The Future Arrived: Photon-Counting Detector CT

A Novel Reconstruction Technique to Reduce Stair-Step Artifacts in Sequential Mode Coronary CT Angiography

PURPOSE

Prospective electrocardiography-triggering is one of the most commonly used cardiac computed tomography (CT) scan modes but can be susceptible to stair-step artifacts in the transition areas of an acquisition over multiple cardiac cycles. We evaluated a novel reconstruction algorithm to reduce the occurrence and severity of such artifacts in sequential coronary CT angiography.

MATERIALS AND METHODS

In this institutional review board-approved, retrospective study, 50 consecutive patients (16 females; mean age, 58.9 ± 15.2) were included who underwent coronary CT angiography on a dual-source photon-counting detector CT in the sequential ultra-high-resolution mode with a detector collimation of 120 × 0.2 mm. Each scan was reconstructed without (hereafter called standard reconstruction) and with the novel ZeeFree reconstruction algorithm, which aims to minimize stair-step artifacts. The presence and extent of stair-step artifacts were rated by 2 independent, blinded readers on a 4-point discrete visual scale. The relationship between the occurrences of artifacts was correlated with the average and variability of heart rate and with patient characteristics.

RESULTS

A total of 504 coronary segments were included into the analyses. In standard reconstructions, reader 1 reported stair-step artifacts in 40/504 (7.9%) segments, from which 12/504 led to nondiagnostic image quality (2.4% of all segments). Reader 2 reported 56/504 (11.1%) stair-step artifacts, from which 11/504 lead to nondiagnostic image quality (2.2% of all segments). With the ZeeFree algorithm, 9/12 (75%) and 8/11 (73%) of the nondiagnostic segments improved to a diagnostic quality for readers 1 and 2, respectively. The ZeeFree reconstruction algorithm significantly reduced the frequency and extent of stair-step artifacts compared with standard reconstructions for both readers ( P < 0.001, each). Heart rate variability and body mass index were significantly related to the occurrence of stair-step artifacts ( P < 0.05).

CONCLUSIONS

Our study demonstrates the feasibility and effectiveness of a novel reconstruction algorithm leading to a significant reduction of stair-step artifacts and, hence, a reduction of coronary segments with a nondiagnostic image quality in sequential ultra-high-resolution coronary photon-counting detector CT angiography.

Photon-Counting Detector CT Radiological-Histological Correlation in Cadaveric Human Lung Nodules and Airways

OBJECTIVES

The aim of this study was to compare the performances of photon-counting detector computed tomography (PCD-CT) and energy-integrating detector computed tomography (EID-CT) for visualizing nodules and airways in human cadaveric lungs.

MATERIALS AND METHODS

Previously obtained 20 cadaveric lungs were scanned, and images were prospectively acquired by EID-CT and PCD-CT at a radiation dose with a noise level equivalent to the diagnostic reference level. PCD-CT was scanned with ultra-high-resolution mode. The EID-CT images were reconstructed with a 512 matrix, 0.6-mm thickness, and a 350-mm field of view (FOV). The PCD-CT images were reconstructed at 3 settings: PCD-512: same as EID-CT; PCD-1024-FOV350: 1024 matrix, 0.2-mm thickness, 350-mm FOV; and PCD-1024-FOV50: 1024 matrix, 0.2-mm thickness, 50-mm FOV. Two specimens per lung were examined after hematoxylin and eosin staining. The CT images were evaluated for nodules on a 5-point scale and for airways on a 4-point scale to compare the histology. The Wilcoxon signed rank test with Bonferroni correction was performed for statistical analyses.

RESULTS

Sixty-seven nodules (1321 μm; interquartile range [IQR], 758-3105 μm) and 92 airways (851 μm; IQR, 514-1337 μm) were evaluated. For nodules and airways, scores decreased in order of PCD-1024-FOV50, PCD-1024-FOV350, PCD-512, and EID-CT. Significant differences were observed between series other than PCD-1024-FOV350 versus PCD-1024-FOV50 for nodules (PCD-1024-FOV350 vs PCD-1024-FOV50, P = 0.063; others P < 0.001) and between series other than EID-CT versus PCD-512 for airways (EID-CT vs PCD-512, P = 0.549; others P < 0.005). On PCD-1024-FOV50, the median size of barely detectable nodules was 604 μm (IQR, 469-756 μm) and that of barely detectable airways was 601 μm (IQR, 489-929 μm). On EID-CT, that of barely detectable nodules was 837 μm (IQR, 678-914 μm) and that of barely detectable airways was 1210 μm (IQR, 674-1435 μm).

CONCLUSIONS

PCD-CT visualized small nodules and airways better than EID-CT and improved with high spatial resolution and potentially can detect submillimeter nodules and airways.

Three-Dimensional Visualization of Shunt Valves with Photon Counting CT and Comparison to Traditional X-ray in a Simple Phantom Model

This study introduces an application of innovative medical technology, Photon Counting Computer Tomography (PC CT) with novel detectors, for the assessment of shunt valves. PC CT technology offers enhanced visualization capabilities, especially for small structures, and opens up new possibilities for detailed three-dimensional imaging. Shunt valves are implanted under the skin and redirect excess cerebrospinal fluid, for example, to the abdominal cavity through a catheter. They play a vital role in regulating cerebrospinal fluid drainage in various pathologies, which can lead to hydrocephalus. Accurate imaging of shunt valves is essential to assess the rate of drainage, as their precise adjustment is a requirement for optimal patient care. This study focused on two adjustable shunt valves, the proGAV 2.0® and M. blue® (manufactured by Miethke, Potsdam, Germany). A comprehensive comparative analysis of PC CT and traditional X-ray techniques was conducted to explore this cutting-edge technology and it demonstrated that routine PC CT can efficiently assess shunt valves' adjustments. This technology shows promise in enhancing the accurate management of shunt valves used in settings where head scans are already frequently required, such as in the treatment of hydrocephalus.

Radiology: Cardiothoracic Imaging Highlights 2023

Radiology: Cardiothoracic Imaging publishes novel research and technical developments in cardiac, thoracic, and vascular imaging. The journal published many innovative studies during 2023 and achieved an impact factor for the first time since its inaugural issue in 2019, with an impact factor of 7.0. The current review article, led by the Radiology: Cardiothoracic Imaging trainee editorial board, highlights the most impactful articles published in the journal between November 2022 and October 2023. The review encompasses various aspects of coronary CT, photon-counting detector CT, PET/MRI, cardiac MRI, congenital heart disease, vascular imaging, thoracic imaging, artificial intelligence, and health services research. Key highlights include the potential for photon-counting detector CT to reduce contrast media volumes, utility of combined PET/MRI in the evaluation of cardiac sarcoidosis, the prognostic value of left atrial late gadolinium enhancement at MRI in predicting incident atrial fibrillation, the utility of an artificial intelligence tool to optimize detection of incidental pulmonary embolism, and standardization of medical terminology for cardiac CT. Ongoing research and future directions include evaluation of novel PET tracers for assessment of myocardial fibrosis, deployment of AI tools in clinical cardiovascular imaging workflows, and growing awareness of the need to improve environmental sustainability in imaging. Keywords: Coronary CT, Photon-counting Detector CT, PET/MRI, Cardiac MRI, Congenital Heart Disease, Vascular Imaging, Thoracic Imaging, Artificial Intelligence, Health Services Research © RSNA, 2024.