-
Je něco špatně v tomto záznamu ?
Fibrous Cap Thickness Predicts Stable Coronary Plaque Progression: Early Clinical Validation of a Semiautomated OCT Technology
N. Kassis, T. Kovarnik, Z. Chen, JR. Weber, B. Martin, A. Darki, V. Woo, A. Wahle, M. Sonka, JJ. Lopez
Status neindexováno Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
Grantová podpora
R01 EB004640
NIBIB NIH HHS - United States
R01 HL063373
NHLBI NIH HHS - United States
T35 HL120835
NHLBI NIH HHS - United States
NLK
Directory of Open Access Journals
od 2022
PubMed Central
od 2022
ROAD: Directory of Open Access Scholarly Resources
od 2022
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Imaging-based characteristics associated with the progression of stable coronary atherosclerotic lesions are poorly defined. Utilizing a combination of optical coherence tomography (OCT) and intravascular ultrasound (IVUS) imaging, we aimed to characterize the lesions prone to progression through clinical validation of a semiautomated OCT computational program. METHODS: Patients with stable coronary artery disease underwent nonculprit vessel imaging with IVUS and OCT at baseline and IVUS at the 12-month follow-up. After coregistration of baseline and follow-up IVUS images, paired 5-mm segments from each patient were identified, demonstrating the greatest plaque progression and regression as measured by the change in plaque burden. Experienced readers identified plaque features on corresponding baseline OCT segments, and predictors of plaque progression were assessed by multivariable analysis. Each segment then underwent volumetric assessment of the fibrous cap (FC) using proprietary software. RESULTS: Among 23 patients (70% men; median age, 67 years), experienced-reader analysis demonstrated that for every 100 μm increase in mean FC thickness, plaques were 87% less likely to progress (P = .01), which persisted on multivariable analysis controlling for baseline plaque burden (P = .05). Automated FC analysis (n = 17 paired segments) confirmed this finding (P = .01) and found thinner minimal FC thickness (P = .01) and larger FC surface area of <65 μm (P = .02) and <100 μm (P = .04) in progressing segments than in regressing segments. No additional imaging features predicted plaque progression. CONCLUSIONS: A semiautomated FC analysis tool confirmed the significant association between thinner FC and stable coronary plaque progression along entire vessel segments, illustrating the diffuse nature of FC thinning and suggesting a future clinical role in predicting the progression of stable coronary artery disease.
Citace poskytuje Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc22031721
- 003
- CZ-PrNML
- 005
- 20230127131300.0
- 007
- ta
- 008
- 230119s2022 xxu f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1016/j.jscai.2022.100400 $2 doi
- 035 __
- $a (PubMed)36397766
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxu
- 100 1_
- $a Kassis, Nicholas $u Department of Medicine, Division of Cardiology, Loyola University Medical Center, Maywood, Illinois
- 245 10
- $a Fibrous Cap Thickness Predicts Stable Coronary Plaque Progression: Early Clinical Validation of a Semiautomated OCT Technology / $c N. Kassis, T. Kovarnik, Z. Chen, JR. Weber, B. Martin, A. Darki, V. Woo, A. Wahle, M. Sonka, JJ. Lopez
- 520 9_
- $a BACKGROUND: Imaging-based characteristics associated with the progression of stable coronary atherosclerotic lesions are poorly defined. Utilizing a combination of optical coherence tomography (OCT) and intravascular ultrasound (IVUS) imaging, we aimed to characterize the lesions prone to progression through clinical validation of a semiautomated OCT computational program. METHODS: Patie $a BACKGROUND Imaging based characteristics associated with the progression of stable coronary atherosclerotic lesions are poorly defined Utilizing a combination of optical coherence tomography OCT and intravascular ultrasound IVUS imaging we aimed to characterize the lesions prone to progression through clinical validation of a semiautomated OCT computational program METHODS Patients with $a BACKGROUND: Imaging-based characteristics associated with the progression of stable coronary atherosclerotic lesions are poorly defined. Utilizing a combination of optical coherence tomography (OCT) and intravascular ultrasound (IVUS) imaging, we aimed to characterize the lesions prone to progression through clinical validation of a semiautomated OCT computational program. METHODS: Patients with stable coronary artery disease underwent nonculprit vessel imaging with IVUS and OCT at baseline and IVUS at the 12-month follow-up. After coregistration of baseline and follow-up IVUS images, paired 5-mm segments from each patient were identified, demonstrating the greatest plaque progression and regression as measured by the change in plaque burden. Experienced readers identified plaque features on corresponding baseline OCT segments, and predictors of plaque progression were assessed by multivariable analysis. Each segment then underwent volumetric assessment of the fibrous cap (FC) using proprietary software. RESULTS: Among 23 patients (70% men; median age, 67 years), experienced-reader analysis demonstrated that for every 100 μm increase in mean FC thickness, plaques were 87% less likely to progress (P = .01), which persisted on multivariable analysis controlling for baseline plaque burden (P = .05). Automated FC analysis (n = 17 paired segments) confirmed this finding (P = .01) and found thinner minimal FC thickness (P = .01) and larger FC surface area of <65 μm (P = .02) and <100 μm (P = .04) in progressing segments than in regressing segments. No additional imaging features predicted plaque progression. CONCLUSIONS: A semiautomated FC analysis tool confirmed the significant association between thinner FC and stable coronary plaque progression along entire vessel segments, illustrating the diffuse nature of FC thinning and suggesting a future clinical role in predicting the progression of stable coronary artery disease.
- 590 __
- $a NEINDEXOVÁNO
- 655 _2
- $a časopisecké články $7 D016428
- 700 1_
- $a Kovarnik, Tomas $u Second Department of Medicine, Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic
- 700 1_
- $a Chen, Zhi $u Department of Electrical and Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa
- 700 1_
- $a Weber, Joseph R $u Department of Medicine, Division of Cardiology, Loyola University Medical Center, Maywood, Illinois
- 700 1_
- $a Martin, Brendan $u Department of Medicine, Division of Cardiology, Loyola University Medical Center, Maywood, Illinois
- 700 1_
- $a Darki, Amir $u Department of Medicine, Division of Cardiology, Loyola University Medical Center, Maywood, Illinois
- 700 1_
- $a Woo, Vincent $u Department of Medicine, Division of Cardiology, Loyola University Medical Center, Maywood, Illinois
- 700 1_
- $a Wahle, Andreas $u Department of Electrical and Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa
- 700 1_
- $a Sonka, Milan $u Department of Electrical and Computer Engineering and Iowa Institute for Biomedical Imaging, The University of Iowa, Iowa City, Iowa
- 700 1_
- $a Lopez, John J $u Department of Medicine, Division of Cardiology, Loyola University Medical Center, Maywood, Illinois
- 773 0_
- $w MED00210149 $t Journal of the Society for Cardiovascular Angiography & Interventions $x 2772-9303 $g Roč. 1, č. 5 (2022)
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/36397766 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y p $z 0
- 990 __
- $a 20230119 $b ABA008
- 991 __
- $a 20230127131252 $b ABA008
- 999 __
- $a ok $b bmc $g 1889618 $s 1183054
- BAS __
- $a 3
- BAS __
- $a PreBMC-PubMed-not-MEDLINE
- BMC __
- $a 2022 $b 1 $c 5 $e 20220713 $i 2772-9303 $m Journal of the Society for Cardiovascular Angiography & Interventions $n J Soc Cardiovasc Angiogr Interv $x MED00210149
- GRA __
- $a R01 EB004640 $p NIBIB NIH HHS $2 United States
- GRA __
- $a R01 HL063373 $p NHLBI NIH HHS $2 United States
- GRA __
- $a T35 HL120835 $p NHLBI NIH HHS $2 United States
- LZP __
- $a Pubmed-20230119