TY - JOUR
T1 - Narrowing of the Middle Cerebral Artery
T2 - Artificial Intelligence Methods and Comparison of Transcranial Color Coded Duplex Sonography with Conventional TCD
AU - Swiercz, Miroslaw
AU - Swiat, Maciej
AU - Pawlak, Mikolaj
AU - Weigele, John
AU - Tarasewicz, Roman
AU - Sobolewski, Andrzej
AU - Hurst, Robert W.
AU - Mariak, Zenon D.
AU - Melhem, Elias R.
AU - Krejza, Jaroslaw
N1 - Funding Information:
This sutdy was supported by the American Heart Association Established Investigator Award grant 044099 N (J. Krejza) and the Polish State Committee for Scientific Research grant 3 T11E 027 28: (M. Swiercz, Z. Mariak, A. Sobolewski, R. Tarasewicz.).
PY - 2010/1
Y1 - 2010/1
N2 - The goal of the study was to compare performances of transcranial color-coded duplex sonography (TCCS) and transcranial Doppler sonography (TCD) in the diagnosis of the middle cerebral artery (MCA) narrowing in the same population of patients using statistical and nonstatistical intelligent models for data analysis. We prospectively collected data from 179 consecutive routine digital subtraction angiography (DSA) procedures performed in 111 patients (mean age 54.17 ± 14.4 years; 59 women, 52 men) who underwent TCD and TCCS examinations simultaneously. Each patient was examined independently using both ultrasound techniques, 267 M1 segments of MCA were assessed and narrowings were classified as ≤50% and >50% lumen reduction. Diagnostic performance was estimated by two statistical and two artificial neural networks (ANN) classification methods. Separate models were constructed for the TCD and TCCS sonographic data, as well as for detection of "any narrowing" and "severe narrowing" of the MCA. Input for each classifier consisted of the peak-systolic, mean and end-diastolic velocities measured with each sonographic method; the output was MCA narrowing. Arterial narrowings less or equal 50% of lumen reduction were found in 55 and >50% narrowings in 26 out of 267 arteries, as indicated by DSA. In the category of "any narrowing" the rate of correct assignment by all models was 82% to 83% for TCCS and 79% to 81% for TCD. In the diagnosis of >50% narrowing the overall classification accuracy remained in the range of 89% to 90% for TCCS data and 90% to 91% for TCD data. For the diagnosis of any narrowing, the sensitivity of the TCCS was significantly higher than that of the TCD, while for diagnosis of >50% MCA narrowing, sensitivity of the TCCS was similar to sensitivity of the TCD. Our study showed that TCCS outperforms conventional TCD in detection of ≤50% MCA narrowing, whereas no significant difference in accuracy between both methods was found in the diagnosis of >50% MCA narrowing. (E-mail: jaroslaw.krejza@uphs.upenn.edu).
AB - The goal of the study was to compare performances of transcranial color-coded duplex sonography (TCCS) and transcranial Doppler sonography (TCD) in the diagnosis of the middle cerebral artery (MCA) narrowing in the same population of patients using statistical and nonstatistical intelligent models for data analysis. We prospectively collected data from 179 consecutive routine digital subtraction angiography (DSA) procedures performed in 111 patients (mean age 54.17 ± 14.4 years; 59 women, 52 men) who underwent TCD and TCCS examinations simultaneously. Each patient was examined independently using both ultrasound techniques, 267 M1 segments of MCA were assessed and narrowings were classified as ≤50% and >50% lumen reduction. Diagnostic performance was estimated by two statistical and two artificial neural networks (ANN) classification methods. Separate models were constructed for the TCD and TCCS sonographic data, as well as for detection of "any narrowing" and "severe narrowing" of the MCA. Input for each classifier consisted of the peak-systolic, mean and end-diastolic velocities measured with each sonographic method; the output was MCA narrowing. Arterial narrowings less or equal 50% of lumen reduction were found in 55 and >50% narrowings in 26 out of 267 arteries, as indicated by DSA. In the category of "any narrowing" the rate of correct assignment by all models was 82% to 83% for TCCS and 79% to 81% for TCD. In the diagnosis of >50% narrowing the overall classification accuracy remained in the range of 89% to 90% for TCCS data and 90% to 91% for TCD data. For the diagnosis of any narrowing, the sensitivity of the TCCS was significantly higher than that of the TCD, while for diagnosis of >50% MCA narrowing, sensitivity of the TCCS was similar to sensitivity of the TCD. Our study showed that TCCS outperforms conventional TCD in detection of ≤50% MCA narrowing, whereas no significant difference in accuracy between both methods was found in the diagnosis of >50% MCA narrowing. (E-mail: jaroslaw.krejza@uphs.upenn.edu).
KW - Artificial neural networks
KW - MCA narrowing
KW - Transcranial Doppler sonography
UR - http://www.scopus.com/inward/record.url?scp=71849109787&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71849109787&partnerID=8YFLogxK
U2 - 10.1016/j.ultrasmedbio.2009.05.005
DO - 10.1016/j.ultrasmedbio.2009.05.005
M3 - Article
C2 - 19854564
AN - SCOPUS:71849109787
SN - 0301-5629
VL - 36
SP - 17
EP - 28
JO - Ultrasound in Medicine and Biology
JF - Ultrasound in Medicine and Biology
IS - 1
ER -