Improving Bone Mineral Density Assessment Using Spectral Detector CT

Introduction: Bone mineral density (BMD) analysis by Dual-Energy x-ray Absorptiometry (DXA) can have some false negatives due to overlapping structures in the projections. Spectral Detector CT (SDCT) can overcome these limitations by providing volumetric information. We investigated its performance...

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Veröffentlicht in:Journal of clinical densitometry 2019-07, Vol.22 (3), p.374-381
Hauptverfasser: Van Hedent, Steven, Su, Kuan-Hao, Jordan, David W., Eck, Brendan, Liang, Fan, Kessner, Rivka, Kuo, Jung-Wen, Buls, Nico, Klahr, Paul, Ros, Pablo, Muzic, Raymond F.
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container_end_page 381
container_issue 3
container_start_page 374
container_title Journal of clinical densitometry
container_volume 22
creator Van Hedent, Steven
Su, Kuan-Hao
Jordan, David W.
Eck, Brendan
Liang, Fan
Kessner, Rivka
Kuo, Jung-Wen
Buls, Nico
Klahr, Paul
Ros, Pablo
Muzic, Raymond F.
description Introduction: Bone mineral density (BMD) analysis by Dual-Energy x-ray Absorptiometry (DXA) can have some false negatives due to overlapping structures in the projections. Spectral Detector CT (SDCT) can overcome these limitations by providing volumetric information. We investigated its performance for BMD assessment and compared it to DXA and phantomless volumetric bone mineral density (PLvBMD), the latter known to systematically underestimate BMD. DXA is the current standard for BMD assessment, while PLvBMD is an established alternative for opportunistic BMD analysis using CT. Similarly to PLvBMD, spectral data could allow BMD screening opportunistically, without additional phantom calibration. Methodology: Ten concentrations of dipotassium phosphate (K2HPO4) ranging from 0 to 600 mg/ml, in an acrylic phantom were scanned using SDCT in four different, clinically-relevant scan conditions. Images were processed to estimate the K2HPO4 concentrations. A model representing a human lumbar spine (European Spine Phantom) was scanned and used for calibration via linear regression analysis. After calibration, our method was retrospectively applied to abdominal SDCT scans of 20 patients for BMD assessment, who also had PLvBMD and DXA. Performance of PLvBMD, DXA and our SDCT method were compared by sensitivity, specificity, negative predictive value and positive predictive value for decreased BMD. Results: There was excellent correlation (R2 >0.99, p < 0.01) between true and measured K2HPO4 concentrations for all scan conditions. Overall mean measurement error ranged from −11.5 ± 4.7 mg/ml (−2.8 ± 6.0%) to −12.3 ± 6.3 mg/ml (−4.8 ± 3.0%) depending on scan conditions. Using DXA as a reference standard, sensitivity/specificity for detecting decreased BMD in the scanned patients were 100%/73% using SDCT, 100%/40% using PLvBMD provided T-scores, and 90–100%/40–53% using PLvBMD hydroxyapatite density classifications, respectively. Conclusions: Our results show excellent sensitivity and high specificity of SDCT for detecting decreased BMD, demonstrating clinical feasibility. Further validation in prospective clinical trials will be required.
doi_str_mv 10.1016/j.jocd.2018.10.004
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Spectral Detector CT (SDCT) can overcome these limitations by providing volumetric information. We investigated its performance for BMD assessment and compared it to DXA and phantomless volumetric bone mineral density (PLvBMD), the latter known to systematically underestimate BMD. DXA is the current standard for BMD assessment, while PLvBMD is an established alternative for opportunistic BMD analysis using CT. Similarly to PLvBMD, spectral data could allow BMD screening opportunistically, without additional phantom calibration. Methodology: Ten concentrations of dipotassium phosphate (K2HPO4) ranging from 0 to 600 mg/ml, in an acrylic phantom were scanned using SDCT in four different, clinically-relevant scan conditions. Images were processed to estimate the K2HPO4 concentrations. A model representing a human lumbar spine (European Spine Phantom) was scanned and used for calibration via linear regression analysis. After calibration, our method was retrospectively applied to abdominal SDCT scans of 20 patients for BMD assessment, who also had PLvBMD and DXA. Performance of PLvBMD, DXA and our SDCT method were compared by sensitivity, specificity, negative predictive value and positive predictive value for decreased BMD. Results: There was excellent correlation (R2 &gt;0.99, p &lt; 0.01) between true and measured K2HPO4 concentrations for all scan conditions. Overall mean measurement error ranged from −11.5 ± 4.7 mg/ml (−2.8 ± 6.0%) to −12.3 ± 6.3 mg/ml (−4.8 ± 3.0%) depending on scan conditions. Using DXA as a reference standard, sensitivity/specificity for detecting decreased BMD in the scanned patients were 100%/73% using SDCT, 100%/40% using PLvBMD provided T-scores, and 90–100%/40–53% using PLvBMD hydroxyapatite density classifications, respectively. Conclusions: Our results show excellent sensitivity and high specificity of SDCT for detecting decreased BMD, demonstrating clinical feasibility. Further validation in prospective clinical trials will be required.</description><identifier>ISSN: 1094-6950</identifier><identifier>EISSN: 1559-0747</identifier><identifier>DOI: 10.1016/j.jocd.2018.10.004</identifier><identifier>PMID: 30497869</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Bone mineral density ; Dual-energy CT ; Dual-layer detector ; Osteopenia ; Quantitative computed tomography ; Spectral detector computed tomography</subject><ispartof>Journal of clinical densitometry, 2019-07, Vol.22 (3), p.374-381</ispartof><rights>2018 The International Society for Clinical Densitometry</rights><rights>Copyright © 2018 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-8144aee652892c7d4bbadb939ef60dfdd0af4560d087a880a177f21432983e173</citedby><cites>FETCH-LOGICAL-c356t-8144aee652892c7d4bbadb939ef60dfdd0af4560d087a880a177f21432983e173</cites><orcidid>0000-0002-4065-7459 ; 0000-0001-8336-8748 ; 0000-0003-3974-0797 ; 0000-0002-5994-9507</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jocd.2018.10.004$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30497869$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Van Hedent, Steven</creatorcontrib><creatorcontrib>Su, Kuan-Hao</creatorcontrib><creatorcontrib>Jordan, David W.</creatorcontrib><creatorcontrib>Eck, Brendan</creatorcontrib><creatorcontrib>Liang, Fan</creatorcontrib><creatorcontrib>Kessner, Rivka</creatorcontrib><creatorcontrib>Kuo, Jung-Wen</creatorcontrib><creatorcontrib>Buls, Nico</creatorcontrib><creatorcontrib>Klahr, Paul</creatorcontrib><creatorcontrib>Ros, Pablo</creatorcontrib><creatorcontrib>Muzic, Raymond F.</creatorcontrib><title>Improving Bone Mineral Density Assessment Using Spectral Detector CT</title><title>Journal of clinical densitometry</title><addtitle>J Clin Densitom</addtitle><description>Introduction: Bone mineral density (BMD) analysis by Dual-Energy x-ray Absorptiometry (DXA) can have some false negatives due to overlapping structures in the projections. Spectral Detector CT (SDCT) can overcome these limitations by providing volumetric information. We investigated its performance for BMD assessment and compared it to DXA and phantomless volumetric bone mineral density (PLvBMD), the latter known to systematically underestimate BMD. DXA is the current standard for BMD assessment, while PLvBMD is an established alternative for opportunistic BMD analysis using CT. Similarly to PLvBMD, spectral data could allow BMD screening opportunistically, without additional phantom calibration. Methodology: Ten concentrations of dipotassium phosphate (K2HPO4) ranging from 0 to 600 mg/ml, in an acrylic phantom were scanned using SDCT in four different, clinically-relevant scan conditions. Images were processed to estimate the K2HPO4 concentrations. A model representing a human lumbar spine (European Spine Phantom) was scanned and used for calibration via linear regression analysis. After calibration, our method was retrospectively applied to abdominal SDCT scans of 20 patients for BMD assessment, who also had PLvBMD and DXA. Performance of PLvBMD, DXA and our SDCT method were compared by sensitivity, specificity, negative predictive value and positive predictive value for decreased BMD. Results: There was excellent correlation (R2 &gt;0.99, p &lt; 0.01) between true and measured K2HPO4 concentrations for all scan conditions. Overall mean measurement error ranged from −11.5 ± 4.7 mg/ml (−2.8 ± 6.0%) to −12.3 ± 6.3 mg/ml (−4.8 ± 3.0%) depending on scan conditions. Using DXA as a reference standard, sensitivity/specificity for detecting decreased BMD in the scanned patients were 100%/73% using SDCT, 100%/40% using PLvBMD provided T-scores, and 90–100%/40–53% using PLvBMD hydroxyapatite density classifications, respectively. Conclusions: Our results show excellent sensitivity and high specificity of SDCT for detecting decreased BMD, demonstrating clinical feasibility. 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Spectral Detector CT (SDCT) can overcome these limitations by providing volumetric information. We investigated its performance for BMD assessment and compared it to DXA and phantomless volumetric bone mineral density (PLvBMD), the latter known to systematically underestimate BMD. DXA is the current standard for BMD assessment, while PLvBMD is an established alternative for opportunistic BMD analysis using CT. Similarly to PLvBMD, spectral data could allow BMD screening opportunistically, without additional phantom calibration. Methodology: Ten concentrations of dipotassium phosphate (K2HPO4) ranging from 0 to 600 mg/ml, in an acrylic phantom were scanned using SDCT in four different, clinically-relevant scan conditions. Images were processed to estimate the K2HPO4 concentrations. A model representing a human lumbar spine (European Spine Phantom) was scanned and used for calibration via linear regression analysis. After calibration, our method was retrospectively applied to abdominal SDCT scans of 20 patients for BMD assessment, who also had PLvBMD and DXA. Performance of PLvBMD, DXA and our SDCT method were compared by sensitivity, specificity, negative predictive value and positive predictive value for decreased BMD. Results: There was excellent correlation (R2 &gt;0.99, p &lt; 0.01) between true and measured K2HPO4 concentrations for all scan conditions. Overall mean measurement error ranged from −11.5 ± 4.7 mg/ml (−2.8 ± 6.0%) to −12.3 ± 6.3 mg/ml (−4.8 ± 3.0%) depending on scan conditions. Using DXA as a reference standard, sensitivity/specificity for detecting decreased BMD in the scanned patients were 100%/73% using SDCT, 100%/40% using PLvBMD provided T-scores, and 90–100%/40–53% using PLvBMD hydroxyapatite density classifications, respectively. 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subjects Bone mineral density
Dual-energy CT
Dual-layer detector
Osteopenia
Quantitative computed tomography
Spectral detector computed tomography
title Improving Bone Mineral Density Assessment Using Spectral Detector CT
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