisted partial nephrectomy (RAPN), especially for highly complex tumors, relies on a detailed understanding of the anatomical relations of the tumor absolute and relative to the urinary tract and the vascular structures, including the renal pedicle. Intraoperative navigation with accurate information regarding tumor position relative to the surrounding urinary vascular structures undoubtedly assists the surgeon during RAPN. In this report, we performed RAPN with intraoperative navigation using a novel computed tomography scanner (UHR-CT) and compared its perioperative and short-term functional outcomes to those of area-detector CT (ADCT). We found that this novel navigation system using UHR-CT provided a shorter warm ischemia time and lower estimated blood loss than ADCT, and concluded this could be a useful tool for patients who undergo RAPN. This is the first report to evaluate the feasibility and usefulness of UHR-CT for intraoperative navigation during RAPN.

Abstract

To assess the perioperative and short-term functional outcomes of robot-assisted partial nephrectomy (RAPN) with intraoperative navigation using an ultra-high-resolution computed tomography (UHR-CT) scanner, we retrospectively analyzed 323 patients who underwent RAPN using an UHR-CT or area-detector CT (ADCT). Perioperative outcomes and the postoperative preservation ratio of estimated glomerular filtration rate (eGFR) were compared. After the propensity score matching, we evaluated 99 patients in each group. Although the median warm ischemia time (WIT) was less than 25 min in both groups, it was significantly shorter in the UHR-CT group than in the ADCT group (15 min vs. 17 min, p = 0.032). Moreover, the estimated blood loss (EBL) was significantly lower in the UHR-CT group than in the ADCT group (33 mL vs. 50 mL, p = 0.028). However, there were no significant intergroup differences in the postoperative preservation ratio of eGFR at 3 or 6 months of follow-up (ADCT 91.8% vs. UHR-CT 93.5%, p = 0.195; and ADCT 91.7% vs. UHR-CT 94.0%, p = 0.160, respectively). Although no differences in short-term renal function were observed in intraoperative navigation for RAPN in this propensity score–matched cohort, this study is the first to demonstrate that UHR-CT resulted in a shorter WIT and lower EBL than ADCT.

On the Role and Effects of Uncertainties in Cardiovascular in silico Analyses

The assessment of cardiovascular hemodynamics with computational techniques is establishing its fundamental contribution within the world of modern clinics. Great research interest was focused on the aortic vessel. The study of aortic flow, pressure, and stresses is at the basis of the understanding of complex pathologies such as aneurysms. Nevertheless, the computational approaches are still affected by sources of errors and uncertainties. These phenomena occur at different levels of the computational analysis, and they also strongly depend on the type of approach adopted. With the current study, the effect of error sources was characterized for an aortic case. In particular, the geometry of a patient-specific aorta structure was segmented at different phases of a cardiac cycle to be adopted in a computational analysis. Different levels of surface smoothing were imposed to define their influence on the numerical results. After this, three different simulation methods were imposed on the same geometry: a rigid wall computational fluid dynamics (CFD), a moving-wall CFD based on radial basis functions (RBF) CFD, and a fluid-structure interaction (FSI) simulation. The differences of the implemented methods were defined in terms of wall shear stress (WSS) analysis. In particular, for all the cases reported, the systolic WSS and the time-averaged WSS (TAWSS) were defined.

Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions

PURPOSE

To determine the image quality improvement including vascular structures using deep learning reconstruction (DLR) for ultra-high-resolution CT (UHR-CT) and area-detector CT (ADCT) compared to a commercially available hybrid-iterative reconstruction (IR) method.

MATERIALS AND METHOD

Thirty-two patients suspected of renal cell carcinoma underwent dynamic contrast-enhanced (CE) CT using UHR-CT or ADCT systems. CT value and contrast-to-noise ratio (CNR) on each CT dataset were assessed with region of interest (ROI) measurements. For qualitative assessment of improvement for vascular structure visualization, each artery was assessed using a 5-point scale. To determine the utility of DLR, CT values and CNRs were compared among all UHR-CT data by means of ANOVA followed by Bonferroni post hoc test, and same values on ADCT data were also compared between hybrid IR and DLR methods by paired t test.

RESULTS

For all arteries except the aorta, the CT value and CNR of the DLR method were significantly higher compared to those of the hybrid-type IR method in both CT systems reconstructed as 512 or 1024 matrixes (p < 0.05).

CONCLUSION

DLR has a higher potential to improve the image quality resulting in a more accurate evaluation for vascular structures than hybrid IR for both UHR-CT and ADCT.