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Advances in Photon Counting Detector Imaging

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A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 32381

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Prof. Dr. Hatem Alkadhi

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Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
Interests: cardiovascular imaging; advanced computed tomography technology

Special Issue Information

Dear Colleagues,

Photon-counting detectors constitute a promising new technology in medical imaging, including recent computed tomography (CT) systems. They provide energy-resolved image data at a high spatial resolution without the downside of electronic noise and with optimized tissue contrast. The first prototype and preclinical installations demonstrated many potential clinical benefits of this new technology regarding image quality, precision, radiation dose, and spectral imaging properties, and also highlighted the option to image new, spectrally optimized contrast media. Recently, the first clinical photon-counting CT systems were installed in various centers, fulfilling the expectations of prototype and preclinical systems.

This Special Issue aims to provide a comprehensive insight into this active research area by gathering contributions covering all aspects related to this topic, starting from fundamental questions (e.g., quantitative imaging, quality, resolution, spectral behavior, and radiation dose) to validation in the clinical setting (e.g., cardiovascular, lung, or abdominal imaging). Contributions may, therefore, be related to all new aspects of this exciting technology, which will transform medical imaging in the near future.

Prof. Dr. Hatem Alkadhi
Guest Editor

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Keywords

photon counting detector
computed tomography
spectral imaging
radiation dose
image quality
contrast media

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Published Papers (9 papers)

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Research

10 pages, 2072 KiB

Open AccessArticle

Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data

by Ronald Booij, Niels R. van der Werf, Marcel L. Dijkshoorn, Aad van der Lugt and Marcel van Straten

Diagnostics 2022, 12(6), 1467; https://doi.org/10.3390/diagnostics12061467 - 14 Jun 2022

Cited by 29 | Viewed by 2895

Abstract

To evaluate whether the contrast-to-noise ratio (CNR) of an iodinated contrast agent in virtual monoenergetic images (VMI) from the first clinical photon-counting detector (PCD) CT scanner is superior to VMI CNR from a dual-source dual-energy CT scanner with energy-integrating detectors (EID), two anthropomorphic phantoms in three different sizes (thorax and abdomen, QRM GmbH), in combination with a custom-built insert containing cavities filled with water, and water with 15 mg iodine/mL, were scanned on an EID-based scanner (Siemens SOMATOM Force) and on a PCD-based scanner (Siemens, NAEOTOM Alpha). VMI (range 40–100 keV) were reconstructed without an iterative reconstruction (IR) technique and with an IR strength of 60% for the EID technique (ADMIRE) and closest matching IR strengths of 50% and 75% for the PCD technique (QIR). CNR was defined as the difference in mean CT numbers of water, and water with iodine, divided by the root mean square value of the measured noise in water, and water with iodine. A two-sample t-test was performed to evaluate differences in CNR between images. A p-value < 0.05 was considered statistically significant. For VMI without IR and below 60 keV, the CNR of the PCD-based images at 120 and 90 kVp was up to 55% and 75% higher than the CNR of the EID-based images, respectively (p < 0.05). For VMI above 60 keV, CNRs of PCD-based images at both 120 and 90 kVp were up to 20% lower than the CNRs of EID-based images. Similar or improved performance of PCD-based images in comparison with EID-based images were observed for VMIs reconstructed with IR techniques. In conclusion, with PCD-CT, iodine CNR on low energy VMI (<60 keV) is better than with EID-CT. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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15 pages, 3362 KiB

Open AccessArticle

Photon Counting CT Angiography of the Head and Neck: Image Quality Assessment of Polyenergetic and Virtual Monoenergetic Reconstructions

by Arwed Elias Michael, Jan Boriesosdick, Denise Schoenbeck, Ingo Lopez-Schmidt, Jan Robert Kroeger, Christoph Moenninghoff, Sebastian Horstmeier, Lenhard Pennig, Jan Borggrefe and Julius Henning Niehoff

Diagnostics 2022, 12(6), 1306; https://doi.org/10.3390/diagnostics12061306 - 24 May 2022

Cited by 19 | Viewed by 2736

Abstract

Background: The purpose of the present study was the evaluation of the image quality of polyenergetic and monoenergetic reconstructions (PERs and MERs) of CT angiographies (CTAs) of the head and neck acquired with the novel photon counting CT (PCCT) method in clinical routine. Methods: Thirty-seven patients were enrolled in this retrospective study. Quantitative image parameters of the extracranial, intracranial and cerebral arteries were evaluated for the PER and MER (40–120 keV). Additionally, two radiologists rated the perceived image quality. Results: The mean CTDI_vol used in the PCCT was 8.31 ± 1.19 mGy. The highest signal within the vessels was detected in the 40 keV MER, whereas the lowest noise was detected in the 115 keV MER. The most favorable contrast-to-noise-ratio (CNR) and signal-to-noise-ratio (SNR) were detected in the PER and low keV MER. In the qualitative image analysis, the PER was superior to the MER in all rated criteria. For MER, 60–65 keV was rated as best image quality. Conclusion: Overall, PCCT offers excellent image quality for CTAs of the head and neck. At the current state, the PER of the PCCT seems to be the most favorable reconstruction for diagnostic reporting. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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12 pages, 1860 KiB

Open AccessArticle

Optimal Conspicuity of Liver Metastases in Virtual Monochromatic Imaging Reconstructions on a Novel Photon-Counting Detector CT—Effect of keV Settings and BMI

by Stefanie Bette, Josua A. Decker, Franziska M. Braun, Judith Becker, Mark Haerting, Thomas Haeckel, Michael Gebhard, Franka Risch, Piotr Woźnicki, Christian Scheurig-Muenkler, Thomas J. Kroencke and Florian Schwarz

Diagnostics 2022, 12(5), 1231; https://doi.org/10.3390/diagnostics12051231 - 14 May 2022

Cited by 29 | Viewed by 2559

Abstract

In dual-energy CT datasets, the conspicuity of liver metastases can be enhanced by virtual monoenergetic imaging (VMI) reconstructions at low keV levels. Our study investigated whether this effect can be reproduced in photon-counting detector CT (PCD-CT) datasets. We analyzed 100 patients with liver metastases who had undergone contrast-enhanced CT of the abdomen on a PCD-CT (n = 50) or energy-integrating detector CT (EID-CT, single-energy mode, n = 50). PCD-VMI-reconstructions were performed at various keV levels. Identical regions of interest were positioned in metastases, normal liver, and other defined locations assessing image noise, tumor-to-liver ratio (TLR), and contrast-to-noise ratio (CNR). Patients were compared inter-individually. Subgroup analyses were performed according to BMI. On the PCD-CT, noise and CNR peaked at the low end of the keV spectrum. In comparison with the EID-CT, PCD-VMI-reconstructions exhibited lower image noise (at 70 keV) but higher CNR (for ≤70 keV), despite similar CTDIs. Comparing high- and low-BMI patients, CTDI-upregulation was more modest for the PCD-CT but still resulted in similar noise levels and preserved CNR, unlike the EID-CT. In conclusion, PCD-CT VMIs in oncologic patients demonstrated reduced image noise–compared to a standard EID-CT–and improved conspicuity of hypovascularized liver metastases at low keV values. Patients with higher BMIs especially benefited from constant image noise and preservation of lesion conspicuity, despite a more moderate upregulation of CTDI. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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11 pages, 4521 KiB

Open AccessArticle

Virtual Non-Contrast Reconstructions of Photon-Counting Detector CT Angiography Datasets as Substitutes for True Non-Contrast Acquisitions in Patients after EVAR—Performance of a Novel Calcium-Preserving Reconstruction Algorithm

by Josua A. Decker, Stefanie Bette, Christian Scheurig-Muenkler, Bertram Jehs, Franka Risch, Piotr Woźnicki, Franziska M. Braun, Mark Haerting, Claudia Wollny, Thomas J. Kroencke and Florian Schwarz

Diagnostics 2022, 12(3), 558; https://doi.org/10.3390/diagnostics12030558 - 22 Feb 2022

Cited by 36 | Viewed by 2901

Abstract

The purpose of this study was to evaluate virtual-non contrast reconstructions of Photon-Counting Detector (PCD) CT-angiography datasets using a novel calcium-preserving algorithm (VNC_PC) vs. the standard algorithm (VNC_Conv) for their potential to replace unenhanced acquisitions (TNC) in patients after endovascular aneurysm repair (EVAR). 20 EVAR patients who had undergone CTA (unenhanced and arterial phase) on a novel PCD-CT were included. VNC_Conv- and VNC_PC-series were derived from CTA-datasets and intraluminal signal and noise compared. Three readers evaluated image quality, contrast removal, and removal of calcifications/stent parts and assessed all VNC-series for their suitability to replace TNC-series. Image noise was higher in VNC- than in TNC-series (18.6 ± 5.3 HU, 16.7 ± 7.1 HU, and 14.9 ± 7.1 HU for VNC_Conv-, VNC_PC-, and TNC-series, p = 0.006). Subjective image quality was substantially higher in VNC_PC- than VNC_Conv-series (4.2 ± 0.9 vs. 2.5 ± 0.6; p < 0.001). Aortic contrast removal was complete in all VNC-series. Unlike in VNC_Conv-reconstructions, only minuscule parts of stents or calcifications were erroneously subtracted in VNC_PC-reconstructions. Readers considered 95% of VNC_PC-series fully or mostly suited to replace TNC-series; for VNC_Conv-reconstructions, however, only 75% were considered mostly (and none fully) suited for TNC-replacement. VNC_PC-reconstructions of PCD-CT-angiography datasets have excellent image quality with complete contrast removal and only minimal erroneous subtractions of stent parts/calcifications. They could replace TNC-series in almost all cases. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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13 pages, 5107 KiB

Open AccessArticle

Quantum Iterative Reconstruction for Low-Dose Ultra-High-Resolution Photon-Counting Detector CT of the Lung

by Thomas Sartoretti, Damien Racine, Victor Mergen, Lisa Jungblut, Pascal Monnin, Thomas G. Flohr, Katharina Martini, Thomas Frauenfelder, Hatem Alkadhi and André Euler

Diagnostics 2022, 12(2), 522; https://doi.org/10.3390/diagnostics12020522 - 18 Feb 2022

Cited by 46 | Viewed by 3979

Abstract

The aim of this study was to characterize image quality and to determine the optimal strength levels of a novel iterative reconstruction algorithm (quantum iterative reconstruction, QIR) for low-dose, ultra-high-resolution (UHR) photon-counting detector CT (PCD-CT) of the lung. Images were acquired on a clinical dual-source PCD-CT in the UHR mode and reconstructed with a sharp lung reconstruction kernel at different strength levels of QIR (QIR-1 to QIR-4) and without QIR (QIR-off). Noise power spectrum (NPS) and target transfer function (TTF) were analyzed in a cylindrical phantom. 52 consecutive patients referred for low-dose UHR chest PCD-CT were included (CTDI_vol: 1 ± 0.6 mGy). Quantitative image quality analysis was performed computationally which included the calculation of the global noise index (GNI) and the global signal-to-noise ratio index (GSNRI). The mean attenuation of the lung parenchyma was measured. Two readers graded images qualitatively in terms of overall image quality, image sharpness, and subjective image noise using 5-point Likert scales. In the phantom, an increase in the QIR level slightly decreased spatial resolution and considerably decreased noise amplitude without affecting the frequency content. In patients, GNI decreased from QIR-off (202 ± 34 HU) to QIR-4 (106 ± 18 HU) (p < 0.001) by 48%. GSNRI increased from QIR-off (4.4 ± 0.8) to QIR-4 (8.2 ± 1.6) (p < 0.001) by 87%. Attenuation of lung parenchyma was highly comparable among reconstructions (QIR-off: −849 ± 53 HU to QIR-4: −853 ± 52 HU, p < 0.001). Subjective noise was best in QIR-4 (p < 0.001), while QIR-3 was best for sharpness and overall image quality (p < 0.001). Thus, our phantom and patient study indicates that QIR-3 provides the optimal iterative reconstruction level for low-dose, UHR PCD-CT of the lungs. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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14 pages, 1843 KiB

Open AccessArticle

Applied Machine Learning in Spiral Breast-CT: Can We Train a Deep Convolutional Neural Network for Automatic, Standardized and Observer Independent Classification of Breast Density?

by Anna Landsmann, Jann Wieler, Patryk Hejduk, Alexander Ciritsis, Karol Borkowski, Cristina Rossi and Andreas Boss

Diagnostics 2022, 12(1), 181; https://doi.org/10.3390/diagnostics12010181 - 13 Jan 2022

Cited by 4 | Viewed by 2684

Abstract

The aim of this study was to investigate the potential of a machine learning algorithm to accurately classify parenchymal density in spiral breast-CT (BCT), using a deep convolutional neural network (dCNN). In this retrospectively designed study, 634 examinations of 317 patients were included. After image selection and preparation, 5589 images from 634 different BCT examinations were sorted by a four-level density scale, ranging from A to D, using ACR BI-RADS-like criteria. Subsequently four different dCNN models (differences in optimizer and spatial resolution) were trained (70% of data), validated (20%) and tested on a “real-world” dataset (10%). Moreover, dCNN accuracy was compared to a human readout. The overall performance of the model with lowest resolution of input data was highest, reaching an accuracy on the “real-world” dataset of 85.8%. The intra-class correlation of the dCNN and the two readers was almost perfect (0.92) and kappa values between both readers and the dCNN were substantial (0.71–0.76). Moreover, the diagnostic performance between the readers and the dCNN showed very good correspondence with an AUC of 0.89. Artificial Intelligence in the form of a dCNN can be used for standardized, observer-independent and reliable classification of parenchymal density in a BCT examination. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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15 pages, 2755 KiB

Open AccessArticle

Performance of Spectral Photon-Counting Coronary CT Angiography and Comparison with Energy-Integrating-Detector CT: Objective Assessment with Model Observer

by David C. Rotzinger, Damien Racine, Fabio Becce, Elias Lahoud, Klaus Erhard, Salim A. Si-Mohamed, Joël Greffier, Anaïs Viry, Loïc Boussel, Reto A. Meuli, Yoad Yagil, Pascal Monnin and Philippe C. Douek

Diagnostics 2021, 11(12), 2376; https://doi.org/10.3390/diagnostics11122376 - 16 Dec 2021

Cited by 30 | Viewed by 4203

Abstract

Aims: To evaluate spectral photon-counting CT’s (SPCCT) objective image quality characteristics in vitro, compared with standard-of-care energy-integrating-detector (EID) CT. Methods: We scanned a thorax phantom with a coronary artery module at 10 mGy on a prototype SPCCT and a clinical dual-layer EID-CT under various conditions of simulated patient size (small, medium, and large). We used filtered back-projection with a soft-tissue kernel. We assessed noise and contrast-dependent spatial resolution with noise power spectra (NPS) and target transfer functions (TTF), respectively. Detectability indices (d’) of simulated non-calcified and lipid-rich atherosclerotic plaques were computed using the non-pre-whitening with eye filter model observer. Results: SPCCT provided lower noise magnitude (9–38% lower NPS amplitude) and higher noise frequency peaks (sharper noise texture). Furthermore, SPCCT provided consistently higher spatial resolution (30–33% better TTF₁₀). In the detectability analysis, SPCCT outperformed EID-CT in all investigated conditions, providing superior d’. SPCCT reached almost perfect detectability (AUC ≈ 95%) for simulated 0.5-mm-thick non-calcified plaques (for large-sized patients), whereas EID-CT had lower d’ (AUC ≈ 75%). For lipid-rich atherosclerotic plaques, SPCCT achieved 85% AUC vs. 77.5% with EID-CT. Conclusions: SPCCT outperformed EID-CT in detecting simulated coronary atherosclerosis and might enhance diagnostic accuracy by providing lower noise magnitude, markedly improved spatial resolution, and superior lipid core detectability. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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9 pages, 1910 KiB

Open AccessArticle

Dose Reduction in Coronary Artery Calcium Scoring Using Mono-Energetic Images from Reduced Tube Voltage Dual-Source Photon-Counting CT Data: A Dynamic Phantom Study

by Niels R. van der Werf, Margo van Gent, Ronald Booij, Daniel Bos, Aad van der Lugt, Ricardo P. J. Budde, Marcel J. W. Greuter and Marcel van Straten

Diagnostics 2021, 11(12), 2192; https://doi.org/10.3390/diagnostics11122192 - 25 Nov 2021

Cited by 28 | Viewed by 3057

Abstract

In order to assess coronary artery calcium (CAC) quantification reproducibility for photon-counting computed tomography (PCCT) at reduced tube potential, an anthropomorphic thorax phantom with low-, medium-, and high-density CAC inserts was scanned with PCCT (NAEOTOM Alpha, Siemens Healthineers) at two heart rates: 0 and 60–75 beats per minute (bpm). Five imaging protocols were used: 120 kVp standard dose (IQ level 16, reference), 90 kVp at standard (IQ level 16), 75% and 45% dose and tin-filtered 100 kVp at standard dose (IQ level 16). Each scan was repeated five times. Images were reconstructed using monoE reconstruction at 70 keV. For each heart rate, CAC values, quantified as Agatston scores, were compared with the reference, whereby deviations >10% were deemed clinically relevant. Reference protocol radiation dose (as volumetric CT dose index) was 4.06 mGy. Radiation dose was reduced by 27%, 44%, 67%, and 46% for the 90 kVp standard dose, 90 kVp 75% dose, 90 kVp 45% dose, and Sn100 standard dose protocol, respectively. For the low-density CAC, all reduced tube current protocols resulted in clinically relevant differences with the reference. For the medium- and high-density CAC, the implemented 90 kVp protocols and heart rates revealed no clinically relevant differences in Agatston score based on 95% confidence intervals. In conclusion, PCCT allows for reproducible Agatston scores at a reduced tube voltage of 90 kVp with radiation dose reductions up to 67% for medium- and high-density CAC. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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9 pages, 1396 KiB

Open AccessArticle

Coronary Calcium Scoring with First Generation Dual-Source Photon-Counting CT—First Evidence from Phantom and In-Vivo Scans

by Matthias Eberhard, Victor Mergen, Kai Higashigaito, Thomas Allmendinger, Robert Manka, Thomas Flohr, Bernhard Schmidt, Andre Euler and Hatem Alkadhi

Diagnostics 2021, 11(9), 1708; https://doi.org/10.3390/diagnostics11091708 - 18 Sep 2021

Cited by 47 | Viewed by 5015

Abstract

We evaluated the accuracy of coronary artery calcium (CAC) scoring on a dual-source photon-counting detector CT (PCD-CT). An anthropomorphic chest phantom underwent ECG-gated sequential scanning on a PCD-CT at 120 kV with four radiation dose levels (CTDIvol, 2.0–8.6 mGy). Polychromatic images at 120 kV (T3D) and virtual monoenergetic images (VMI), from 60 to 75 keV without quantum iterative reconstruction (no QIR) and QIR strength levels 1–4, were reconstructed. For reference, the same phantom was scanned on a conventional energy-integrating detector CT (120 kV; filtered back projection) at identical radiation doses. CAC scoring in 20 patients with PCD-CT (120 kV; no QIR and QIR 1–4) were included. In the phantom, there were no differences between CAC scores of different radiation doses (all, p > 0.05). Images with 70 keV, no QIR (CAC score, 649); 65 keV, QIR 3 (656); 65 keV; QIR4 (648) and T3D, QIR4 (656) showed a <1% deviation to the reference (653). CAC scores significantly decreased at increasing QIR levels (all, p < 0.001) and for each 5 keV-increase (all, p < 0.001). Patient data (median CAC score: 86 [inter-quartile range: 38–978] at 70 keV) confirmed relationships and differences between reconstructions from the phantom. First phantom and in-vivo experience with a clinical dual-source PCD-CT system shows accurate CAC scoring with VMI reconstructions at different radiation dose levels. Full article

(This article belongs to the Special Issue Advances in Photon Counting Detector Imaging)

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