Rajendran, Kishore

Abstract Objectives Determine differences in quantitative stenosis severity measurements for ultra-high-resolution (UHR) photon-counting detector (PCD) coronary CT angiography (cCTA) relative to energy-integrating detector (EID) cCTA in a large patient cohort. Methods Adult participants seen between November 2022 and March 2023 underwent a clinical dual-source EID-CT cCTA and a research dual-source PCD-CT cCTA on the same day. Percent diameter stenosis (PDS) was measured, and stenosis severity was assigned based on the PDS of the most severe lesion per patient to determine a coronary artery disease reporting and data system (CAD-RADS) score. Agreement between EID-CT and PCD-CT for PDS and CAD-RADS was determined. Results A total of 112 participants were enrolled, yielding 82 subjects with at least 1 stenosis at PCD-CT (mean age, 68.0 ± 10.8 years; 69.5% [57/82] males). A total of 177 paired stenoses were quantified. The percent decrease in mean PDS from PCD-CT (24.3%) to EID-CT (29.4%) was 17.3% (median difference in PDS: −5.0%, 95% CI: −5.7% to −4.0%). The assigned CAD-RADS score changed in 31/82 subjects. In 11/31 subjects, the most severe stenosis was missed at EID-CT due to partial volume averaging of a small calcification, yet PCD clearly identified stenosis at those locations. In 20/31 subjects, the CAD-RADS score decreased at PCD-CT due to the decreased calcium blooming resulting from the improved spatial resolution. Conclusions UHR PCD cCTA decreases quantitative measures of stenosis severity when a stenosis is identified at EID, leading to decreases in CAD-RADS assignments. Advances in knowledge With its improved spatial resolution, PCD-CT identifies stenoses missed on EID-CT.

Abstract Photon-counting detector CT (PCD-CT) represents a significant advancement in medical imaging, particularly for musculoskeletal (MSK) applications. Its primary innovation lies in enhanced spatial resolution, which facilitates improved detection of small anatomical structures such as trabecular bone, osteophytes, and subchondral cysts. PCD-CT enables high-quality imaging with reduced radiation doses, making it especially beneficial for populations requiring frequent imaging, such as paediatric patients and individuals with multiple myeloma. Additionally, PCD-CT supports advanced applications like bone quality assessment, which correlates well with gold-standard tests, and can aid in diagnosing osteoporosis and assessing fracture risk. Techniques such as spectral shaping and virtual monoenergetic imaging further optimize the technology, minimizing artefacts and enhancing material decomposition. These capabilities extend to conditions like gout and haematologic malignancies, offering improved detection and assessment. The integration of artificial intelligence could enhance PCD-CT’s performance by reducing image noise and improving quantitative assessments. Ultimately, PCD-CT’s superior resolution, reduced dose protocols, and multi-energy imaging capabilities will likely have a transformative impact on MSK imaging, improving diagnostic accuracy, patient care, and clinical outcomes.

Abstract Quantitative computed tomography (CT) enables the measurement of biophysical processes characterized by morphology, composition, flow, and/or motion to aid in clinical diagnosis and intervention. Since its initial application for determining bone mineral density for skeletal fragility assessment, quantitative CT has continued to evolve alongside CT’s technological advancements. A key challenge facing quantitative CT is the lack of standardization pertinent to image acquisition, reconstruction, and image analysis. With the introduction of spectral CT involving dual-energy approaches and photon-counting detectors (PCD), we are now able to obtain detailed information regarding mass densities of endogenous and exogeneous materials. Furthermore, energy-resolved CT yields spectral image types (eg, virtual monoenergetic image) that are, in principle, independent of tube potential and patient size. This paves the way for workflow standardization and helps improve the consistency and reproducibility of CT-derived measurements. In this article, we review clinical applications of quantitative CT, discuss key challenges associated with quantitative CT and its adoption into routine practice, and outline the unique benefits ushered by new CT technologies such as PCD-CT towards improving quantitative imaging.

Abstract Objectives To assess quantitative and qualitative image characteristics in phantoms and patients using a simultaneous ultra-high resolution (UHR) and multi-energy (ME) dual-source cardiac scan mode in a photon counting detector (PCD) CT scanner. Methods UHR-ME cardiac scans were performed to determine the spatial resolution and multi-energy performance. UHR reconstructions were completed to measure transverse and axial spatial resolution in terms of modulation transfer function (MTF) and slice sensitivity profile (SSP). Virtual monoenergetic images (VMIs), virtual non-contrast (VNC) images, and iodine concentration images were created using moderately sharp reconstruction kernels to assess ME performance. With IRB approval, coronary CT angiograms were acquired in 19 patients using the UHR-ME mode, from which iodine contrast-to-noise ratio (CNR) was measured. Various ME post-processing tasks were performed to show the utility of the spectral capabilities. Results VMIs showed a mean CT number error of 6.0%, while iodine accuracy was 0.71 mg/cc (root-mean-square-error). Spatial resolution matched well with a standard UHR mode. Patient images showed a trend of higher CNR at lower keV, while higher keV images showed decreased calcium blooming. ME techniques to separate iodine and calcium were used successfully. Conclusions The combination of UHR-ME cardiac mode retains UHR image quality while providing flexibility for ME post-processing. Advances in knowledge Cardiac UHR-ME PCD-CT scanning offers simultaneous UHR and ME imaging without loss of spatial or temporal resolution or quantitative accuracy.

AbstractBackgroundThe first commercially available photon‐counting‐detector CT (PCD‐CT) has been introduced for clinical use. However, its spectral performance on single‐ and dual‐contrast imaging tasks has not been comprehensively assessed.PurposeTo evaluate the spectral imaging performance of a clinical PCD‐CT system for single‐contrast material [iodine (I) or gadolinium (Gd)] and dual‐contrast materials (I and Gd) in comparison with a dual‐source dual‐energy CT (DS‐DECT).MethodsIodine (5, 10, and 15 mg/mL) and gadolinium (3.3, 6.6, and 9.9 mg/mL) samples, and their mixtures (I/Gd: 5/3.3 and 10/6.6 mg/mL) were prepared and placed in two torso‐shaped water phantoms (lateral dimensions: 30 and 40 cm). These phantoms were scanned on a PCD‐CT (NAEOTOM Alpha, Siemens) at 90, 120, and 140 kV. The same phantoms were scanned on a DS‐DECT (SOMATOM Force, Siemens) with 70/Sn150, 80/Sn150, 90/Sn150, and 100/Sn150 kV. The radiation dose levels were matched [volume CT dose index (CTDIvol): 10 mGy for the 30 cm phantom and 20 mGy for the 40 cm phantom] across all tube voltage settings and between scanners. Two‐material decomposition (I/water or Gd/water) was performed on iodine or gadolinium samples, and three‐material decomposition (I/Gd/water) on both individual samples and mixtures. On each decomposed image, mean mass concentration (± standard deviation) was measured in circular region‐of‐interests placed on the contrast samples. Root‐mean‐square‐error (RMSE) values of iodine and gadolinium concentrations were reported based on the measurements across all contrast samples and repeated on 10 consecutive slices.ResultsFor all material decomposition tasks on the DS‐DECT, the kV pairs with greater spectral separation (70/Sn150 kV and 80/Sn150 kV) yielded lower RMSE values than other DS‐DECT and PCD‐CT alternatives. Specifically, for the optimal 70/Sn150 kV, RMSE values were 1.2 ± 0.1 mg/mL (I) for I/water material decomposition, 1.0 ± 0.1 mg/mL (Gd) for Gd/water material decomposition, and 4.5 ± 0.2 mg/mL (I) and 3.7 ± 0.2 mg/mL (Gd), respectively, for I/Gd/water material decomposition. On the PCD‐CT, the optimal tube voltages were 120 or 140 kV for I/water decomposition with RMSE values of 2.0 ± 0.1 mg/mL (I). For Gd/water decomposition on PCD‐CT, the optimal tube voltage was 140 kV with gadolinium RMSE values of 1.5 ± 0.1 mg/mL (Gd), with the 90 kV setting on PCD‐CT generating higher RMSE values for gadolinium concentration compared to all DS‐DECT and PCD‐CT alternatives. For three material decomposition, both imaging modalities demonstrated substantially higher RMSE values for iodine and gadolinium, with 90 kV being the optimal tube potential for Gd/I quantitation on PCD‐CT [5.4 ± 0.3 mg/mL (I) and 3.9 ± 0.2 mg/mL (Gd)], and DS‐DECT at 100/Sn150 kV having larger RMSE values for both materials compared to the alternatives for either modality.ConclusionOptimal tube voltage for material decomposition on the clinical PCD‐CT is task‐dependent but inferior to DS‐DECT using 70/Sn150 kV or 80/Sn150 kV in two‐material decomposition for single‐contrast imaging (iodine/water or gadolinium/water). Three material decomposition (iodine/gadolinium/water) in dual‐contrast imaging yields substantially higher RMSE for both imaging platforms.

Abstract Objective . Photon-counting detector (PCD) CT enables routine virtual-monoenergetic image (VMI) reconstruction. We evaluated the performance of an automatic VMI energy level (keV) selection tool on a clinical PCD-CT system in comparison to an automatic tube potential (kV) selection tool from an energy-integrating-detector (EID) CT system from the same manufacturer. Approach. Four torso-shaped phantoms (20–50 cm width) containing iodine (2, 5, and 10 mg cc −1 ) and calcium (100 mg cc −1 ) were scanned on PCD-CT and EID-CT. Dose optimization techniques, task-based VMI energy level and tube-potential selection on PCD-CT (CARE keV) and task-based tube potential selection on EID-CT (CARE kV), were enabled. CT numbers, image noise, and dose-normalized contrast-to-noise ratio (CNR d ) were compared. Main results . PCD-CT produced task-specific VMIs at 70, 65, 60, and 55 keV for non-contrast, bone, soft tissue with contrast, and vascular settings, respectively. A 120 kV tube potential was automatically selected on PCD-CT for all scans. In comparison, EID-CT used x-ray tube potentials from 80 to 150 kV based on imaging task and phantom size. PCD-CT achieved consistent dose reduction at 9%, 21% and 39% for bone, soft tissue with contrast, and vascular tasks relative to the non-contrast task, independent of phantom size. On EID-CT, dose reduction factor for contrast tasks relative to the non-contrast task ranged from a 65% decrease (vascular task, 70 kV, 20 cm phantom) to a 21% increase (soft tissue with contrast task, 150 kV, 50 cm phantom) due to size-specific tube potential adaptation. PCD-CT CNR d was equivalent to or higher than those of EID-CT for all tasks and phantom sizes, except for the vascular task with 20 cm phantom, where 70 kV EID-CT CNR d outperformed 55 keV PCD-CT images. Significance . PCD-CT produced more consistent CT numbers compared to EID-CT due to standardized VMI output, which greatly benefits standardization efforts and facilitates radiation dose reduction.