Photon-Counting Detector CT: Key Points Radiologists Should Know

Andrea Esquivel, Andrea Ferrero, Achille Mileto, Francis Baffour, Kelly Horst, Prabhakar Shantha Rajiah, Akitoshi Inoue, Shuai Leng, Cynthia McCollough, Joel G Fletcher, Andrea Esquivel, Andrea Ferrero, Achille Mileto, Francis Baffour, Kelly Horst, Prabhakar Shantha Rajiah, Akitoshi Inoue, Shuai Leng, Cynthia McCollough, Joel G Fletcher

Abstract

Photon-counting detector (PCD) CT is a new CT technology utilizing a direct conversion X-ray detector, where incident X-ray photon energies are directly recorded as electronical signals. The design of the photon-counting detector itself facilitates improvements in spatial resolution (via smaller detector pixel design) and iodine signal (via count weighting) while still permitting multi-energy imaging. PCD-CT can eliminate electronic noise and reduce artifacts due to the use of energy thresholds. Improved dose efficiency is important for low dose CT and pediatric imaging. The ultra-high spatial resolution of PCD-CT design permits lower dose scanning for all body regions and is particularly helpful in identifying important imaging findings in thoracic and musculoskeletal CT. Improved iodine signal may be helpful for low contrast tasks in abdominal imaging. Virtual monoenergetic images and material classification will assist with numerous diagnostic tasks in abdominal, musculoskeletal, and cardiovascular imaging. Dual-source PCD-CT permits multi-energy CT images of the heart and coronary arteries at high temporal resolution. In this special review article, we review the clinical benefits of this technology across a wide variety of radiological subspecialties.

Keywords: Clinical applications; Computed tomography; Diagnostic imaging; Photon counting X-ray detectors; Spectral tomography.

Conflict of interest statement

Cynthia H. McCollough: Research Grant to institution, Siemens Healthcare GmbH. Joel G. Fletcher: Research Grant to institution, Siemens Healthcare GmbH.

Copyright © 2022 The Korean Society of Radiology.

Figures

Fig. 1. Schematic comparison of conventional EIDs…
Fig. 1. Schematic comparison of conventional EIDs and PCDs.
A. EIDs use a scintillator to generate visible light when an incident X-ray photon hits them, then the light is recorded by a photodiode with reflective septa in between detector elements to reduce crosstalk. B. While PCD-CT uses a semiconductor to directly generate positive and negative charges, with negative charges going to pixelated anodes to record each individual photon and its energy. EID = energy integrating detector, PCD = photon-counting detector
Fig. 2. A 74-year-old male clinically diagnosed…
Fig. 2. A 74-year-old male clinically diagnosed with idiopathic non-specific interstitial pneumonia was scanned on conventional energy-integrating detector CT (A) and investigational PCD-CT (B) using a clinical routine protocol.
A, B. PCD-CT demonstrates fine reticulations (arrowheads, B) in the right subpleural right lower lobe, compared to conventional CT, which appears to show ground glass opacities in this region (arrowheads, A). PCD-CT more sharply displays traction bronchiectasis than conventional CT (arrows). PCD = photon-counting detector
Fig. 3. A 56-year-old male with multiple…
Fig. 3. A 56-year-old male with multiple myeloma.
A, B. Axial energy integrating detector-CT (A) and PCD-CT (B) slices through the thoracic spine. Lytic lesions in the thoracic spine are more clearly seen on the PCD-CT image. A lytic lesion in the posterior aspect of the vertebral body with breach of the posterior cortex is more clearly dealinated (dashed arrows). A smaller lytic lesion in the vertebral body (arrows) is more conspicuous on the PCD-CT image. PCD = photon-counting detector
Fig. 4. The incudostapedial joint (arrows), shown…
Fig. 4. The incudostapedial joint (arrows), shown on energy integrating detector-CT (A) and PCD-CT (B) images.
The joint was one of several anatomic structures specifically graded using a 5-point Likert score, with higher scores favoring the quality of the PCD-CT images. Adapted from Benson et al. AJNR Am J Neuroradiol 2022;43:579-584 [18]. PCD = photon-counting detector
Fig. 5. A 70-year-old female with a…
Fig. 5. A 70-year-old female with a history of resected intrahepatic cholangiocarcinoma, gastric bypass, and a side-to-side jejunojejunostomy.
A, B. Both studies were taken at a tube voltage of 120 kV. Coronal energy integrating detector-CT (A) shows the jejunojejunostomy (dashed arrow) but photon-counting detector-CT (B) improves the visualization of the contrast and the sharpness of the folds in the jejunojejunostomy (arrow).
Fig. 6. A 67-year-old female with pancreatic…
Fig. 6. A 67-year-old female with pancreatic adenocarcinoma.
A-D. Compared with axial and coronal 2-mm images acquired with energy integrating detector-CT (A, B), axial and coronal 1-mm images acquired with PCD-CT (C, D) provide better visualization of the hypodense tumor in the uncinate owing to the ability of PCD-CT to highlight iodine contrast; also in these images, the ability of PCD-CT to display thinner slices without substantial increase in image noise is demonstrated. Thinner slices reduce partial volume averaging for small structures and pathologies. PCD = photon-counting detector
Fig. 7. A 64-year-old patient with metastatic…
Fig. 7. A 64-year-old patient with metastatic pancreatic cancer.
A, B. Photon-counting detector-CT image (A) shows a very small liver metastasis in the right posterior section (arrows) confirmed on subsequent MRI (B).
Fig. 8. A 73-year-old female with peritoneal…
Fig. 8. A 73-year-old female with peritoneal dissemination of ovarian cancer.
A. Energy integrating detector-CT demonstrates irregularity of the serosa of the sigmoid colon and questionable nodularity along the anterior peritoneal reflection. B. Photon-counting detector-CT clearly demonstrates small tumor implants causing irregular and nodular-like thickening of the anterior peritoneal reflection (arrows).
Fig. 9. A 69-year-old female patient with…
Fig. 9. A 69-year-old female patient with known peripheral arterial disease.
A, B. 3-dimensional reconstruction images reconstructed from energy integrating detector-CT angiography (A) and 145 mL of iodinated contrast appear similar to PCD-CT angiography images (B) using only 55 mL of the same iodinated contrast agent. This example illustrates the ability to leverage improved iodine signal from PCD-CT for reduced need for iodine contrast. PCD = photon-counting detector
Fig. 10. A 36-year-old male patient with…
Fig. 10. A 36-year-old male patient with gout arthritis with tophi.
A-D. Images obtained using PCD-CT with subsequent material classification show monosodium urate deposition in green at the great toe interphalangeal joint.
Fig. 11. A 6-year-old female clinically diagnosed…
Fig. 11. A 6-year-old female clinically diagnosed with cystic fibrosis was scanned on a PCD-CT (CT dose index: 0.05 mGy inspiration [shown] and 0.05 mGy expiration).
PCD-CT demonstrates cylindrical bronchiectasis in the right middle lobe (arrow). PCD = photon-counting detector
Fig. 12. A 74-year-old male patient with…
Fig. 12. A 74-year-old male patient with known peripheral arterial disease.
A, B. Axial reconstructions in a patient with peripheral arterial disease show calcium blooming in the anterior tibial artery on energy integrating detector-CT (arrow, A). Compared with energy integrating detector-CT reconstruction (A), photon-counting detector-CT reconstruction (B) in the same patient at the same level shows significantly improved visualization of the calcium plaque in the anterior tibial artery (arrow, B) because of which the luminal caliber can be better assessed.
Fig. 13. Calcium separation algorithm.
Fig. 13. Calcium separation algorithm.
A. Axial energy integrating detector-CT reconstruction in a patient with peripheral arterial disease shows a dense calcific plaque in the right common femoral artery (arrow). B. Axial photon-counting detector-CT reconstruction of the same patient with the use of a dedicated calcium separation algorithm shows subtraction of the calcified plaque (arrow).

References

    1. Willemink MJ, Persson M, Pourmorteza A, Pelc NJ, Fleischmann D. Photon-counting CT: technical principles and clinical prospects. Radiology. 2018;289:293–312.
    1. Bartlett DJ, Koo CW, Bartholmai BJ, Rajendran K, Weaver JM, Halaweish AF, et al. High-resolution chest computed tomography imaging of the lungs: impact of 1024 matrix reconstruction and photon-counting detector computed tomography. Invest Radiol. 2019;54:129–137.
    1. Leng S, Rajendran K, Gong H, Zhou W, Halaweish AF, Henning A, et al. 150-µm spatial resolution using photon-counting detector computed tomography technology: technical performance and first patient images. Invest Radiol. 2018;53:655–662.
    1. Leng S, Yu Z, Halaweish A, Kappler S, Hahn K, Henning A, et al. Dose-efficient ultrahigh-resolution scan mode using a photon counting detector computed tomography system. J Med Imaging (Bellingham) 2016;3:043504.
    1. Zhou W, Lane JI, Carlson ML, Bruesewitz MR, Witte RJ, Koeller KK, et al. Comparison of a photon-counting-detector CT with an energy-integrating-detector CT for temporal bone imaging: a cadaveric study. AJNR Am J Neuroradiol. 2018;39:1733–1738.
    1. Zhou W, Montoya J, Gutjahr R, Ferrero A, Halaweish A, Kappler S, et al. Lung nodule volume quantification and shape differentiation with an ultra-high resolution technique on a photon-counting detector computed tomography system. J Med Imaging (Bellingham) 2017;4:043502.
    1. Gutjahr R, Halaweish AF, Yu Z, Leng S, Yu L, Li Z, et al. Human imaging with photon counting-based computed tomography at clinical dose levels: contrast-to-noise ratio and cadaver studies. Invest Radiol. 2016;51:421–429.
    1. Leng S, Zhou W, Yu Z, Halaweish A, Krauss B, Schmidt B, et al. Spectral performance of a whole-body research photon counting detector CT: quantitative accuracy in derived image sets. Phys Med Biol. 2017;62:7216–7232.
    1. Rajendran K, Voss BA, Zhou W, Tao S, DeLone DR, Lane JI, et al. Dose reduction for sinus and temporal bone imaging using photon-counting detector CT with an additional tin filter. Invest Radiol. 2020;55:91–100.
    1. Tao S, Marsh JF, Tao A, Michalak GJ, Rajendran K, McCollough CH, et al. Multi-energy CT imaging for large patients using dual-source photon-counting detector CT. Phys Med Biol. 2020;65:17NT01
    1. Leng S, Bruesewitz M, Tao S, Rajendran K, Halaweish AF, Campeau NG, et al. Photon-counting detector CT: system design and clinical applications of an emerging technology. Radiographics. 2019;39:729–743.
    1. Rajendran K, Petersilka M, Henning A, Shanblatt E, Marsh J, Jr, Thorne J, et al. Full field-of-view, high-resolution, photon-counting detector CT: technical assessment and initial patient experience. Phys Med Biol. 2021;66:205019
    1. Rajendran K, Petersilka M, Henning A, Shanblatt ER, Schmidt B, Flohr TG, et al. First clinical photon-counting detector CT system: technical evaluation. Radiology. 2022;303:130–138.
    1. Inoue A, Johnson TF, White D, Cox CW, Hartman TE, Thorne JE, et al. Estimating the clinical impact of photon-counting-detector CT in diagnosing usual interstitial pneumonia. Invest Radiol. 2022 May; doi: 10.1097/RLI.0000000000000888. [Epub]
    1. Hong G, Baffour F, Glazebrook KN, Thorne J, Marsh J, VanMeter PD, et al. Dual-task convolutional neural network based virtual non-calcium imaging for bone marrow diseases detection in dual energy muscular skeletal CT; The 107th Scientific Assembly & Annual Meeting of the Radiological Society of North America Annual Meeting; 2021 Nov 28-Dec 2; Chicago, IL, USA. Radiological Society of North America; 2021.
    1. Baffour FI, Rajendran K, Glazebrook KN, Thorne JE, Larson NB, Leng S, et al. Ultra-high-resolution imaging of the shoulder and pelvis using photon-counting-detector CT: a feasibility study in patients. Eur Radiol. 2022 Jun; doi: 10.1007/s00330-022-08925-x. [Epub]
    1. Marcus RP, Fletcher JG, Ferrero A, Leng S, Halaweish AF, Gutjahr R, et al. Detection and characterization of renal stones by using photon-counting-based CT. Radiology. 2018;289:436–442.
    1. Benson JC, Rajendran K, Lane JI, Diehn FE, Weber NM, Thorne JE, et al. A new frontier in temporal bone imaging: photon-counting detector CT demonstrates superior visualization of critical anatomic structures at reduced radiation dose. AJNR Am J Neuroradiol. 2022;43:579–584.
    1. Iyer VR, Ehman EC, Khandelwal A, Wells ML, Lee YS, Weber NM, et al. Image quality in abdominal CT using an iodine contrast reduction algorithm employing patient size and weight and low kV CT technique. Acta Radiol. 2020;61:1186–1195.
    1. Hsieh SS, Leng S, Rajendran K, Tao S, McCollough CH. Photon counting CT: clinical applications and future developments. IEEE Trans Radiat Plasma Med Sci. 2021;5:441–452.
    1. Kappler S, Hannemann T, Kraft E, Kreisler B, Niederloehner D, Stierstorfer K, et al. First results from a hybrid prototype CT scanner for exploring benefits of quantum-counting in clinical CT; Proceedings Volume 8313, Medical Imaging 2012: Physics of Medical Imaging; 2012 Mar 2; San Diego, CA, USA. SPIE; 2012.
    1. Kalisz K, Halliburton S, Abbara S, Leipsic JA, Albrecht MH, Schoepf UJ, et al. Update on cardiovascular applications of multienergy CT. Radiographics. 2017;37:1955–1974.
    1. Tao S, Rajendran K, McCollough CH, Leng S. Feasibility of multi-contrast imaging on dual-source photon counting detector (PCD) CT: an initial phantom study. Med Phys. 2019;46:4105–4115.
    1. Yu Z, Leng S, Kappler S, Hahn K, Li Z, Halaweish AF, et al. Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner. J Med Imaging (Bellingham) 2016;3:043503.
    1. Zhou W, Bartlett DJ, Diehn FE, Glazebrook KN, Kotsenas AL, Carter RE, et al. Reduction of metal artifacts and improvement in dose efficiency using photon-counting detector computed tomography and tin filtration. Invest Radiol. 2019;54:204–211.
    1. Koons E, VanMeter PD, Rajendran K, Yu L, McCollough C, Leng S. Improved assessment of coronary artery luminal stenosis with heavy calcifications using high-resolution photon-counting detector CT; Proceedings Volume 12031, Medical Imaging 2022: Physics of Medical Imaging; 2022 Apr 4; San Diego, CA, USA. SPIE; 2022.
    1. Allmendinger T, Nowak T, Flohr T, Klotz E, Hagenauer J, Alkadhi H, et al. Photon-counting detector CT-based vascular calcium removal algorithm: assessment using a cardiac motion phantom. Invest Radiol. 2022;57:399–405.
    1. Sandfort V, Persson M, Pourmorteza A, Noël PB, Fleischmann D, Willemink MJ. Spectral photon-counting CT in cardiovascular imaging. J Cardiovasc Comput Tomogr. 2021;15:218–225.

Source: PubMed

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