Automated segmental-IMT measurement in thin/thick plaque with bulb presence in carotid ultrasound from multiple scanners: Stroke risk assessment

Nobutaka Ikeda, Nilanjan Dey, Aditya Sharma, Ajay Gupta, Soumyo Bose, Suvojit Acharjee, Shoaib Shafique, Elisa Cuadrado-Godia, Tadashi Araki, Luca Saba, John R. Laird, Andrew Nicolaides, Jasjit S. Suri

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Background and objectives Standardization of the carotid IMT requires a reference marker in ultrasound scans. It has been shown previously that manual reference marker and manually created carotid segments are used for measuring IMT in these segments. Manual methods are tedious, time consuming, subjective, and prone to errors. Bulb edge can be considered as a reference marker for measurements of the cIMT. However, bulb edge can be difficult to locate in ultrasound scans due to: (a) low signal to noise ratio in the bulb region as compared to common carotid artery region; (b) uncertainty of bulb location in craniocaudal direction; and (c) variability in carotid bulb shape and size. This paper presents an automated system (a class of AtheroEdge™ system from AtheroPoint™, Roseville, CA, USA) for locating the bulb edge as a reference marker and further develop segmental-IMT (sIMT) which measures IMT in 10 mm segments (namely: s1, s2 and s3) proximal to the bulb edge. Methods The patented methodology uses an integrated approach which combines carotid geometry and pixel-classification paradigms. The system first finds the bulb edge and then measures the sIMT proximal to the bulb edge. The system also estimates IMT in bulb region (bIMT). The 649 image database consists of varying plaque (light, moderate to heavy), image resolutions, shapes, sizes and ethnicity. Results Our results show that the IMT contributions in different carotid segments are as follows: bulb-IMT 34%, s1-IMT 29.46%, s2-IMT 11.48%, and s3-IMT 12.75%, respectively. We compare our automated results against reader's tracings demonstrating the following performance: mean lumen-intima error: 0.01235 ± 0.01224 mm, mean media-adventitia error: 0.020933 ± 0.01539 mm and mean IMT error: 0.01063 ± 0.0031 mm. Our system's Precision of Merit is: 98.23%, coefficient of correlation between automated and Reader's IMT is: 0.998 (p-value < 0.0001). These numbers are improved compared to previous publications by Suri's group which is automated multi-resolution conventional cIMT. Conclusions Our fully automated bulb detection system reports 92.67% precision against ideal bulb edge locations as marked by the reader in the bulb transition zone.

Original languageEnglish (US)
Pages (from-to)73-81
Number of pages9
JournalComputer Methods and Programs in Biomedicine
Volume141
DOIs
StatePublished - Apr 1 2017

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Risk assessment
Ultrasonics
Stroke
Adventitia
Common Carotid Artery
Signal-To-Noise Ratio
Uncertainty
Databases
Light
Image resolution
Standardization
Signal to noise ratio
Pixels
Geometry
Direction compound

Keywords

  • bIMT
  • Carotid ultrasound
  • cIMT
  • Heavy plaque
  • Segmental-IMT
  • Stroke risk assessment

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics

Cite this

Automated segmental-IMT measurement in thin/thick plaque with bulb presence in carotid ultrasound from multiple scanners : Stroke risk assessment. / Ikeda, Nobutaka; Dey, Nilanjan; Sharma, Aditya; Gupta, Ajay; Bose, Soumyo; Acharjee, Suvojit; Shafique, Shoaib; Cuadrado-Godia, Elisa; Araki, Tadashi; Saba, Luca; Laird, John R.; Nicolaides, Andrew; Suri, Jasjit S.

In: Computer Methods and Programs in Biomedicine, Vol. 141, 01.04.2017, p. 73-81.

Research output: Contribution to journalArticle

Ikeda, N, Dey, N, Sharma, A, Gupta, A, Bose, S, Acharjee, S, Shafique, S, Cuadrado-Godia, E, Araki, T, Saba, L, Laird, JR, Nicolaides, A & Suri, JS 2017, 'Automated segmental-IMT measurement in thin/thick plaque with bulb presence in carotid ultrasound from multiple scanners: Stroke risk assessment', Computer Methods and Programs in Biomedicine, vol. 141, pp. 73-81. https://doi.org/10.1016/j.cmpb.2017.01.009
Ikeda, Nobutaka ; Dey, Nilanjan ; Sharma, Aditya ; Gupta, Ajay ; Bose, Soumyo ; Acharjee, Suvojit ; Shafique, Shoaib ; Cuadrado-Godia, Elisa ; Araki, Tadashi ; Saba, Luca ; Laird, John R. ; Nicolaides, Andrew ; Suri, Jasjit S. / Automated segmental-IMT measurement in thin/thick plaque with bulb presence in carotid ultrasound from multiple scanners : Stroke risk assessment. In: Computer Methods and Programs in Biomedicine. 2017 ; Vol. 141. pp. 73-81.
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abstract = "Background and objectives Standardization of the carotid IMT requires a reference marker in ultrasound scans. It has been shown previously that manual reference marker and manually created carotid segments are used for measuring IMT in these segments. Manual methods are tedious, time consuming, subjective, and prone to errors. Bulb edge can be considered as a reference marker for measurements of the cIMT. However, bulb edge can be difficult to locate in ultrasound scans due to: (a) low signal to noise ratio in the bulb region as compared to common carotid artery region; (b) uncertainty of bulb location in craniocaudal direction; and (c) variability in carotid bulb shape and size. This paper presents an automated system (a class of AtheroEdge™ system from AtheroPoint™, Roseville, CA, USA) for locating the bulb edge as a reference marker and further develop segmental-IMT (sIMT) which measures IMT in 10 mm segments (namely: s1, s2 and s3) proximal to the bulb edge. Methods The patented methodology uses an integrated approach which combines carotid geometry and pixel-classification paradigms. The system first finds the bulb edge and then measures the sIMT proximal to the bulb edge. The system also estimates IMT in bulb region (bIMT). The 649 image database consists of varying plaque (light, moderate to heavy), image resolutions, shapes, sizes and ethnicity. Results Our results show that the IMT contributions in different carotid segments are as follows: bulb-IMT 34{\%}, s1-IMT 29.46{\%}, s2-IMT 11.48{\%}, and s3-IMT 12.75{\%}, respectively. We compare our automated results against reader's tracings demonstrating the following performance: mean lumen-intima error: 0.01235 ± 0.01224 mm, mean media-adventitia error: 0.020933 ± 0.01539 mm and mean IMT error: 0.01063 ± 0.0031 mm. Our system's Precision of Merit is: 98.23{\%}, coefficient of correlation between automated and Reader's IMT is: 0.998 (p-value < 0.0001). These numbers are improved compared to previous publications by Suri's group which is automated multi-resolution conventional cIMT. Conclusions Our fully automated bulb detection system reports 92.67{\%} precision against ideal bulb edge locations as marked by the reader in the bulb transition zone.",
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T1 - Automated segmental-IMT measurement in thin/thick plaque with bulb presence in carotid ultrasound from multiple scanners

T2 - Stroke risk assessment

AU - Ikeda, Nobutaka

AU - Dey, Nilanjan

AU - Sharma, Aditya

AU - Gupta, Ajay

AU - Bose, Soumyo

AU - Acharjee, Suvojit

AU - Shafique, Shoaib

AU - Cuadrado-Godia, Elisa

AU - Araki, Tadashi

AU - Saba, Luca

AU - Laird, John R.

AU - Nicolaides, Andrew

AU - Suri, Jasjit S.

PY - 2017/4/1

Y1 - 2017/4/1

N2 - Background and objectives Standardization of the carotid IMT requires a reference marker in ultrasound scans. It has been shown previously that manual reference marker and manually created carotid segments are used for measuring IMT in these segments. Manual methods are tedious, time consuming, subjective, and prone to errors. Bulb edge can be considered as a reference marker for measurements of the cIMT. However, bulb edge can be difficult to locate in ultrasound scans due to: (a) low signal to noise ratio in the bulb region as compared to common carotid artery region; (b) uncertainty of bulb location in craniocaudal direction; and (c) variability in carotid bulb shape and size. This paper presents an automated system (a class of AtheroEdge™ system from AtheroPoint™, Roseville, CA, USA) for locating the bulb edge as a reference marker and further develop segmental-IMT (sIMT) which measures IMT in 10 mm segments (namely: s1, s2 and s3) proximal to the bulb edge. Methods The patented methodology uses an integrated approach which combines carotid geometry and pixel-classification paradigms. The system first finds the bulb edge and then measures the sIMT proximal to the bulb edge. The system also estimates IMT in bulb region (bIMT). The 649 image database consists of varying plaque (light, moderate to heavy), image resolutions, shapes, sizes and ethnicity. Results Our results show that the IMT contributions in different carotid segments are as follows: bulb-IMT 34%, s1-IMT 29.46%, s2-IMT 11.48%, and s3-IMT 12.75%, respectively. We compare our automated results against reader's tracings demonstrating the following performance: mean lumen-intima error: 0.01235 ± 0.01224 mm, mean media-adventitia error: 0.020933 ± 0.01539 mm and mean IMT error: 0.01063 ± 0.0031 mm. Our system's Precision of Merit is: 98.23%, coefficient of correlation between automated and Reader's IMT is: 0.998 (p-value < 0.0001). These numbers are improved compared to previous publications by Suri's group which is automated multi-resolution conventional cIMT. Conclusions Our fully automated bulb detection system reports 92.67% precision against ideal bulb edge locations as marked by the reader in the bulb transition zone.

AB - Background and objectives Standardization of the carotid IMT requires a reference marker in ultrasound scans. It has been shown previously that manual reference marker and manually created carotid segments are used for measuring IMT in these segments. Manual methods are tedious, time consuming, subjective, and prone to errors. Bulb edge can be considered as a reference marker for measurements of the cIMT. However, bulb edge can be difficult to locate in ultrasound scans due to: (a) low signal to noise ratio in the bulb region as compared to common carotid artery region; (b) uncertainty of bulb location in craniocaudal direction; and (c) variability in carotid bulb shape and size. This paper presents an automated system (a class of AtheroEdge™ system from AtheroPoint™, Roseville, CA, USA) for locating the bulb edge as a reference marker and further develop segmental-IMT (sIMT) which measures IMT in 10 mm segments (namely: s1, s2 and s3) proximal to the bulb edge. Methods The patented methodology uses an integrated approach which combines carotid geometry and pixel-classification paradigms. The system first finds the bulb edge and then measures the sIMT proximal to the bulb edge. The system also estimates IMT in bulb region (bIMT). The 649 image database consists of varying plaque (light, moderate to heavy), image resolutions, shapes, sizes and ethnicity. Results Our results show that the IMT contributions in different carotid segments are as follows: bulb-IMT 34%, s1-IMT 29.46%, s2-IMT 11.48%, and s3-IMT 12.75%, respectively. We compare our automated results against reader's tracings demonstrating the following performance: mean lumen-intima error: 0.01235 ± 0.01224 mm, mean media-adventitia error: 0.020933 ± 0.01539 mm and mean IMT error: 0.01063 ± 0.0031 mm. Our system's Precision of Merit is: 98.23%, coefficient of correlation between automated and Reader's IMT is: 0.998 (p-value < 0.0001). These numbers are improved compared to previous publications by Suri's group which is automated multi-resolution conventional cIMT. Conclusions Our fully automated bulb detection system reports 92.67% precision against ideal bulb edge locations as marked by the reader in the bulb transition zone.

KW - bIMT

KW - Carotid ultrasound

KW - cIMT

KW - Heavy plaque

KW - Segmental-IMT

KW - Stroke risk assessment

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