Minimizing Contrast Media Dose in CT Pulmonary Angiography with Clinical Photon Counting Using High Pitch Technique.

RATIONALE AND OBJECTIVES: To evaluate the potential to reduce the amount of iodinated contrast media (CM) for computer tomographic pulmonary angiography (CTPA) with a novel photon-counting-detector CT (PCCT). MATERIALS AND METHODS: Overall, 105 patients referred for CTPA were retrospectively included in this study. CTPA was performed using bolus tracking and high-pitch dual-source scanning (FLASH mode) on a novel PCCT (Naeotom Alpha, Siemens Healthineers). CM (Accupaque 300, GE Healthcare) dose was lowered stepwise following the introduction of the new CT scanner. Thus, patients could be divided into 3 groups as follows: group 1, n = 29, 35 ml of CM; group 2, n = 62, 45 ml of CM and group 3, n = 14, 60 ml of CM. Four readers independently assessed the image quality (Likert-scale 1-5) and adequate assessment of the segmental pulmonary arteries. Additionally, the pulmonary arterial contrast opacification was measured. RESULTS: The subjective image quality was rated highest in group 1 with 4.6 compared to 4.5 (group 2) and 4.1 (group 3) with a significant difference between groups 1 and 3 (p < 0.001) and between groups 2 and 3 (p = 0.003). In all groups, almost all segmental pulmonary arteries could be assessed adequately without significant differences (18.5 vs. 18.7 vs. 18.4). Mean attenuation in the pulmonary trunk did not differ significantly between groups 321 ± 92 HU versus 345 ± 93 HU versus 347 ± 88 HU (p = 0.69). CONCLUSION: Significant CM dose reduction is possible without a reduction in image quality. PCCT enables diagnostic CTPA with 35 ml of CM.

Dedicated virtual non-contrast images adapted for liver tissue in clinical photon counting CT improve virtual non-contrast imaging in various organs beyond the liver.

PURPOSE: Purpose of this study is to re-evaluate the accuracy and diagnostic reliability of virtual non-contrast (VNC) images acquired with the photon-counting computed tomography (PCCT) after an update of the CT scanner software. METHODS: Fifty-four patients were retrospectively enrolled. VNC images were reconstructed from true non-contrast (TNC) images (VNCn) and contrast-enhanced images in portal venous contrast phase (VNCv). Additionally, a liver-specific VNC (VNCl) was assessed. Quantitative image properties of VNC and TNC images were compared and consistency between VNC images was evaluated. Regions of interest were drawn in the liver, spleen, renal cortex, aorta, muscle and subcutaneous fat. RESULTS: Attenuation values on all VNC images differed significantly from TNC images in the liver, renal cortex, aorta and fat. A mean offset of <10HU between TNC and all VNC images was found in the liver, spleen and muscle. The comparison of TNC and VNCl images revealed an offset < 10HU in fat. Differences ≤ 10HU between TNC and VNCv and between TNC and VNCl were found in 68%, respectively in 75%. Differences ≤ 15HU were found in 79%, respectively in 92% of all measurements. Differences ≤ 10HU between TNC and VNCn were found in 79% and differences ≤ 15HU in 85%. CONCLUSION: Although there are statistically significant differences between HU values measured on TNC and VNC images in certain tissues, the minor offsets measured in liver and spleen suggest a good clinical applicability of VNCv and VNCl images. The significantly lower offset in subcutaneous fat on VNCl images suggests a superiority for measurements in adipose tissues.

Mechanical thrombectomy using the Nimbus stent-retriever - initial experiences in a single-center observational study.

BACKGROUND: The Nimbus stent-retriever (NSR) was developed for mechanical thrombectomy of wall-adherent thrombi in cerebral arteries. It features a novel geometry with a proximal spiral section and a distal barrel section. The new device is designed to retrieve tough clots with a micro-clamping technique. In the first case series reporting on the NSR, we share our initial experience about the first 12 treated cases. METHODS: In total, 12 patients (5 men, 7 women; mean age 78 years) with occlusion of the internal carotid artery or the middle cerebral artery (M1 or M2 segment) were treated with the NSR, 11 after unsuccessful recanalization attempts with conventional stent-retrievers or aspiration thrombectomy. RESULTS: Retrieving maneuvers with the NSR recovered a thrombus in 7 patients (58%), of which 6 resulted in vessel recanalization mTICI ≥ 2b. Successful recanalization improved the mTICI score by a median of 3 points. In 5 of 7 cases, this required only one thrombectomy maneuver. In 5 cases, no improvement of recanalization could be achieved with the NSR (1-3 attempts). No NSR-related complications occurred in this case series. CONCLUSIONS: In our initial experience, the NSR appeared to be a safe and effective second-line stent-retriever after unsuccessful MT with conventional stent-retrievers or aspiration thrombectomy allowing for mTICI ≥ 2b rescue thrombectomy in ab 50% of cases. No NSR associated complications occurred in our case series.

Assessment of hepatic steatosis based on virtual non-contrast computed tomography: Initial experiences with a photon counting scanner approved for clinical use.

PURPOSE: The present study evaluates the diagnostic accuracy of virtual non-contrast (VNC) images acquired with the first clinical photon counting CT scanner for the assessment of hepatic steatosis. METHOD: 140 patients were retrospectively enrolled in this study. The following CT indices were calculated according to the attenuation on VNC and true non-contrast (TNC) images: Liver attenuation CT (L), difference between liver and spleen attenuation CT (L-S) and the ratio between liver and spleen attenuation CT (L/S). RESULTS: Considering previously reported cut-off values, the sensitivity, specificity, positive and negative predictive value (PPV, NPV) for the detection of hepatic steatosis on VNC images was 94%, 87%, 30% and 99.5% for CT (L), 52%, 99%, 81% and 96% for CT (L-S) and 67%, 98%, 74% and 94% for CT (L/S). When adjusting the cut-off values according to the present study, the sensitivity, specificity, PPV and NPV for the detection of hepatic steatosis on VNC images was 94%, 92%, 41% and 99.6% for CT (L), 96%, 90%, 46% and 99.6% for CT (L-S) and 95%, 99.6%, 42% and 99.6% for CT (L/S). CONCLUSIONS: In conclusion, the spectral datasets acquired with the first clinical PCCT scanner enable the reconstruction of VNC images that are reliable for the image-based assessment of hepatic steatosis. By adjusting the cut-off values all tested CT indices perform well and offer an excellent sensitivity as well as specificity.

Image-Quality Assessment of Polyenergetic and Virtual Monoenergetic Reconstructions of Unenhanced CT Scans of the Head: Initial Experiences with the First Photon-Counting CT Approved for Clinical Use.

In 2021, the first clinical photon-counting CT (PCCT) was introduced. The purpose of this study is to evaluate the image quality of polyenergetic and virtual monoenergetic reconstructions in unenhanced PCCTs of the head. A total of 49 consecutive patients with unenhanced PCCTs of the head were retrospectively included. The signals ± standard deviations of the gray and white matter were measured at three different locations in axial slices, and a measure of the artifacts below the cranial calvaria and in the posterior fossa between the petrous bones was also obtained. The signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) were calculated for all reconstructions. In terms of the SNRs and CNRs, the polyenergetic reconstruction is superior to all virtual monoenergetic reconstructions (p < 0.001). In the MERs, the highest SNR is found in the 70 keV MER, and the highest CNR is in the 65 keV MER. In terms of artifacts below the cranial calvaria and in the posterior fossa, certain MERs are superior to polyenergetic reconstruction (p < 0.001). The PCCT provided excellent image contrast and low-noise profiles for the differentiation of the grey and white matter. Only the artifacts below the calvarium and in the posterior fossa still underperform, which is attributable to the lack of an artifact reduction algorithm in image postprocessing. It is conceivable that the usual improvements in image postprocessing, especially with regard to glaring artifacts, will lead to further improvements in image quality.