High yield clinical applications for photon counting CT in neurovascular imaging

Photon-counting CT (PCCT) uses a novel X-ray detection mechanism that confers many advantages over that used in traditional energy integrating CT. As PCCT becomes more available, it is important to thoroughly understand its benefits and highest yield areas for improvements in diagnosis of various diseases. Based on our early experience, we have identified several areas of neurovascular imaging in which PCCT shows promise. Here, we describe the benefits in diagnosing arterial and venous diseases in the head, neck, and spine. Specifically, we focus on applications in head and neck CT angiography (CTA), spinal CT angiography, and CT myelography for detection of CSF-venous fistulas. Each of these applications highlights the technological advantages of PCCT in neurovascular imaging. Further understanding of these applications will not only benefit institutions incorporating PCCT into their practices but will also help guide future directions for implementation of PCCT for diagnosing other pathologies in neuroimaging.

A systematic task-based image quality assessment of photon-counting and energy integrating CT as a function of reconstruction kernel and phantom size

BACKGROUND

Image quality of photon-counting and energy integrating CT scanners changes with object size, dose to the object, and kernel selection.

PURPOSE

To comprehensively compare task-generic image quality of photon-counting CT (PCCT) and energy integrating CT (EICT) systems as a function of phantom size, dose, and reconstruction kernel.

METHODS

A size-variant phantom (Mercury Phantom 3.0) was used to characterize the image quality of PCCT and EICT systems as a function of object size. The phantom contained five cylinders attached by slanted tapered sections. Each cylinder contained two sections: one uniform for noise, and the other with inserts for spatial resolution and contrast measurements. The phantom was scanned on Siemens' SOMATOM Force and NAEOTOM Alpha at 1.18 and 7.51 mGy without tube current modulation. CTDIvol was matched across two systems by setting the required tube currents, else, all other acquisition settings were fixed. CT sinograms were reconstructed using FBP and iterative (ADMIRE2 - Force; QIR2 - Alpha) algorithms with Body regular (Br) kernels. Noise Power Spectrum (NPS), Task Transfer Function (TTF), contrast-to-noise ratio (CNR), and detectability index (d') for a task of identifying 2-mm disk were evaluated based on AAPM TG-233 metrology using imQuest, an open-source software package. Averaged noise frequency (fav ) and 50% cut-off frequency for TTF (f50 ) were used as scalar metrics to quantify noise texture and spatial resolution, respectively. The difference between image quality metrics' measurements was calculated as IQPCCT - IQEICT .

RESULTS

From Br40 (soft) to Br64 (sharp), f50 for air insert increased from 0.35 mm-1  ± 0.04 (standard deviation) to 0.76 mm-1  ± 0.17, 0.34 mm-1  ± 0.04 to 0.77 mm-1  ± 0.17, 0.37 mm-1  ± 0.02 to 0.95 mm-1  ± 0.17 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively, when averaged over all sizes and dose levels. Similarly, from Br40 to Br64, noise magnitude increased from 10.86 HU ± 7.12 to 38.61 HU ± 18.84, 10.94 HU ± 7.08 to 38.82 HU ± 18.70, 13.74 HU ± 11.02 to 52.11 HU ± 26.22 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively. The difference in fav was consistent across all sizes and dose levels. PCCT-70keV-VMI showed better consistency in contrast measurements for iodine and bone inserts than PCCT-T3D and EICT; however, PCCT-T3D had higher contrast for both inserts. From Br40 to Br64, considering all sizes and dose levels, CNR for iodine insert decreased from 52.30 ± 46.44 to 12.18 ± 10.07, 40.42 ± 33.42 to 9.48 ± 7.16, 39.94 ± 37.60 to 7.84 ± 6.67 for PCCT-T3D-QIR2, PCCT-70keV-QIR2, and EICT-ADMIRE2, respectively.

CONCLUSIONS

Both PCCT image types, T3D and 70-keV-VMI exhibited similar or better noise, contrast, CNR than EICT when comparing kernels with similar names. For 512 × 512 matrix, PCCT's sharp kernels had lower resolution than EICT's sharp kernels. For all image quality metrics, except extreme low, every dose condition had a similar set of IQ-matching kernels. It suggests that considering patient size and dose level to determine IQ-matching kernel pairs across PCCT and EICT systems may not be imperative while translating protocols, except when the signal to the detector is extremely low.

Exploration of the pulse pileup effects in a clinical CdTe-based photon-counting computed tomography

BACKGROUND

High tube current generates a high flux of x-rays to photon counting detectors (PCDs) that can potentially result in the piling up of pulses formed by concurrent photons, which can cause count loss and energy resolution degradation.

PURPOSE

To evaluate the performance of clinical photon-counting CT (PCCT) systems in high flux, potentially influenced by pulse pileup effects, in terms of task-generic image quality metrics.

METHODS

A clinical phantom was scanned on a commercial PCCT scanner (NAEOTOM Alpha, Siemens) at 120 kV under fourteen different tube current levels (40-1000 mA) with a rotation time of 0.25 s and a pitch of 1. The dose levels corresponded to CTDIvol (32 cm phantom) of 0.79-19.8 mGy. CT sinograms were reconstructed using QIR-off mode (noniterative reconstruction algorithm), Br44 kernel, and a voxel size of0.4102 × 0.4102 × 3 mm 3 $0.4102 \times 0.4102 \times 3{\mathrm{\ mm}}^3$ . imQuest, an open-source MATLAB-based software package was used to calculate noise power spectrum (NPS), task transfer function (TTF), contrast-to-noise ratio (CNR), and CT number according to AAPM Task Group 233 metrology.

RESULTS

The 50% cut-off frequency of TTF (f50 ) remained mostly constant across all higher tube currents for all inserts, namely polyethylene, bone, air, and acrylic. Using the lowest two data points (40 and 80 mA), the expected relationship between noise magnitude and tube current was determined to be noise∝ $ \propto \ $ mA-0.47 . The measured noise magnitude were up to 11.1% higher than the expected value at the highest tube current. The average frequency of NPS (fav ) decreased from 0.32 to 0.29 mm-1 as tube current increased from 40 to 1000 mA. No considerable effects were observed in CT number measurement of any insert; however, CT numbers for air and bone changed almost monotonically as tube current increased. Absolute CNR increased monotonically for all inserts; however, the difference between measured and expected CNRs were approximately -6% to 12% across all tube currents.

CONCLUSIONS

Increasing tube currents did not affect the spatial resolution, but slightly affected the CT number and noise measurements of the clinical PCCT system. However, the effects were only considerable at clinically irrelevant tube currents used on a small 20-cm phantom. In general clinical practices, automatic exposure control techniques are used to decrease the variation of flux on the detector, which alleviates the chances of detector saturation due to high count rates. The observed effects could be due to pulse pileup, signal-dependent filtration of the system, or nonlinearities in the reconstruction algorithm. In conclusion, either the deadtime of the detector used in the photon-counting CT system is shorter such that count losses due to pulse pileup are negligible, or pulse pileup has inconsiderable effects on the image quality of clinical photon-counting CT systems in routine clinical practice due to possible corrections applied on the system.

Correcting statistical CT number biases without access to raw detector counts: Applications to high spatial resolution photon counting CT imaging

BACKGROUND

Due to the nonlinear nature of the logarithmic operation and the stochastic nature of photon counts (N), sinogram data of photon counting detector CT (PCD-CT) are intrinsically biased, which leads to statistical CT number biases. When raw counts are available, nearly unbiased statistical estimators for projection data were developed recently to address the CT number bias issue. However, for most clinical PCD-CT systems, users' access to raw detector counts is limited. Therefore, it remains a challenge for end users to address the CT number bias issue in clinical applications.

PURPOSE

To develop methods to correct statistical biases in PCD-CT without requiring access to raw PCD counts.

METHODS

(1) The sample variance of air-only post-log sinograms was used to estimate air-only detector counts,N ¯ 0 $\bar{N}_0$ . (2) If the post-log sinogram data, y, is available, then N of each detector pixel was estimated usingN = N ¯ 0 e - y $N = \bar{N}_0 \, \mathrm{e}^{-y}$ . Once N was estimated, a closed-form analytical bias correction was applied to the sinogram. (3) If a patient's post-log sinogram data are not archived, a forward projection of the bias-contaminated CT image was used to perform a first-order bias correction. Both the proposed sinogram domain- and image domain-based bias correction methods were validated using experimental PCD-CT data.

RESULTS

Experimental results demonstrated that both sinogram domain- and image domain-based bias correction methods enabled reduced-dose PCD-CT images to match the CT numbers of reference-standard images within [-5, 5] HU. In contrast, uncorrected reduced-dose PCD-CT images demonstrated biases ranging from -25 to 55 HU, depending on the material. No increase in image noise or spatial resolution degradation was observed using the proposed methods.

CONCLUSIONS

CT number bias issues can be effectively addressed using the proposed sinogram or image domain method in PCD-CT, allowing PCD-CT acquired at different radiation dose levels to have consistent CT numbers desired for quantitative imaging.

Comprehensive evaluations of a prototype full field-of-view photon counting CT system through phantom studies

Objective. Photon counting CT (PCCT) has been a research focus in the last two decades. Recent studies and advancements have demonstrated that systems using semiconductor-based photon counting detectors (PCDs) have the potential to provide better contrast, noise and spatial resolution performance compared to conventional scintillator-based systems. With multi-energy threshold detection, PCD can simultaneously provide the photon energy measurement and enable material decomposition for spectral imaging. In this work, we report a performance evaluation of our first CdZnTe-based prototype full-size PCCT system through various phantom imaging studies.Approach.This prototype system supports a 500 mm scan field-of-view and 10 mmz-coverage at isocenter. Phantom scans were acquired using 120 kVp from 50 to 400 mAs to assess the imaging performance on: CT number accuracy, uniformity, noise, spatial resolution, material differentiation and quantification.Main results.Both qualitative and quantitative evaluations show that PCCT, under the tested conditions, has superior imaging performance with lower noise and improved spatial resolution compared to conventional energy integrating detector (EID)-CT. Using projection domain material decomposition approach with multiple energy bin measurements, PCCT virtual monoenergetic images have lower noise, and good accuracy in quantifying iodine and calcium concentrations. These results lead to increased contrast-to-noise ratio (CNR) for both high and low contrast study objects compared to EID-CT at matched dose and spatial resolution. PCCT can also generate super-high resolution images using much smaller detector pixel size than EID-CT and greatly improve image spatial resolution.Significance.Improved spatial resolution and quantification accuracy with reduced image noise of the PCCT images can potentially lead to better diagnosis at reduced radiation dose compared to conventional EID-CT. Increased CNR achieved by PCCT suggests potential reduction in iodine contrast media load, resulting in better patient safety and reduced cost.

Simultaneous photon counting and charge integrating for pulse pile-up correction in paralyzable photon counting detectors

Objective.In photon counting detectors (PCDs), electric pulses induced by two or more x-ray photons can pile up and result in count losses when their temporal separation is less than the detector dead time. The correction of pulse pile-up-induced count loss is particularly difficult for paralyzable PCDs since a given value of recorded counts can correspond to two different values of true photon interactions. In contrast, charge (energy) integrating detectors work by integrating collected electric charge induced by x-rays over time and do not suffer from pile-up losses. This work introduces an inexpensive readout circuit element to the circuits of PCDs to simultaneously collect time-integrated charge to correct pile-up-induced count losses.Approach.Prototype electronics were constructed to collect time-integrated charges simultaneously with photon counts. A splitter was used to feed the electric signal in parallel to both a digital counter and a charge integrator. After recording PCD counts and integrating collected charge, a lookup table can be generated to map raw counts in the total- and high-energy bins and total charge to estimate pile-up-free true counts. Proof-of-concept imaging experiments were performed with a CdTe-based PCD array to test this method.Main results.The proposed electronics successfully recorded photon counts and time-integrated charge simultaneously, and whereas photon counts exhibited paralyzable pulse pile-up, time-integrated charge using the same electric signal as the counts measurement was linear with x-ray flux. With the proposed correction, paralyzable PCD counts became linear with input flux for both total- and high-energy bins. At high flux levels, uncorrected post-log measurements of PMMA objects severely overestimated radiological path lengths for both energy bins. After the proposed correction, the non-monotonic measurements again became linear with flux and accurately represented the true radiological path lengths. No impact on the spatial resolution was observed after the proposed correction in images of a line-pair test pattern.Significance.Time-integrated charge can be used to correct for pulse pile-up in paralyzable PCDs where analytical solutions may be difficult to use, and integrated charge can be collected simultaneously with counts using inexpensive electronics.

Is There Still a Role for Two-Phase Contrast-Enhanced CT and Virtual Monoenergetic Images in the Era of Photon-Counting Detector CT?

BACKGROUND

To compare the diagnostic characteristics between arterial phase imaging versus portal venous phase imaging, applying polychromatic T3D images and low keV virtual monochromatic images using a 1st generation photon-counting CT detector, of CT in patients with hepatocellular carcinoma (HCC).

METHODS

Consecutive patients with HCC, with a clinical indication for CT imaging, were prospectively enrolled. Virtual monoenergetic images (VMI) were reconstructed at 40 to 70 keV for the PCD-CT. Two independent, blinded radiologists counted all hepatic lesions and quantified their size. The lesion-to-background ratio was quantified for both phases. SNR and CNR were determined for T3D and low VMI images; non-parametric statistics were used.

RESULTS

Among 49 oncologic patients (mean age 66.9 ± 11.2 years, eight females), HCC was detected in both arterial and portal venous scans. The signal-to-noise ratio, the CNR liver-to-muscle, the CNR tumor-to-liver, and CNR tumor-to-muscle were 6.58 ± 2.86, 1.40 ± 0.42, 1.13 ± 0.49, and 1.53 ± 0.76 in the arterial phase and 5.93 ± 2.97, 1.73 ± 0.38, 0.79 ± 0.30, and 1.36 ± 0.60 in the portal venous phase with PCD-CT, respectively. There was no significant difference in SNR between the arterial and portal venous phases, including between "T3D" and low keV images (p > 0.05). CNR_{tumor-to-liver} differed significantly between arterial and portal venous contrast phases (p < 0.005) for both "T3D" and all reconstructed keV levels. CNR_{liver-to-muscle} and CNR_{tumor-to-muscle} did not differ in either the arterial or portal venous contrast phases. CNR_{tumor-to-liver} increased in the arterial contrast phase with lower keV in addition to SD. In the portal venous contrast phase, CNR_{tumor-to-liver} decreased with lower keV; whereas, CNR_{tumor-to-muscle} increased with lower keV in both arterial and portal venous contrast phases. CTDI and DLP mean values for the arterial upper abdomen phase were 9.03 ± 3.59 and 275 ± 133, respectively. CTDI and DLP mean values for the abdominal portal venous phase were 8.75 ± 2.99 and 448 ± 157 with PCD-CT, respectively. No statistically significant differences were found concerning the inter-reader agreement for any of the (calculated) keV levels in either the arterial or portal-venous contrast phases.

CONCLUSIONS

The arterial contrast phase imaging provides higher lesion-to-background ratios of HCC lesions using a PCD-CT; especially, at 40 keV. However, the difference was not subjectively perceived as significant.

Improvements in dose efficiency with high resolution scan modes in photon counting CT

For the detection of very small objects, high resolution detectors are expected to provide higher dose efficiency. We assessed this impact of increased resolution on a clinical photon counting detector CT (PCD-CT) by comparing its detectability in high resolution and standard resolution (with 2×2 binning and larger focal spot) modes. A 50μm-thin metal wire was placed in a thorax phantom and scanned in both modes at three exposure levels (12, 15, and 18 mAs); acquired data were reconstructed with three reconstruction kernels (Br40, Br68, and Br76, from smooth to sharp). A scanning nonprewhitening model observer searched for the wire location within each slice independently. Detection performance was quantified as area under the exponential transform of the free response ROC curve. The high-resolution mode had the mean AUCs at 18 mAs of 0.45, 0.49, and 0.65 for Br40, Br68, and Br76, respectively, which were 2 times, 3.6 times, and 4.6 times those of the standard resolution mode. The high-resolution mode achieved greater AUC at 12 mAs than the standard resolution mode at 18 mAs for every reconstruction kernel, but improvements were larger at sharper kernels. The results are consistent with the greater suppression of noise aliasing expected at higher frequencies with high resolution CT. This work illustrates that PCD-CT can provide large dose efficiency gains for detection tasks of small, high contrast lesions.

Clinical Low Dose Photon Counting CT for the Detection of Urolithiasis: Evaluation of Image Quality and Radiation Dose

The purpose of this study was the evaluation of image quality and radiation dose parameters of the novel photon counting CT (PCCT, Naeotom Alpha, Siemens Healthineers) using low-dose scan protocols for the detection of urolithiasis. Standard CT scans were used as a reference (S40, Somatom Sensation 40, Siemens Healthineers). Sixty-three patients, who underwent CT scans between August and December 2021, were retrospectively enrolled. Thirty-one patients were examined with the PCCT and 32 patients were examined with the S40. Radiation dose parameters, as well as quantitative and qualitative image parameters, were analyzed. The presence of urolithiasis, image quality, and diagnostic certainty were rated on a 5-point-scale by 3 blinded readers. Both patient groups (PCCT and S40) did not differ significantly in terms of body mass index. Radiation dose was significantly lower for examinations with the PCCT compared to the S40 (2.4 ± 1.0 mSv vs. 3.4 ± 1.0 mSv; p < 0.001). The SNR was significantly better on images acquired with the PCCT (13.3 ± 3.3 vs. 8.2 ± 1.9; p < 0.001). The image quality of the PCCT was rated significantly better (4.3 ± 0.7 vs. 2.8 ± 0.6; p < 0.001). The detection rate of kidney or ureter calculi was excellent with both CT scanners (PCCT 97.8% and S40 99%, p = 0.611). In high contrast imaging, such as the depiction of stones of the kidney and the ureter, PCCT allows a significant reduction of radiation dose, while maintaining excellent diagnostic confidence and image quality. Given this image quality with our current protocol, further adjustments towards ultra-low-dose CT scans appear feasible.

An experimental method to correct low-frequency concentric artifacts in photon counting CT

Large-area photon counting detectors (PCDs) are usually built by tiling multiple semiconductor panels that often have slightly different spectral responses to input x-rays. As a result of this spectral inconsistency, experimental PCD-CT images of large, human-sized objects may show high-frequency ring artifacts and low-frequency band artifacts. Due to the much larger width of the bands compared with the rings, the concentric artifact problem in PCD-CT images of human-sized objects cannot be adequately addressed by conventional CT ring correction methods. This work presents an experimental method to correct the concentric artifacts in PCD-CT. The method is applicable to not only energy-discriminating PCDs with multiple bins but also PCDs with only a single threshold controller. Its principle is similar to the two-step beam hardening correction method, except that the proposed method uses pixel-specific polynomial functions to address the spectral inconsistency problem across the detector plane. The pixel-specific polynomial coefficients were experimentally calibrated using 15 acrylic sheets and 6 aluminum sheets of known thicknesses. The pixel-specific polynomial functions were used to convert the measured PCD-CT projection data to acrylic- and aluminum-equivalent thicknesses that are energy-independent. The proposed method was experimentally evaluated using a human cadaver head and multiple physical phantoms: two of them contain iodine and one phantom contains dual K-edge contrast materials (gadolinium and iodine). The results show that the proposed method can effectively remove the low-frequency concentric artifacts in PCD-CT images while reducing beam hardening artifacts. In contrast, the conventional CT ring correction algorithm did not adequately address the low-frequency band artifacts. Compared with the direct material decomposition-based correction method, the proposed method not only relaxes the requirement of multi-energy bins but also generates images with lower noise and fewer concentric artifacts.

An effective noise reduction method for multi-energy CT images that exploit spatio-spectral features

PURPOSE

To develop and evaluate an image-domain noise reduction method for multi-energy CT (MECT) data.

METHODS

Multi-Energy Non-Local Means (MENLM) is a technique that uses the redundant information in MECT images to achieve noise reduction. In this method, spatio-spectral features are used to determine the similarity between pixels, making the similarity evaluation more robust to image noise. The performance of this MENLM filter was tested on images acquired on a whole-body research photon counting CT system. The impact of filtering on image quality was quantitatively evaluated in phantom studies in terms of image noise level (standard deviation of pixel values), noise power spectrum (NPS), in-plane and cross-plane spatial resolution, CT number accuracy, material decomposition performance, and subjective low-contrast spatial resolution using the American College of Radiology (ACR) CT accreditation phantom. Clinical feasibility was assessed by performing MENLM on contrast-enhanced swine images and unenhanced cadaver head images using clinically relevant doses and dose rates.

RESULTS

The phantom studies demonstrated that the MENLM filter reduced noise substantially and still preserved the shape and peak frequency of the NPS. With 80% noise reduction, MENLM filtering caused no degradation of high-contrast spatial resolution, as illustrated by the modulation transfer function (MTF) and slice sensitivity profile (SSP). CT number accuracy was also maintained for all energy channels, demonstrating that energy resolution was not affected by filtering. Material decomposition performance was improved with MENLM filtering. The subjective evaluation using the ACR phantom demonstrated an improvement in low-contrast performance. MENLM achieved effective noise reduction in both contrast-enhanced swine images and unenhanced cadaver head images, resulting in improved detection of subtle vascular structures and the differentiation of white/gray matter.

CONCLUSION

In MECT, MENLM achieved around 80% noise reduction and greatly improved material decomposition performance and the detection of subtle anatomical/low-contrast features while maintaining spatial and energy resolution. MENLM filtering may improve diagnostic or functional analysis accuracy and facilitate radiation dose and contrast media reduction for MECT.