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.

To assess the impact of deep learning (DL)-based image reconstruction on quantitative and subjective image quality in brain MRI at 0.55 T by comparing DL-reconstructed MPRAGE with standard MPRAGE using comparable acquisition geometry and timing parameters. In this prospective study, 30 patients underwent two consecutive 3D T1-weighted MPRAGE acquisitions on a 0.55 T MRI system (MAGNETOM Free.Max, Siemens Healthineers): a standard reconstruction and a DL-based reconstruction generated from undersampled k-space data using a variational-network architecture. Identical circular regions of interest (ROIs) were placed in gray matter (caudate nucleus), white matter (centrum semiovale), cerebrospinal fluid (lateral ventricle), and air for noise estimation. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were computed. Three blinded radiologists independently evaluated image quality using a 5-point Likert scale based on anatomical detail, gray-white matter differentiation, vascular visibility, artifact burden, and overall diagnostic quality. DL-based reconstruction significantly improved objective image quality across all metrics. SNR increased from 40.83 ± 10.11 to 106.30 ± 51.38 in gray matter (p < 0.0001), from 48.95 ± 12.52 to 125.30 ± 58.01 in white matter (p < 0.0001), and from 5.77 ± 1.10 to 7.75 ± 4.76 in CSF (p = 0.021). CNR between gray and white matter increased from 8.12 ± 4.24 to 18.99 ± 11.21 (p < 0.0001). Subjective ratings favored DL reconstruction for anatomical detail (4.05 ± 0.62 vs. 3.68 ± 0.64), vascular visibility (4.37 ± 0.56 vs. 3.63 ± 0.72), and overall image quality (4.07 ± 0.72 vs. 3.57 ± 0.73). Standard reconstruction showed slightly better artifact suppression (3.80 ± 0.61 vs. 3.27 ± 0.78) and gray-white matter contrast (4.00 ± 0.64 vs. 3.87 ± 0.71). Acquisition time was reduced from 6:44 min (standard MPRAGE) to 3:06 min with DL reconstruction, corresponding to a substantial scan time reduction. DL-based reconstruction markedly enhances quantitative and subjective image quality in low-field brain MRI and enables a markedly shorter acquisition time compared to the standard protocol. This study adds clinical evidence that DL reconstruction can substantially improve 0.55 T MPRAGE imaging, supporting its integration into routine neuroimaging workflows to improve efficiency, patient comfort, and diagnostic confidence.

Objectives: Photon-counting computed tomography (PCCT) enables quantitative assessment of tissue iodine distribution. This exploratory study investigated associations between PCCT-derived iodine parameters and clinical, serologic, and histopathologic characteristics of pancreatic ductal adenocarcinoma (PDAC). Materials and methods: This retrospective single-center study included 27 patients with histologically confirmed PDAC who underwent pretreatment contrast-enhanced PCCT. Iodine concentration was measured independently by two blinded readers in arterial and portal-venous phases using a whole-tumor ROI on the largest axial section and a solid-component ROI. Absolute iodine concentration, tumor-to-aorta normalized iodine ratios, and phase-to-phase Δ iodine were evaluated. CA 19 − 9 was analyzed continuously using Spearman rank correlation; cutoff-based and clinicopathologic subgroup comparisons were considered secondary exploratory analyses and were re-analyzed using two-sided Wilcoxon rank-sum tests. All p-values are nominal. Results: CA 19 − 9 was available in 24 patients (median 123.5 U/mL; IQR 55.3–1962). Higher CA 19 − 9 was associated with lower portal-venous absolute iodine concentration in the solid tumor component (Spearman ρ=-0.45, 95% CI -0.77 to -0.04; nominal p = 0.028) and with the arterial whole-tumor normalized iodine ratio (ρ=-0.58, 95% CI -0.84 to -0.14; nominal p = 0.010). At the 100 U/mL cutoff, portal-venous solid-component absolute iodine concentration was higher below the cutoff (1.77 ± 0.57 vs. 1.19 ± 0.50 mg/mL; nominal p = 0.017). After two-sided re-analysis, previously reported differences by T category, Ki-67, and tumor-cell count did not reach nominal significance. Interreader reliability was excellent across iodine parameters (ICC range 0.960–0.989). Conclusion: In this small exploratory cohort, selected absolute and normalized iodine measurements showed nominal inverse associations with CA 19 − 9, whereas associations with tumor stage and histopathologic parameters were not consistent after conservative two-sided re-analysis. PCCT iodine measurements were highly reproducible between readers. These findings are hypothesis-generating and require validation in larger independent cohorts before any incremental clinical value can be inferred.