Narrowing of the middle cerebral artery: artificial intelligence methods and comparison of transcranial color coded duplex sonography with conventional TCD.
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 < or =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 < or =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).
Swiercz
Miroslaw
M
Electrical Faculty, Bialystok Technical University, Poland.
Swiat
Maciej
M
Pawlak
Mikolaj
M
Weigele
John
J
Tarasewicz
Roman
R
Sobolewski
Andrzej
A
Hurst
Robert W
RW
Mariak
Zenon D
ZD
Melhem
Elias R
ER
Krejza
Jaroslaw
J
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001185:Artificial Intelligence; D002533:Cerebral Angiography; D002539:Cerebral Arterial Diseases / Q000000981:diagnostic imaging*; D002560:Cerebrovascular Circulation; D003251:Constriction, Pathologic; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D020768:Middle Cerebral Artery / Q000000981:diagnostic imaging* / Q000473:pathology*; D016571:Neural Networks, Computer; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D017585:Ultrasonography, Doppler, Transcranial / Q000379:methods*; D055815:Young Adult