Table 1
Open in new tab

Summary of studies investigating the qualitative assessment of macrophages using OCT

AuthorStudy aimSampleMethodsResults
Tearney et al (2003)52To investigate the use of OCT for identifying macrophages in fibrous caps26 lipid-rich atherosclerotic arterial segments obtained at autopsyMacrophage density was quantified morphometrically by immunoperoxidase staining with CD68 and then compared with the NSD of the OCT signal intensity

  1. High degree of positive correlation between OCT and histological measurements of fibrous cap macrophage density (R = 0.84, P < 0.0001)

  2. A range of OCT Signal SD thresholds (6.15–6.35%) yielded 100% sensitivity and specificity for identifying caps containing >10% CD68 staining

Phipps et al (2015)53To quantitatively identify macrophages using a novel algorithm including tissue depth, distance from light source, and signal-to-noise ratioFresh 14 coronary arteries from 10 human heartsUse of specific OCT algorithm (an intensity threshold was employed on the normalized algorithm OCT data, considering the distance between the catheter and the surface of the vessel) in 1599 OCT cross-sectional images and validated with histology

  1. Macrophages were present in 57% of bright spot-positive regions

  2. Other aetiologies for bright spots included cellular fibrous tissue (8%), interface of calcium and fibrous tissue (10%), calcium and lipids (5%) and fibrous cap and lipid pool (3%)

  3. Bright spots in the context of thin cap fibro atheroma were caused by macrophages in 94% of cases

Di Vito et al (2015)54To investigate the capability of OCT to identify coronary plaque macrophage presence using tissue property indexes15 epicardial coronary arteriesOCT analysis of histologically correlated regions of interest (ROI) was performed in a stepwise manner
The ROI after histological evaluation were divided in to inflamed (ROI having a macrophage percentage >10) or non-inflamed (ROI having a macrophage percentage <10)
The application of OCT-derived tissue property indexes including signal attenuation, NSD and granulometry index were again applied in a stepwise manner

  1. 43 paired samples (OCT frame and histology sections) were considered suitable as ROIs for analysis. 11 out of 43 ROIs were considered inflamed

  2. ROC curve analysis showed that NSD, granulometry index and signal attenuation had a significant AUC (AUC = 0.906, 0.804 and 0.793 respectively)

  3. a two-step algorithm requiring to first apply NSD with a cut off value of 0.0570 followed by granulometry index was able to identify an inflamed ROI with a sensitivity of 100% and a specificity of 96.8%

Gutierrez-Chico et al (2017)56To investigate whether imaging of macrophages in OCT could be enhanced by means of superparamagnetic nanoparticlesCell pelletsComparison of optical backscattering and attenuation of cell pellets containing RAW 264.7 macrophages with those of macrophagic cell pellets labelled with very small superparamagnetic oxidized nanoparticles (VSOP) by means of light intensity analysis in OCT
The backscattering was estimated by the peak normalization intensity, whilst the attenuation was estimated by the number of pixels between the peak and normalized intensity (PNI)

  1. VSOP-loaded macrophages have higher backscattering than the corresponding unlabelled macrophages (PNI 6.30 vs. 3.15)

  2. There was slightly higher attenuation (PNI 61 vs. 66 pixels)

To evaluate the accuracy of OCT in tissue characterization in vivo25 patients with stable angina undergoing directional coronary atherectomyOCT was performed before and after a single debulking. The debulked region was determined on OCT and classified into fibrous tissue, lipid, calcification, thrombus and macrophage accumulation, which were compared with histology

  1. The sensitivity, specificity, positive predictive value and negative predictive values and predictive accuracy by OCT were respectively:

    • for lipid detection—89%, 75%, 68, 92 and 80%

    • for calcification—50%, 100%, 100, 91 and 92%

    • for macrophage accumulation—86%, 89%, 75, 94 and 88%

Shimokado et al (2018)57To assess agreement between OCT and healed coronary plaques (HCP) ex vivo, and to evaluate the prevalence and characteristics of HCP’s in vivoIn a subset clinical study 60 lesions (in 60 patients) were compared based on presence or absence of HCP73 coronary arteries were examined by OCT from cadavers. The left main coronary and the proximal and middle portion of the 3 coronary arteries were examined
One or more heterogonous signal-rich layers of different optical density located close to luminal surface with clear demarcation from the underlying tissue, which was deemed OCT-derived HCP

  1. In the autopsy study, the sensitivity, specificity, positive predictive value and negative predictive value of OCT-derived HCP to detect histologically defined HCPs were 81%, 98, 93 and 93% respectively

  2. In the clinical study 46 (77%) had OCT-derived HCPs. Microvessels and macrophages were more frequently identified in OCT-derived HCP’s compared with their counterparts (43 vs. 0%; P < 0.01, 70 vs. 21%; P < 0.01, respectively)

Rico-Jimenez et al (2019)58To introduce and validate a simple intravascular OCT image processing method for automated, accurate and fast detection of macrophage infiltration with atherosclerotic plaqueOCT images acquired from 28 cadaveric human coronary artery segmentsThe ratio of the NSD was estimated over two axially adjacent regions of interest in OCT cross-sectional images (B-Scan)
When applied to entire OCT B-scans, the areas of plaque with high NSD ratio were highlighted, which was demonstrated to be correlated with the degree of coronary plaque macrophage infiltration

  1. Using an optimized NSDRatio threshold value, coronary plaque macrophage infiltration could be detected with 88% sensitivity and specificity

  2. For comparison, using an optimized NSD threshold value (considered the standard OCT signature for macrophages), coronary plaque macrophage infiltration could be detected with only 55% sensitivity and specificity

Nicol et al (2021)59To investigate whether tissue attenuation differs between regions with and without neointimal foam cell infiltration, and whether tissue attenuation index could reliably identify patients with neointimal foamy macrophage infiltration as an early sign of atherosclerosis13 autopsy samples of stented coronary arteries. 29 patients with in-stent restenosis undergoing OCT were included13 autopsy samples of stented coronary arteries were assessed to determine attenuation index of neointima with and without foam cells. Based on this, a threshold for homogenous and non-homogenous neointima was determined
The established attenuation index derived from autopsy cases was applied to detect neointimal foam cells in clinical cases presenting with in-stent restenosis

  1. ROC analysis of homogenous neointima using a threshold of −0.796 demonstrated an AUC of 0.87, a sensitivity of 0.93 and a specificity of 0.73

  2. ROC analysis of nonhomogeneous neointima using a threshold of −1.93 demonstrated an AUC of 0.69, a sensitivity of 0.40 and a specificity of 0.95

  3. In patients with in-stent restenosis, neointimal foamy macrophages were detected in 34.2% of homogenous and 43.6% of the non-homogenous neointimal ROIs that were evaluated

AuthorStudy aimSampleMethodsResults
Tearney et al (2003)52To investigate the use of OCT for identifying macrophages in fibrous caps26 lipid-rich atherosclerotic arterial segments obtained at autopsyMacrophage density was quantified morphometrically by immunoperoxidase staining with CD68 and then compared with the NSD of the OCT signal intensity

  1. High degree of positive correlation between OCT and histological measurements of fibrous cap macrophage density (R = 0.84, P < 0.0001)

  2. A range of OCT Signal SD thresholds (6.15–6.35%) yielded 100% sensitivity and specificity for identifying caps containing >10% CD68 staining

Phipps et al (2015)53To quantitatively identify macrophages using a novel algorithm including tissue depth, distance from light source, and signal-to-noise ratioFresh 14 coronary arteries from 10 human heartsUse of specific OCT algorithm (an intensity threshold was employed on the normalized algorithm OCT data, considering the distance between the catheter and the surface of the vessel) in 1599 OCT cross-sectional images and validated with histology

  1. Macrophages were present in 57% of bright spot-positive regions

  2. Other aetiologies for bright spots included cellular fibrous tissue (8%), interface of calcium and fibrous tissue (10%), calcium and lipids (5%) and fibrous cap and lipid pool (3%)

  3. Bright spots in the context of thin cap fibro atheroma were caused by macrophages in 94% of cases

Di Vito et al (2015)54To investigate the capability of OCT to identify coronary plaque macrophage presence using tissue property indexes15 epicardial coronary arteriesOCT analysis of histologically correlated regions of interest (ROI) was performed in a stepwise manner
The ROI after histological evaluation were divided in to inflamed (ROI having a macrophage percentage >10) or non-inflamed (ROI having a macrophage percentage <10)
The application of OCT-derived tissue property indexes including signal attenuation, NSD and granulometry index were again applied in a stepwise manner

  1. 43 paired samples (OCT frame and histology sections) were considered suitable as ROIs for analysis. 11 out of 43 ROIs were considered inflamed

  2. ROC curve analysis showed that NSD, granulometry index and signal attenuation had a significant AUC (AUC = 0.906, 0.804 and 0.793 respectively)

  3. a two-step algorithm requiring to first apply NSD with a cut off value of 0.0570 followed by granulometry index was able to identify an inflamed ROI with a sensitivity of 100% and a specificity of 96.8%

Gutierrez-Chico et al (2017)56To investigate whether imaging of macrophages in OCT could be enhanced by means of superparamagnetic nanoparticlesCell pelletsComparison of optical backscattering and attenuation of cell pellets containing RAW 264.7 macrophages with those of macrophagic cell pellets labelled with very small superparamagnetic oxidized nanoparticles (VSOP) by means of light intensity analysis in OCT
The backscattering was estimated by the peak normalization intensity, whilst the attenuation was estimated by the number of pixels between the peak and normalized intensity (PNI)

  1. VSOP-loaded macrophages have higher backscattering than the corresponding unlabelled macrophages (PNI 6.30 vs. 3.15)

  2. There was slightly higher attenuation (PNI 61 vs. 66 pixels)

To evaluate the accuracy of OCT in tissue characterization in vivo25 patients with stable angina undergoing directional coronary atherectomyOCT was performed before and after a single debulking. The debulked region was determined on OCT and classified into fibrous tissue, lipid, calcification, thrombus and macrophage accumulation, which were compared with histology

  1. The sensitivity, specificity, positive predictive value and negative predictive values and predictive accuracy by OCT were respectively:

    • for lipid detection—89%, 75%, 68, 92 and 80%

    • for calcification—50%, 100%, 100, 91 and 92%

    • for macrophage accumulation—86%, 89%, 75, 94 and 88%

Shimokado et al (2018)57To assess agreement between OCT and healed coronary plaques (HCP) ex vivo, and to evaluate the prevalence and characteristics of HCP’s in vivoIn a subset clinical study 60 lesions (in 60 patients) were compared based on presence or absence of HCP73 coronary arteries were examined by OCT from cadavers. The left main coronary and the proximal and middle portion of the 3 coronary arteries were examined
One or more heterogonous signal-rich layers of different optical density located close to luminal surface with clear demarcation from the underlying tissue, which was deemed OCT-derived HCP

  1. In the autopsy study, the sensitivity, specificity, positive predictive value and negative predictive value of OCT-derived HCP to detect histologically defined HCPs were 81%, 98, 93 and 93% respectively

  2. In the clinical study 46 (77%) had OCT-derived HCPs. Microvessels and macrophages were more frequently identified in OCT-derived HCP’s compared with their counterparts (43 vs. 0%; P < 0.01, 70 vs. 21%; P < 0.01, respectively)

Rico-Jimenez et al (2019)58To introduce and validate a simple intravascular OCT image processing method for automated, accurate and fast detection of macrophage infiltration with atherosclerotic plaqueOCT images acquired from 28 cadaveric human coronary artery segmentsThe ratio of the NSD was estimated over two axially adjacent regions of interest in OCT cross-sectional images (B-Scan)
When applied to entire OCT B-scans, the areas of plaque with high NSD ratio were highlighted, which was demonstrated to be correlated with the degree of coronary plaque macrophage infiltration

  1. Using an optimized NSDRatio threshold value, coronary plaque macrophage infiltration could be detected with 88% sensitivity and specificity

  2. For comparison, using an optimized NSD threshold value (considered the standard OCT signature for macrophages), coronary plaque macrophage infiltration could be detected with only 55% sensitivity and specificity

Nicol et al (2021)59To investigate whether tissue attenuation differs between regions with and without neointimal foam cell infiltration, and whether tissue attenuation index could reliably identify patients with neointimal foamy macrophage infiltration as an early sign of atherosclerosis13 autopsy samples of stented coronary arteries. 29 patients with in-stent restenosis undergoing OCT were included13 autopsy samples of stented coronary arteries were assessed to determine attenuation index of neointima with and without foam cells. Based on this, a threshold for homogenous and non-homogenous neointima was determined
The established attenuation index derived from autopsy cases was applied to detect neointimal foam cells in clinical cases presenting with in-stent restenosis

  1. ROC analysis of homogenous neointima using a threshold of −0.796 demonstrated an AUC of 0.87, a sensitivity of 0.93 and a specificity of 0.73

  2. ROC analysis of nonhomogeneous neointima using a threshold of −1.93 demonstrated an AUC of 0.69, a sensitivity of 0.40 and a specificity of 0.95

  3. In patients with in-stent restenosis, neointimal foamy macrophages were detected in 34.2% of homogenous and 43.6% of the non-homogenous neointimal ROIs that were evaluated

AUC, area under the ROC curve; CD, cluster of differentiation; HCP, healed coronary plaque; NSD, normalized-intensity standard deviation; OCT, optical coherence tomography; PNI, peak and normalized intensity; ROC, receiver operating characteristic; ROI, region of interest; SD, standard deviation; VSOP, very small superparamagnetic oxidized nanoparticles.

Table 1
Open in new tab

Summary of studies investigating the qualitative assessment of macrophages using OCT

AuthorStudy aimSampleMethodsResults
Tearney et al (2003)52To investigate the use of OCT for identifying macrophages in fibrous caps26 lipid-rich atherosclerotic arterial segments obtained at autopsyMacrophage density was quantified morphometrically by immunoperoxidase staining with CD68 and then compared with the NSD of the OCT signal intensity

  1. High degree of positive correlation between OCT and histological measurements of fibrous cap macrophage density (R = 0.84, P < 0.0001)

  2. A range of OCT Signal SD thresholds (6.15–6.35%) yielded 100% sensitivity and specificity for identifying caps containing >10% CD68 staining

Phipps et al (2015)53To quantitatively identify macrophages using a novel algorithm including tissue depth, distance from light source, and signal-to-noise ratioFresh 14 coronary arteries from 10 human heartsUse of specific OCT algorithm (an intensity threshold was employed on the normalized algorithm OCT data, considering the distance between the catheter and the surface of the vessel) in 1599 OCT cross-sectional images and validated with histology

  1. Macrophages were present in 57% of bright spot-positive regions

  2. Other aetiologies for bright spots included cellular fibrous tissue (8%), interface of calcium and fibrous tissue (10%), calcium and lipids (5%) and fibrous cap and lipid pool (3%)

  3. Bright spots in the context of thin cap fibro atheroma were caused by macrophages in 94% of cases

Di Vito et al (2015)54To investigate the capability of OCT to identify coronary plaque macrophage presence using tissue property indexes15 epicardial coronary arteriesOCT analysis of histologically correlated regions of interest (ROI) was performed in a stepwise manner
The ROI after histological evaluation were divided in to inflamed (ROI having a macrophage percentage >10) or non-inflamed (ROI having a macrophage percentage <10)
The application of OCT-derived tissue property indexes including signal attenuation, NSD and granulometry index were again applied in a stepwise manner

  1. 43 paired samples (OCT frame and histology sections) were considered suitable as ROIs for analysis. 11 out of 43 ROIs were considered inflamed

  2. ROC curve analysis showed that NSD, granulometry index and signal attenuation had a significant AUC (AUC = 0.906, 0.804 and 0.793 respectively)

  3. a two-step algorithm requiring to first apply NSD with a cut off value of 0.0570 followed by granulometry index was able to identify an inflamed ROI with a sensitivity of 100% and a specificity of 96.8%

Gutierrez-Chico et al (2017)56To investigate whether imaging of macrophages in OCT could be enhanced by means of superparamagnetic nanoparticlesCell pelletsComparison of optical backscattering and attenuation of cell pellets containing RAW 264.7 macrophages with those of macrophagic cell pellets labelled with very small superparamagnetic oxidized nanoparticles (VSOP) by means of light intensity analysis in OCT
The backscattering was estimated by the peak normalization intensity, whilst the attenuation was estimated by the number of pixels between the peak and normalized intensity (PNI)

  1. VSOP-loaded macrophages have higher backscattering than the corresponding unlabelled macrophages (PNI 6.30 vs. 3.15)

  2. There was slightly higher attenuation (PNI 61 vs. 66 pixels)

To evaluate the accuracy of OCT in tissue characterization in vivo25 patients with stable angina undergoing directional coronary atherectomyOCT was performed before and after a single debulking. The debulked region was determined on OCT and classified into fibrous tissue, lipid, calcification, thrombus and macrophage accumulation, which were compared with histology

  1. The sensitivity, specificity, positive predictive value and negative predictive values and predictive accuracy by OCT were respectively:

    • for lipid detection—89%, 75%, 68, 92 and 80%

    • for calcification—50%, 100%, 100, 91 and 92%

    • for macrophage accumulation—86%, 89%, 75, 94 and 88%

Shimokado et al (2018)57To assess agreement between OCT and healed coronary plaques (HCP) ex vivo, and to evaluate the prevalence and characteristics of HCP’s in vivoIn a subset clinical study 60 lesions (in 60 patients) were compared based on presence or absence of HCP73 coronary arteries were examined by OCT from cadavers. The left main coronary and the proximal and middle portion of the 3 coronary arteries were examined
One or more heterogonous signal-rich layers of different optical density located close to luminal surface with clear demarcation from the underlying tissue, which was deemed OCT-derived HCP

  1. In the autopsy study, the sensitivity, specificity, positive predictive value and negative predictive value of OCT-derived HCP to detect histologically defined HCPs were 81%, 98, 93 and 93% respectively

  2. In the clinical study 46 (77%) had OCT-derived HCPs. Microvessels and macrophages were more frequently identified in OCT-derived HCP’s compared with their counterparts (43 vs. 0%; P < 0.01, 70 vs. 21%; P < 0.01, respectively)

Rico-Jimenez et al (2019)58To introduce and validate a simple intravascular OCT image processing method for automated, accurate and fast detection of macrophage infiltration with atherosclerotic plaqueOCT images acquired from 28 cadaveric human coronary artery segmentsThe ratio of the NSD was estimated over two axially adjacent regions of interest in OCT cross-sectional images (B-Scan)
When applied to entire OCT B-scans, the areas of plaque with high NSD ratio were highlighted, which was demonstrated to be correlated with the degree of coronary plaque macrophage infiltration

  1. Using an optimized NSDRatio threshold value, coronary plaque macrophage infiltration could be detected with 88% sensitivity and specificity

  2. For comparison, using an optimized NSD threshold value (considered the standard OCT signature for macrophages), coronary plaque macrophage infiltration could be detected with only 55% sensitivity and specificity

Nicol et al (2021)59To investigate whether tissue attenuation differs between regions with and without neointimal foam cell infiltration, and whether tissue attenuation index could reliably identify patients with neointimal foamy macrophage infiltration as an early sign of atherosclerosis13 autopsy samples of stented coronary arteries. 29 patients with in-stent restenosis undergoing OCT were included13 autopsy samples of stented coronary arteries were assessed to determine attenuation index of neointima with and without foam cells. Based on this, a threshold for homogenous and non-homogenous neointima was determined
The established attenuation index derived from autopsy cases was applied to detect neointimal foam cells in clinical cases presenting with in-stent restenosis

  1. ROC analysis of homogenous neointima using a threshold of −0.796 demonstrated an AUC of 0.87, a sensitivity of 0.93 and a specificity of 0.73

  2. ROC analysis of nonhomogeneous neointima using a threshold of −1.93 demonstrated an AUC of 0.69, a sensitivity of 0.40 and a specificity of 0.95

  3. In patients with in-stent restenosis, neointimal foamy macrophages were detected in 34.2% of homogenous and 43.6% of the non-homogenous neointimal ROIs that were evaluated

AuthorStudy aimSampleMethodsResults
Tearney et al (2003)52To investigate the use of OCT for identifying macrophages in fibrous caps26 lipid-rich atherosclerotic arterial segments obtained at autopsyMacrophage density was quantified morphometrically by immunoperoxidase staining with CD68 and then compared with the NSD of the OCT signal intensity

  1. High degree of positive correlation between OCT and histological measurements of fibrous cap macrophage density (R = 0.84, P < 0.0001)

  2. A range of OCT Signal SD thresholds (6.15–6.35%) yielded 100% sensitivity and specificity for identifying caps containing >10% CD68 staining

Phipps et al (2015)53To quantitatively identify macrophages using a novel algorithm including tissue depth, distance from light source, and signal-to-noise ratioFresh 14 coronary arteries from 10 human heartsUse of specific OCT algorithm (an intensity threshold was employed on the normalized algorithm OCT data, considering the distance between the catheter and the surface of the vessel) in 1599 OCT cross-sectional images and validated with histology

  1. Macrophages were present in 57% of bright spot-positive regions

  2. Other aetiologies for bright spots included cellular fibrous tissue (8%), interface of calcium and fibrous tissue (10%), calcium and lipids (5%) and fibrous cap and lipid pool (3%)

  3. Bright spots in the context of thin cap fibro atheroma were caused by macrophages in 94% of cases

Di Vito et al (2015)54To investigate the capability of OCT to identify coronary plaque macrophage presence using tissue property indexes15 epicardial coronary arteriesOCT analysis of histologically correlated regions of interest (ROI) was performed in a stepwise manner
The ROI after histological evaluation were divided in to inflamed (ROI having a macrophage percentage >10) or non-inflamed (ROI having a macrophage percentage <10)
The application of OCT-derived tissue property indexes including signal attenuation, NSD and granulometry index were again applied in a stepwise manner

  1. 43 paired samples (OCT frame and histology sections) were considered suitable as ROIs for analysis. 11 out of 43 ROIs were considered inflamed

  2. ROC curve analysis showed that NSD, granulometry index and signal attenuation had a significant AUC (AUC = 0.906, 0.804 and 0.793 respectively)

  3. a two-step algorithm requiring to first apply NSD with a cut off value of 0.0570 followed by granulometry index was able to identify an inflamed ROI with a sensitivity of 100% and a specificity of 96.8%

Gutierrez-Chico et al (2017)56To investigate whether imaging of macrophages in OCT could be enhanced by means of superparamagnetic nanoparticlesCell pelletsComparison of optical backscattering and attenuation of cell pellets containing RAW 264.7 macrophages with those of macrophagic cell pellets labelled with very small superparamagnetic oxidized nanoparticles (VSOP) by means of light intensity analysis in OCT
The backscattering was estimated by the peak normalization intensity, whilst the attenuation was estimated by the number of pixels between the peak and normalized intensity (PNI)

  1. VSOP-loaded macrophages have higher backscattering than the corresponding unlabelled macrophages (PNI 6.30 vs. 3.15)

  2. There was slightly higher attenuation (PNI 61 vs. 66 pixels)

To evaluate the accuracy of OCT in tissue characterization in vivo25 patients with stable angina undergoing directional coronary atherectomyOCT was performed before and after a single debulking. The debulked region was determined on OCT and classified into fibrous tissue, lipid, calcification, thrombus and macrophage accumulation, which were compared with histology

  1. The sensitivity, specificity, positive predictive value and negative predictive values and predictive accuracy by OCT were respectively:

    • for lipid detection—89%, 75%, 68, 92 and 80%

    • for calcification—50%, 100%, 100, 91 and 92%

    • for macrophage accumulation—86%, 89%, 75, 94 and 88%

Shimokado et al (2018)57To assess agreement between OCT and healed coronary plaques (HCP) ex vivo, and to evaluate the prevalence and characteristics of HCP’s in vivoIn a subset clinical study 60 lesions (in 60 patients) were compared based on presence or absence of HCP73 coronary arteries were examined by OCT from cadavers. The left main coronary and the proximal and middle portion of the 3 coronary arteries were examined
One or more heterogonous signal-rich layers of different optical density located close to luminal surface with clear demarcation from the underlying tissue, which was deemed OCT-derived HCP

  1. In the autopsy study, the sensitivity, specificity, positive predictive value and negative predictive value of OCT-derived HCP to detect histologically defined HCPs were 81%, 98, 93 and 93% respectively

  2. In the clinical study 46 (77%) had OCT-derived HCPs. Microvessels and macrophages were more frequently identified in OCT-derived HCP’s compared with their counterparts (43 vs. 0%; P < 0.01, 70 vs. 21%; P < 0.01, respectively)

Rico-Jimenez et al (2019)58To introduce and validate a simple intravascular OCT image processing method for automated, accurate and fast detection of macrophage infiltration with atherosclerotic plaqueOCT images acquired from 28 cadaveric human coronary artery segmentsThe ratio of the NSD was estimated over two axially adjacent regions of interest in OCT cross-sectional images (B-Scan)
When applied to entire OCT B-scans, the areas of plaque with high NSD ratio were highlighted, which was demonstrated to be correlated with the degree of coronary plaque macrophage infiltration

  1. Using an optimized NSDRatio threshold value, coronary plaque macrophage infiltration could be detected with 88% sensitivity and specificity

  2. For comparison, using an optimized NSD threshold value (considered the standard OCT signature for macrophages), coronary plaque macrophage infiltration could be detected with only 55% sensitivity and specificity

Nicol et al (2021)59To investigate whether tissue attenuation differs between regions with and without neointimal foam cell infiltration, and whether tissue attenuation index could reliably identify patients with neointimal foamy macrophage infiltration as an early sign of atherosclerosis13 autopsy samples of stented coronary arteries. 29 patients with in-stent restenosis undergoing OCT were included13 autopsy samples of stented coronary arteries were assessed to determine attenuation index of neointima with and without foam cells. Based on this, a threshold for homogenous and non-homogenous neointima was determined
The established attenuation index derived from autopsy cases was applied to detect neointimal foam cells in clinical cases presenting with in-stent restenosis

  1. ROC analysis of homogenous neointima using a threshold of −0.796 demonstrated an AUC of 0.87, a sensitivity of 0.93 and a specificity of 0.73

  2. ROC analysis of nonhomogeneous neointima using a threshold of −1.93 demonstrated an AUC of 0.69, a sensitivity of 0.40 and a specificity of 0.95

  3. In patients with in-stent restenosis, neointimal foamy macrophages were detected in 34.2% of homogenous and 43.6% of the non-homogenous neointimal ROIs that were evaluated

AUC, area under the ROC curve; CD, cluster of differentiation; HCP, healed coronary plaque; NSD, normalized-intensity standard deviation; OCT, optical coherence tomography; PNI, peak and normalized intensity; ROC, receiver operating characteristic; ROI, region of interest; SD, standard deviation; VSOP, very small superparamagnetic oxidized nanoparticles.

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