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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, METHODS, RESULTS. Meshes: Adolescent, Adult, Algorithms, Dilatation, Pathologic, Electrocardiography, Female, Heart Ventricles, Humans, Intracranial Pressure, Middle Aged, Monitoring, Physiologic, Pulse, Reaction Time, Signal Processing, Computer-Assisted, Time Factors.
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Are morphological changes of intracranial pressure pulses correlated with acute dilatation of ventricles? Context: Potentially useful information may exist in the morphological changes in intracranial pressure pulse therefore their extraction by automated methods is highly desirable. Long-term continuous recordings of intracranial pressure and electrocardiogram (ECG) signals were analyzed for four patients undergoing intracranial pressure (ICP) monitoring with their implanted shunts externalized and clamped. A novel clustering algorithm was invented to process hours of continuous ICP recordings such that a dominant ICP pulse was extracted every 5 min. Morphological characteristics of dominant ICP pulses were then extracted after detecting characteristics points of a dominant ICP pulse that include the locations of ICP pulse onset, the first (P1), the second (P2), and the third peaks (P3) (or inflection points in the absence of peaks). It was found that ratios of P2 amplitude to P1 amplitude and P3 amplitude to P1 amplitude showed a strong increasing trend for a patient whose lateral ventricles were significantly enlarged (bi-frontal distance was 33 cm on day 0 and 37 cm on day 2) while there were no consistent trends in these morphological features of ICP pulse for the three patients whose ventricles size was not altered during the monitoring period.
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The present work demonstrates the usefulness of this novel ICP pulse analysis algorithm in terms of its potential capabilities of extracting predictive pulse morphological features from long-term continuous ICP recordings that correlate with the development of ventriculomegaly. Final Decision: yes