Classification of high-risk coronary plaques using radiomic analysis of multi-energy photon-counting-detector computed tomography (PCD-CT) images.

Coronary plaque risk classification in images acquired with photon-counting-detector (PCD) CT was performed using a radiomics-based machine learning (ML) model. With IRB approval, 19 coronary CTA patients were scanned on a PCD-CT (NAEOTOM Alpha, Siemens Healthineers) with median CTDIvol of 8.02 mGy. Five types of images: virtual monoenergetic images (VMIs) at 50-keV, 70-keV, and 100-keV, iodine maps, and virtual non-contrast (VNC) images were reconstructed using an iterative reconstruction algorithm (QIR), a quantitative kernel (Qr40) and 0.6-mm/0.3-mm slice thickness/increment. Atherosclerotic plaques were segmented using semi-automatic software (Research Frontier, Siemens). Segmentation confirmation and risk stratification (low- vs high-risk) were performed by a board-certified cardiac radiologist. A total of 93 radiomic features were extracted from each image using PyRadiomics (v2.2.0b1). For each feature, a t-test was performed between low- and high-risk plaques (p<0.05 considered significant). Two significant and non-redundant features were input into a support vector machine (SVM). A leave-one-out cross-validation strategy was adopted and the classification accuracy was computed. Fifteen low-risk and ten high-risk plaques were identified by the radiologist. A total of 18, 32, 43, 16, and 55 out of 93 features in 50-keV, 70-keV, 100-keV, iodine map, and VNC images were statistically significant. A total of 17, 19, 22, 20, and 22 out of 25 plaques were classified correctly in 50-keV, 70-keV, 100-keV, iodine map, and VNC images, respectively. A ML model using 100-keV VMIs and VNC images derived from coronary PCD-CTA best automatically differentiated low- and high-risk coronary plaques.

Optimal Virtual Monoenergetic Photon Energy (keV) for Photon-Counting-Detector Computed Tomography Angiography.

OBJECTIVE: This study aimed to determine the optimal photon energy for virtual monoenergetic images (VMI) in computed tomography angiography (CTA) using photon-counting-detector (PCD) CT. METHODS: Under institutional review board approval, 10 patients (abdominal, n = 4; lower extremity, n = 3; head and neck, n = 3) were scanned on an investigational PCD-CT (Count Plus, Siemens Healthcare) at 120 or 140 kV. All images were iteratively reconstructed with Bv48 kernel and 2-mm slice thickness. Axial and coronal VMI maximum-intensity projections were created in the range 40 to 65 keV (5-keV steps). Contrast-to-noise ratio (CNR) was calculated for major arteries in each VMI series. Two radiologists blindly ranked each VMI series for overall image quality and visualization of small vessels and pathology. The median and SD of scores for each photon energy were calculated. In addition, readers identified any VMIs that distinguished itself from others in terms of vessel/pathology visualization or artifacts. RESULTS: Mean iodine CNR was highest in 40-keV VMIs for all evaluated arteries. Across readers, the 50-keV VMI had the highest combined score (2.00 ± 1.11). Among different body parts, the 45-keV VMI was ranked highest for the head-and-neck (1.75 ± 0.68) and lower extremity (2.00 ± 1.41) CTA. Meanwhile, 50- and 55-keV VMIs were ranked highest for abdominal (2.50 ± 1.35 and 2.50 ± 1.56) CTA. The 40-keV VMI received the highest score for iodine visualization in vessels, and the 65-keV VMI for reduced metal/calcium-blooming artifacts. CONCLUSIONS: Quantitatively, VMIs at 40 keV had the highest CNR in major arterial vasculature using PCD-CTA. Based on radiologists' preference, the 45- and 50-keV VMIs were optimal for small body parts (eg, head and neck and lower extremity) and large body parts (eg, abdomen), respectively.

High-Pitch Multienergy Coronary CT Angiography in Dual-Source Photon-Counting Detector CT Scanner at Low Iodinated Contrast Dose.

OBJECTIVES: The aim of this study was to evaluate the high-helical pitch, multienergy (ME) scanning mode of a clinical dual-source photon-counting detector (PCD) computed tomography (CT) and the benefit of virtual monoenergetic images (VMIs) for low-contrast-dose coronary CT angiography (CTA). MATERIALS AND METHODS: High-pitch (3.2) ME coronary CTA was performed in PCD-CT in 27 patients using low contrast dose (30 mL of iohexol 350 mg/mL) and in 26 patients at routine contrast dose (60 mL). Low-energy-threshold 120 kV images (also known as T3D images) and 50 kiloelectron volts (50 keV) and 100 kiloelectron volts (100 keV) VMIs were reconstructed using a 1024 × 1024 matrix and 0.6-mm slices. The CT numbers, noise, and contrast-to-noise ratio (CNR) were measured in the ascending aorta (AA), left main coronary artery (LMCA), and distal left anterior descending (LAD) artery. Confidence in grading luminal stenosis with calcific plaque, noncalcific plaque, and stent was evaluated by 2 independent readers on a 0-100 scale (0 the lowest), and a CAD-RADS score was assigned. Image contrast enhancement, sharpness, noise, artifacts, and overall image quality were rated using a 5-point ordinal scale (1 the lowest). RESULTS: The radiation doses (CTDI) in low- and routine-contrast cohorts were 2.5 ± 0.6 mGy and 3.1 ± 1.7 mGy, respectively ( P = 0.12). At all measured locations, the mean CT number was >300 HU in 120 kV (LMCA 382.9 ± 76.2, distal LAD 341.0 ± 53.9, AA 399.5 ± 76.1) and 50 keV images (LMCA 667.5 ± 139.9, distal LAD 578.1 ± 121.5, AA 700.8 ± 142.5) in the low-contrast cohort, with a 96% increase in CT numbers for 50 keV over 120 kV. The CT numbers were significantly higher ( P < 0.0001) in 50 keV than 120 kV and 100 keV VMI. The CNR was also significantly ( P < 0.0001) higher in 50 keV than 120 kV and 100 keV images in all vessels. Confidence in the assessment of luminal stenosis in the presence of calcific plaque was significantly higher ( P = 0.001) with the addition of 100 keV VMI (median score, 100) than using 50 keV alone (median score, 70) and 120 kV (median score, 70) for reader 1, but no significant differences were seen for reader 2 who had same median scores of 100 for all image types. The confidence in the assessment of luminal stenosis within a stent improved with the use of 100 keV images for both readers (reader 1: median scores for 50 + 100 keV = 100, 50 keV = 82.5, 120 kV = 82.5; reader 2: 50 + 100 keV = 100, 50 keV = 90, 120 kV = 90). There were no significant differences in confidence scores for assessment of luminal stenosis from noncalcific plaques for both readers. The reader-averaged qualitative scores for vascular enhancement and overall image quality were significantly higher for 50 keV VMI than for 120 kV images in both low- and routine-contrast dose cohorts. The image sharpness was nonsignificantly higher at 50 keV VMI than 120 kV images, and the artifact score was comparable for 50 keV VMI and 120 kV images. The noise was higher in 50 keV VMI than in 120 kV images. CONCLUSIONS: High-pitch ME PCD-CT mode produced diagnostic quality coronary CTA images at low radiation and iodinated contrast doses. The availability of ME VMIs significantly improved the CNR, overall image quality, and confidence in assessment of luminal stenosis in the presence of calcific plaques and stents, and resulted in change of CAD-RADS categories in 9 patients.

Accuracy of Nodule Volume and Airway Wall Thickness Measurement Using Low-Dose Chest CT on a Photon-Counting Detector CT Scanner.

OBJECTIVES: A comparison of high-resolution photon-counting detector computed tomography (PCD-CT) versus energy-integrating detector (EID) CT via a phantom study using low-dose chest CT to evaluate nodule volume and airway wall thickness quantification. MATERIALS AND METHODS: Twelve solid and ground-glass lung nodule phantoms with 3 diameters (5 mm, 8 mm, and 10 mm) and 2 shapes (spherical and star-shaped) and 12 airway tube phantoms (wall thicknesses, 0.27-1.54 mm) were placed in an anthropomorphic chest phantom. The phantom was scanned with EID-CT and PCD-CT at 5 dose levels (CTDI vol = 0.1-0.8 mGy at Sn-100 kV, 7.35 mGy at 120 kV). All images were iteratively reconstructed using matched kernels for EID-CT and medium-sharp kernel (MK) PCD-CT and an ultra-sharp kernel (USK) PCD-CT kernel, and image noise at each dose level was quantified. Nodule volumes were measured using semiautomated segmentation software, and the accuracy was expressed as the percentage error between segmented and reference volumes. Airway wall thicknesses were measured, and the root-mean-square error across all tubes was evaluated. RESULTS: MK PCD-CT images had the lowest noise. At 0.1 mGy, the mean volume accuracy for the solid and ground-glass nodules was improved in USK PCD-CT (3.1% and 3.3% error) compared with MK PCD-CT (9.9% and 10.2% error) and EID-CT images (11.4% and 9.2% error), respectively. At 0.2 mGy and 0.8 mGy, the wall thickness root-mean-square error values were 0.42 mm and 0.41 mm for EID-CT, 0.54 mm and 0.49 mm for MK PCD-CT, and 0.23 mm and 0.16 mm for USK PCD-CT. CONCLUSIONS: USK PCD-CT provided more accurate lung nodule volume and airway wall thickness quantification at lower radiation dose compared with MK PCD-CT and EID-CT.

Impact of improved spatial resolution on radiomic features using photon-counting-detector CT.

Radiomics is a promising mathematical tool for characterizing disease and predicting clinical outcomes from radiological images such as CT. Photon-counting-detector (PCD) CT provides improved spatial resolution and dose efficiency relative to conventional energy-integrating-detector CT systems. Since improved spatial resolution enables visualization of smaller structures and more details that are not typically visible at routine resolution, it has a direct impact on textural features in CT images. Therefore, it is of clinical interest to quantify the impact of the improved spatial resolution on calculated radiomic features and, consequently, on sample classification. In this work, organic samples (zucchini, onions, and oranges) were scanned on both clinical PCD-CT and EID-CT systems at two dose levels. High-resolution PCD-CT and routine-resolution EID-CT images were reconstructed using a dedicated sharp kernel and a routine kernel, respectively. The noise in each image was quantified. Fourteen radiomic features of relevance were calculated in each image for each sample and compared between the two scanners. Radiomic features were plotted pairwise to evaluate the resulting cluster separation of the samples by their type between PCD-CT and EID-CT. Thirteen out of 14 studied radiomic features were notably changed by the improved resolution of the PCD-CT system, and the cluster separation was better when assessing features derived from PCD-CT. These results show that features derived from high-resolution PCD-CT, which are subject to higher noise compared to EID-CT, may impact radiomics-based clinical decision making.

Photon-counting computed tomography of lanthanide contrast agents with a high-flux 330-µm-pitch cadmium zinc telluride detector in a table-top system.

Purpose: We present photon-counting computed tomography (PCCT) imaging of contrast agent triplets similar in atomic number ( Z ) achieved with a high-flux cadmium zinc telluride (CZT) detector. Approach: The table-top PCCT imaging system included a 330 - µ m -pitch CZT detector of size 8 mm × 24 mm 2 capable of using six energy bins. Four 3D-printed 3-cm-diameter phantoms each contained seven 6-mm-diameter vials with water and low and high concentration solutions of various contrast agents. Lanthanum ( Z = 57 ), gadolinium (Gd) ( Z = 64 ), and lutetium ( Z = 71 ) were imaged together and so were iodine ( Z = 53 ), Gd, and holmium ( Z = 67 ). Each phantom was imaged with 1-mm aluminum-filtered 120-kVp cone beam x rays to produce six energy-binned computed tomography (CT) images. Results: K -edge images were reconstructed using a weighted sum of six CT images, which distinguished each contrast agent with a root-mean-square error (RMSE) of < 0.29 % and 0.51% for the 0.5% and 5% concentrations, respectively. Minimal cross-contamination in each K -edge image was seen, with RMSE values < 0.27 % in vials with no contrast. Conclusion: This is the first preliminary demonstration of simultaneously imaging three similar Z contrast agents with a difference in Z as low as 3.

X-Ray Fluorescence Computed Tomography Induced by Photon, Electron, and Proton Beams.

X-ray fluorescence CT (XFCT) has shown promise for molecular imaging of gold nanoparticles. To date, XFCT has been induced by kilovoltage photon beams due to the high photoelectric interaction probability. We compare K-shell and L-shell XFCT induced by photon, electron, and proton beams for two phantom sizes. A 2.5 and 5.0-cm diameter phantom with four 5 mm and 10 mm vials, respectively, with gold-solutions of 0.1%-2% by weight were built in TOPAS, a GEANT4-based Monte Carlo simulation tool. The 2.5-cm phantom was imaged with XFCT induced by beams of 7.45×104 81 keV- and 5 MeV-photons, 220 kVp- and 6 MV-photons, 10 MeV- and 100 MeV-electrons, and 100 MeV- and 250 MeV-protons. The doses between each phantom size were equal. First-generation CT geometry with 0.5 mm × 0.5 mm pencil beams with 0.5 mm-translation and 2°-rotation steps over each phantom was modeled. The scattered x-rays were detected on an idealized spherical detector from which the K-shell and L-shell fluorescent x-rays were extracted in 0.5 keV and 0.2 keV bins. XFCT images were generated using iterative reconstruction algorithms. The highest gold sensitivity was seen in the 81 keV-photon K-shell and L-shell images (0.004% and 0.007%) of the 5.0 cm-phantom at 30 mGy. For the 2.5 cm-phantom, the detection limits were 0.006%, 0.62%, and 0.28% for 81 keV-photon K-shell, 100 MeV-electron K-shell, and 100 MeV-proton L-shell images, respectively. The mean imaging dose was approximately 2-3 orders of magnitude higher in electron- and proton-XFCT compared to 81keV-photon XFCT. Our MC study demonstrates that the small-object XFCT imaging achieves the best performance when induced with kilovoltage-photon beams. Due to high imaging doses, electron- and proton-induced XFCT might be feasible for guiding nanoparticle-enhanced charged-particle radiotherapy.

Sheet beam x-ray fluorescence computed tomography (XFCT) imaging of gold nanoparticles.

PURPOSE: X-ray fluorescence computed tomography (XFCT) experiments have typically used pencil beams for data acquisition, which yielded good quality images of gold nanoparticles (AuNP) but prolonged the imaging time. Here we propose three novel collimator geometries for use with faster sheet beam XFCT data acquisition. The feasibility of a multipinhole, parallel, and converging collimator was investigated in a Monte Carlo study. METHODS: A cylindrical water phantom with 2 cm in diameter and 3 cm in height containing 0.5-2 mm diameter vials with 0.4%-1.6% AuNP concentrations was modelled by FLUKA. A 15 and 81 keV monoenergetic x-ray sheet beam of 0.4 mm in width was used to image the phantom with L-shell and K-shell XFCT, respectively, with a dose of 30 mGy. The collimator thickness for L-shell and K-shell data acquisition was 3.3 and 5.1 mm, respectively. The XFCT images resulting from three collimator geometries were generated using the maximum likelihood expectation maximization (MLEM) iterative reconstruction method. With a resolution of 0.4 mm they were corrected for x-ray attenuation. The sheet beam XFCT images were compared against pencil beam geometry images that were generated using 55 translations. To assess image quality, the contrast-to-noise ratio (CNR) was evaluated for each vial. The Rose criterion was used to determine the lowest AuNP concentration detectable for each image. RESULTS: Among the three collimator geometry types, the sheet beam L-shell and K-shell parallel collimator XFCT images yielded AuNP sensitivity limits at 0.09% and 0.08%, respectively, for a 2 mm diameter vial. The AuNP sensitivity limits of the pencil beam XFCT images were 0.07% and 0.01% for L-shell and K-shell XFCT, respectively. The L-shell parallel collimator AuNP imaging sensitivity approached that of the pencil beam geometry with a 55-fold reduction in imaging time. The AuNP sensitivity limits for the 1 mm diameter vial for the L-shell and K-shell parallel collimator XFCT images were 0.19% and 0.16%, respectively, and those of the pencil beam XFCT images were 0.08% and 0.01% for L-shell and K-shell XFCT, respectively. The remaining two collimator geometries resulted in a lower CNR and poorer image quality. For a 2 mm diameter vial, the AuNP sensitivity limits for the L-shell and K-shell multipinhole collimator XFCT images were 0.23% and 0.52%, respectively, while for the L-shell and K-shell converging collimator XFCT images the AuNP sensitivity limits were 0.38% and 0.13%, respectively. CONCLUSION: This work demonstrates the feasibility of sheet beam L-shell XFCT imaging for small animal studies using parallel-oriented lead collimators which can detect AuNP concentrations approaching the level of pencil beam images with reduced imaging time.