Photon-Counting Computed Tomography (PC-CT) of the spine: impact on diagnostic confidence and radiation dose.
Artifacts
Bone screws
Radiation dosage
Radiology
Tomography, X-ray computed
Journal
European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774
Informations de publication
Date de publication:
Aug 2023
Aug 2023
Historique:
received:
22
09
2022
accepted:
10
02
2023
revised:
23
01
2023
medline:
10
7
2023
pubmed:
9
3
2023
entrez:
8
3
2023
Statut:
ppublish
Résumé
Computed tomography (CT) is employed to evaluate surgical outcome after spinal interventions. Here, we investigate the potential of multispectral photon-counting computed tomography (PC-CT) on image quality, diagnostic confidence, and radiation dose compared to an energy-integrating CT (EID-CT). In this prospective study, 32 patients underwent PC-CT of the spine. Data was reconstructed in two ways: (1) standard bone kernel with 65-keV (PC-CT Sharpness was rated significantly higher (p = 0.009) and noise significantly lower (p < 0.001) in PC-CTstd vs. EID-CT. In the subset of patients with metallic implants, reading scores for PC-CT PC-CT of the spine with high-kiloelectronvolt reconstructions provides sharper images, higher diagnostic confidence, and lower radiation dose in patients with metallic implants. • Compared to energy-integrating CT, photon-counting CT of the spine had significantly higher sharpness and lower image noise while radiation dose was reduced by 45%. • In patients with metallic implants, virtual monochromatic photon-counting images at 130 keV were superior to standard reconstruction at 65 keV in terms of image quality, artifacts, noise, and diagnostic confidence.
Identifiants
pubmed: 36890304
doi: 10.1007/s00330-023-09511-5
pii: 10.1007/s00330-023-09511-5
pmc: PMC10326119
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
5578-5586Subventions
Organisme : Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg
ID : 35-4223.10/20.
Informations de copyright
© 2023. The Author(s).
Références
Albert TJ, Vacarro AR (2016) Spine surgery: tricks of the trade, 3rd edn. Thieme, New York
Ghodasara N, Yi PH, Clark K et al (2019) Postoperative spinal CT: what the radiologist needs to know. Radiographics 39:1840–1861. https://doi.org/10.1148/rg.2019190050
doi: 10.1148/rg.2019190050
pubmed: 31589573
Long Z, DeLone DR, Kotsenas AL et al (2019) Clinical assessment of metal artifact reduction methods in dual-energy CT examinations of instrumented spines. AJR Am J Roentgenol 212:395–401. https://doi.org/10.2214/AJR.18.19757
doi: 10.2214/AJR.18.19757
pubmed: 30667317
Barrett JF, Keat N (2004) Artifacts in CT: recognition and avoidance. Radiographics 24:1679–1691. https://doi.org/10.1148/rg.246045065
doi: 10.1148/rg.246045065
pubmed: 15537976
Dangelmaier J, Schwaiger BJ, Gersing AS et al (2018) Dual layer computed tomography: reduction of metal artefacts from posterior spinal fusion using virtual monoenergetic imaging. Eur J Radiol 105:195–203. https://doi.org/10.1016/j.ejrad.2018.05.034
doi: 10.1016/j.ejrad.2018.05.034
pubmed: 30017279
Coupal TM, Mallinson PI, McLaughlin P et al (2014) Peering through the glare: using dual-energy CT to overcome the problem of metal artefacts in bone radiology. Skeletal Radiol 43:567–575. https://doi.org/10.1007/s00256-013-1802-5
doi: 10.1007/s00256-013-1802-5
pubmed: 24435711
Lee M-J, Kim S, Lee S-A et al (2007) Overcoming artifacts from metallic orthopedic implants at high-field-strength MR imaging and multi-detector CT. Radiographics 27:791–803. https://doi.org/10.1148/rg.273065087
doi: 10.1148/rg.273065087
pubmed: 17495293
Wellenberg RHH, Hakvoort ET, Slump CH et al (2018) Metal artifact reduction techniques in musculoskeletal CT-imaging. Eur J Radiol 107:60–69. https://doi.org/10.1016/j.ejrad.2018.08.010
doi: 10.1016/j.ejrad.2018.08.010
pubmed: 30292274
Katsura M, Sato J, Akahane M et al (2018) Current and novel techniques for metal artifact reduction at CT: practical guide for radiologists. Radiographics 38:450–461. https://doi.org/10.1148/rg.2018170102
doi: 10.1148/rg.2018170102
pubmed: 29528826
Meyer E, Raupach R, Lell M et al (2012) Frequency split metal artifact reduction (FSMAR) in computed tomography. Med Phys 39:1904–1916. https://doi.org/10.1118/1.3691902
doi: 10.1118/1.3691902
pubmed: 22482612
Lai Z, Li L, Cao W (2021) Metal artifact reduction with deep learning based spectral CT. 2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). https://doi.org/10.1109/CISP-BMEI53629.2021.9624386
Arabi H, Zaidi H (2021) Deep learning-based metal artefact reduction in PET/CT imaging. Eur Radiol 31:6384–6396. https://doi.org/10.1007/s00330-021-07709-z
doi: 10.1007/s00330-021-07709-z
pubmed: 33569626
pmcid: 8270868
Willemink MJ, Persson M, Pourmorteza A et al (2018) Photon-counting CT: technical principles and clinical prospects. Radiology 289:293–312. https://doi.org/10.1148/radiol.2018172656
doi: 10.1148/radiol.2018172656
pubmed: 30179101
Zhou W, Schornak R, Michalak G et al (2018) Determination of optimal image type and lowest detectable concentration for iodine detection on a photon counting detector-based multi-energy CT system. Proc SPIE Int Soc Opt Eng 10573:105734U. https://doi.org/10.1117/12.2294949
doi: 10.1117/12.2294949
pubmed: 30034080
pmcid: 6052869
Si-Mohamed SA, Boccalini S, Lacombe H et al (2022) Coronary CT angiography with photon-counting CT: first-in-human results. Radiology 303:303–313. https://doi.org/10.1148/radiol.211780
doi: 10.1148/radiol.211780
pubmed: 35166583
Boccalini S, Si-Mohamed SA, Lacombe H et al (2022) First in-human results of computed tomography angiography for coronary stent assessment with a spectral photon counting computed tomography. Invest Radiol 57:212–221. https://doi.org/10.1097/RLI.0000000000000835
doi: 10.1097/RLI.0000000000000835
pubmed: 34711766
Lloyd JT, Alley DE, Hawkes WG et al (2014) Body mass index is positively associated with bone mineral density in US older adults. Arch Osteoporos 9:175. https://doi.org/10.1007/s11657-014-0175-2
doi: 10.1007/s11657-014-0175-2
pubmed: 24664472
Kim G-U, Chang MC, Kim TU, Lee GW (2020) Diagnostic modality in spine disease: a review. Asian Spine J 14:910–920. https://doi.org/10.31616/asj.2020.0593
Tins B (2010) Technical aspects of CT imaging of the spine. Insights Imaging 1:349–359. https://doi.org/10.1007/s13244-010-0047-2
doi: 10.1007/s13244-010-0047-2
pubmed: 22347928
pmcid: 3259341
Do TD, Sawall S, Heinze S et al (2020) A semi-automated quantitative comparison of metal artifact reduction in photon-counting computed tomography by energy-selective thresholding. Sci Rep 10:21099. https://doi.org/10.1038/s41598-020-77904-3
doi: 10.1038/s41598-020-77904-3
pubmed: 33273590
pmcid: 7713179
Große Hokamp N, Neuhaus V, Abdullayev N et al (2018) Reduction of artifacts caused by orthopedic hardware in the spine in spectral detector CT examinations using virtual monoenergetic image reconstructions and metal-artifact-reduction algorithms. Skeletal Radiol 47:195–201. https://doi.org/10.1007/s00256-017-2776-5
doi: 10.1007/s00256-017-2776-5
pubmed: 28932962
Bamberg F, Dierks A, Nikolaou K et al (2011) Metal artifact reduction by dual energy computed tomography using monoenergetic extrapolation. Eur Radiol 21:1424–1429. https://doi.org/10.1007/s00330-011-2062-1
doi: 10.1007/s00330-011-2062-1
pubmed: 21249370
Laukamp KR, Lennartz S, Neuhaus V-F et al (2018) CT metal artifacts in patients with total hip replacements: for artifact reduction monoenergetic reconstructions and post-processing algorithms are both efficient but not similar. Eur Radiol 28:4524–4533. https://doi.org/10.1007/s00330-018-5414-2
doi: 10.1007/s00330-018-5414-2
pubmed: 29725834
Große Hokamp N, Laukamp KR, Lennartz S et al (2018) Artifact reduction from dental implants using virtual monoenergetic reconstructions from novel spectral detector CT. Eur J Radiol 104:136–142. https://doi.org/10.1016/j.ejrad.2018.04.018
doi: 10.1016/j.ejrad.2018.04.018
pubmed: 29857859
Bongers MN, Schabel C, Thomas C, et al (2015) Comparison and combination of dual-energy- and iterative-based metal artefact reduction on hip prosthesis and dental implants. PLoS One 10:e0143584. https://doi.org/10.1371/journal.pone.0143584
Weiß J, Schabel C, Bongers M et al (2017) Impact of iterative metal artifact reduction on diagnostic image quality in patients with dental hardware. Acta Radiol 58:279–285. https://doi.org/10.1177/0284185116646144
doi: 10.1177/0284185116646144
pubmed: 27166346
Han SC, Chung YE, Lee YH et al (2014) Metal artifact reduction software used with abdominopelvic dual-energy CT of patients with metal hip prostheses: assessment of image quality and clinical feasibility. AJR Am J Roentgenol 203:788–795. https://doi.org/10.2214/AJR.13.10980
doi: 10.2214/AJR.13.10980
pubmed: 25247944
Anhaus JA, Schmidt S, Killermann P, et al (2022) Iterative metal artifact reduction on a clinical photon counting system-technical possibilities and reconstruction selection for optimal results dependent on the metal scenario. Phys Med Biol 67. https://doi.org/10.1088/1361-6560/ac71f0
Byl A, Klein L, Sawall S et al (2021) Photon-counting normalized metal artifact reduction (NMAR) in diagnostic CT. Med Phys 48:3572–3582. https://doi.org/10.1002/mp.14931
doi: 10.1002/mp.14931
pubmed: 33973237
Benson JC, Rajendran K, Lane JI et al (2022) 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 43:579–584. https://doi.org/10.3174/ajnr.A7452
doi: 10.3174/ajnr.A7452
pubmed: 35332019
pmcid: 8993187
Bette SJ, Braun FM, Haerting M et al (2022) Visualization of bone details in a novel photon-counting dual-source CT scanner—comparison with energy-integrating CT. Eur Radiol 32:2930–2936. https://doi.org/10.1007/s00330-021-08441-4
doi: 10.1007/s00330-021-08441-4
pubmed: 34936011
Thomsen FSL, Horstmeier S, Niehoff JH et al (2022) Effective spatial resolution of photon counting CT for imaging of trabecular structures is superior to conventional clinical CT and similar to high resolution peripheral CT. Invest Radiol 57:620–626. https://doi.org/10.1097/RLI.0000000000000873
doi: 10.1097/RLI.0000000000000873
pubmed: 35318968
Rajendran K, Voss BA, Zhou W et al (2020) Dose reduction for sinus and temporal bone imaging using photon-counting detector CT with an additional tin filter. Invest Radiol 55:91–100. https://doi.org/10.1097/RLI.0000000000000614
doi: 10.1097/RLI.0000000000000614
pubmed: 31770297
pmcid: 8522262
Grunz J-P, Heidenreich JF, Lennartz S et al (2022) Spectral shaping via tin prefiltration in ultra-high-resolution photon-counting and energy-integrating detector CT of the temporal bone. Invest Radiol. https://doi.org/10.1097/RLI.0000000000000901
doi: 10.1097/RLI.0000000000000901
pubmed: 36070523
Rajendran K, Petersilka M, Henning A et al (2022) First clinical photon-counting detector CT system: technical evaluation. Radiology 303:130–138. https://doi.org/10.1148/radiol.212579
doi: 10.1148/radiol.212579
pubmed: 34904876