Multiway PCA for Early Leak Detection in a Pipeline System of a Steam Boiler-Selected Case Studies.

In the paper the usability of the Multiway PCA (MPCA) method for early detection of leakages in the pipeline system of a steam boiler in a thermal-electrical power plant is presented. A long segment of measurements of selected process variables was divided into a series of "batches" (representing daily recordings of normal behavior of the plant) and used to create the MPCA model of a "healthy" system in a reduced space of three principal components (PC). The periodically updated MPCA model was used to establish the confidence ellipsoid for the "healthy" system in the PC coordinates. [d=replaced]The staff's decision of the probable leak detection is supported by comparison of the current location of the operating point (on the "fault trajectory") with the boundaries of the confidence ellipsoid.The location of the process operating point created the "fault trajectory," which (if located outside the confidence ellipsoid) supported the decision of probable leak detection. It must be emphasized that due to daily and seasonal changes of heat/electricity demands, the process variables have substantially greater variability than in the examples of batch processes studied in literature. Despite those real challenges for the MPCA method, numerical examples confirmed that the presented approach was able to foresee the leaks earlier than the operator, typically 3-5 days before the boiler shutdown. The presented methodology may be useful in implementation of an on-line system, developed to improve safety and maintenance of boilers in a thermal-electrical power plant.

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).

Middle cerebral artery vasospasm: transcranial color-coded duplex sonography versus conventional nonimaging transcranial Doppler sonography.

OBJECTIVE: To prospectively compare accuracies of transcranial color-coded duplex sonography (TCCS) and transcranial Doppler sonography (TCD) in the diagnosis of middle cerebral artery (MCA) vasospasm. DESIGN: Prospective blinded head-to-head comparison TCD and TCCS methods using digital subtraction angiography (DSA) as the reference standard. SETTING: Department of Radiology in a tertiary university health center in a metropolitan area. PATIENTS: Eighty-one consecutive patients (mean age, 53.9 +/- 13.9 years; 48 women). The indication for DSA was subarachnoid hemorrhage in 71 patients (87.6%), stroke or transient ischemic attack in five patients (6.2%), and other reasons in five patients (6.2%). INTERVENTIONS: The MCA was graded as normal, narrowed <50%, and >50% using DSA. The accuracy of ultrasound methods was estimated by total area (Az) under receiver operator characteristic curve. To compare sensitivities of ultrasound methods, McNemar's test was used with mean velocity thresholds of 120 cm/sec for the detection of less advanced, and 200 cm/sec for the more advanced MCA narrowing. MEASUREMENTS AND MAIN RESULTS: Angiographic MCA narrowing 50% in 10 of 135 arteries. Accuracy of TCCS was insignificantly higher than that of TCD in the detection of 50% narrowing, total Az for mean velocity being 0.83 +/- 0.05, 0.77 +/- 0.05, and 0.95 +/- 0.02, 0.86 +/- 0.08, respectively. Sensitivity of TCCS at commonly used threshold of 120 cm/sec for less advanced MCA spasm was significantly better than that of TCD at similar specificity, 55% vs. 39%, p = 0.038, whereas at a threshold of 200 cm/sec used for more advanced spasm, sensitivities and specificities of both methods were not different. CONCLUSION: The accuracy of TCCS and TCD is similar, but TCCS is more sensitive than TCD in the detection of MCA spasm. Sensitivity of both techniques in the detection of mild and more advanced spasm using 120 cm/sec and 200 cm/sec thresholds, respectively, is poor; however, a larger sample is required to increase precision of our sensitivity estimates.

Learning vector quantization neural networks improve accuracy of transcranial color-coded duplex sonography in detection of middle cerebral artery spasm--preliminary report.

To determine the performance of an artificial neural network in transcranial color-coded duplex sonography (TCCS) diagnosis of middle cerebral artery (MCA) spasm. TCCS was prospectively acquired within 2 h prior to routine cerebral angiography in 100 consecutive patients (54M:46F, median age 50 years). Angiographic MCA vasospasm was classified as mild (<25% of vessel caliber reduction), moderate (25-50%), or severe (>50%). A Learning Vector Quantization neural network classified MCA spasm based on TCCS peak-systolic, mean, and end-diastolic velocity data. During a four-class discrimination task, accurate classification by the network ranged from 64.9% to 72.3%, depending on the number of neurons in the Kohonen layer. Accurate classification of vasospasm ranged from 79.6% to 87.6%, with an accuracy of 84.7% to 92.1% for the detection of moderate-to-severe vasospasm. An artificial neural network may increase the accuracy of TCCS in diagnosis of MCA spasm.

Diagnostic cerebral angiography affects the tonus of the major cerebral arteries.

BACKGROUND: Vascular reactions after cerebral angiography have not been hitherto extensively explored due to the lack of a simple, easily available, and safe method for the measurement of cerebral circulation. We attempted to study cerebral circulation with color Doppler transcranial sonography (TCCS) in consecutive patients before and immediately after digital subtraction angiography (DSA). MATERIAL/METHODS: TCCS examination of the major cerebral arteries was carried out in 52 patients (25 females and 27 males), mean age 50.3+/-11.5 years, before and 10-20 minutes after cerebral angiography. A Toshiba Aplio SSA 770A system with a 2.5-MHz sector transducer was used. RESULTS: In general terms, there was a tendency after DSA towards a slight decrease in peak systolic blood velocity and an increase in mean and end-diastolic velocity in all the major cerebral arteries which, in turn, led to a decrease in the impedance index (pulsatility index, PI). In 19 patients, the impedance index as measured in the middle cerebral artery decreased after DSA, in 29 it did not change, while in 4 patients PI increased. Discriminant analysis showed that the factors predisposing individuals to these adverse reactions were a low score on the Glasgow Coma Scale, etiological diagnosis of intracerebral bleeding, and a high value of the impedance index prior to the procedure. CONCLUSIONS: Contrast cerebral angiography may affect the tonus of cerebral vessels. In the majority of patients it caused vasodilatation to varying degrees and in a small sub-group vasoconstriction.

Accuracy of transcranial color Doppler ultrasonography in the diagnosis of middle cerebral artery spasm determined by receiver operating characteristic analysis.

OBJECT: The value of transcranial Doppler ultrasonography for the detection of middle cerebral artery (MCA) spasm has been asserted. None of the published studies, however, has adequately scrutinized the overall diagnostic accuracy of this procedure. There are only sporadic reports concerning the utility of transcranial color Doppler (TCCD) ultrasonography, although this method has been proved to be more precise. In this study the authors attempted to estimate the performance of TCCD ultrasonography in detecting MCA narrowing by using receiver operating characteristic (ROC) curve analysis, based on TCCD studies obtained in a relatively large, randomly selected population of patients. METHODS: Transcranial color Doppler ultrasonography studies were obtained in 100 consecutive patients (54 men and 46 women ages 18-74 years, median age 50 years) routinely referred by neurosurgeons for intraarterial angiography. The M1 segment of the MCA was insonated using a 2.5-MHz probe via a temporal acoustic window, and angle-corrected flow velocities were obtained. Angiographically depicted vasospasm was graded as none, mild (< or = 25% vessel caliber reduction), and moderate to severe (> 25% vessel caliber reduction). The effectiveness of TCCD ultrasonography in diagnosing MCA spasm was evaluated by calculating the areas under the ROC curves (Az). Of the 200 MCAs examined, 173 were successfully visualized with the aid of TCCD ultrasonography. Mild vasospasm was angiographically diagnosed in 15 arteries and moderate-to-severe vasospasm in 28. The best-performing TCCD parameter for the detection of MCA narrowing was revealed to be peak systolic velocity. The Az value for moderate-to-severe vasospasm only was 0.93 and that for all vasospasms was 0.8. The best efficiency, that is, the optimal tradeoff between sensitivity and specificity in diagnosing vasospasms, was associated with a peak systolic velocity of 182 cm/second. CONCLUSIONS: The performance of TCCD ultrasonography in the diagnosis of advanced MCA narrowing is very good, and is acceptable for all vasospasms. The best-performing parameter was peak systolic velocity.