OBJECTIVE: Transcranial Magnetic Stimulation (TMS) has been suggested as a reliable, non-invasive, and inexpensive tool for the diagnosis of neurodegenerative dementias. In this study we assessed the classification performance of TMS parameters in the differential diagnosis of common neurodegenerative disorders, including Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). METHODS: We performed a multicenter study enrolling patients referred to four dementia centers in Italy, in accordance with the Standards for Reporting of Diagnostic Accuracy. All patients underwent TMS assessment at recruitment (index test), with application of reference clinical criteria, to predict different neurodegenerative disorders. The investigators who performed the index test were masked to the results of the reference test and all other investigations. We trained and tested a Random Forests classifier using 5-fold cross validation. The primary outcome measures were the classification accuracy, precision, recall and F1-score of TMS in differentiating each neurodegenerative disorder. RESULTS: 694 participants were included, namely 273 patients diagnosed as AD, 67 as DLB, 207 as FTD, and 147 as healthy controls (HC). A series of 3 binary classifiers was employed, and the prediction model exhibited high classification accuracy (ranging from 0.89 to 0.92), high precision (0.86-0.92), high recall (0.93-0.98), and high F1 scores (0.89-0.95), in differentiating each neurodegenerative disorder. INTERPRETATION: TMS is a non-invasive procedure which reliably and selectively distinguishes AD, DLB, FTD and HC, representing a useful additional screening tool to be used in clinical practice. This article is protected by copyright. All rights reserved.dementia (FTD).

Classification accuracy of TMS for the diagnosis of neurodegenerative dementias

Ranieri, Federico;
2020-01-01

Abstract

OBJECTIVE: Transcranial Magnetic Stimulation (TMS) has been suggested as a reliable, non-invasive, and inexpensive tool for the diagnosis of neurodegenerative dementias. In this study we assessed the classification performance of TMS parameters in the differential diagnosis of common neurodegenerative disorders, including Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). METHODS: We performed a multicenter study enrolling patients referred to four dementia centers in Italy, in accordance with the Standards for Reporting of Diagnostic Accuracy. All patients underwent TMS assessment at recruitment (index test), with application of reference clinical criteria, to predict different neurodegenerative disorders. The investigators who performed the index test were masked to the results of the reference test and all other investigations. We trained and tested a Random Forests classifier using 5-fold cross validation. The primary outcome measures were the classification accuracy, precision, recall and F1-score of TMS in differentiating each neurodegenerative disorder. RESULTS: 694 participants were included, namely 273 patients diagnosed as AD, 67 as DLB, 207 as FTD, and 147 as healthy controls (HC). A series of 3 binary classifiers was employed, and the prediction model exhibited high classification accuracy (ranging from 0.89 to 0.92), high precision (0.86-0.92), high recall (0.93-0.98), and high F1 scores (0.89-0.95), in differentiating each neurodegenerative disorder. INTERPRETATION: TMS is a non-invasive procedure which reliably and selectively distinguishes AD, DLB, FTD and HC, representing a useful additional screening tool to be used in clinical practice. This article is protected by copyright. All rights reserved.dementia (FTD).
2020
Alzheimer’s disease; frontotemporal dementia; dementia with Lewy bodies; transcranial magnetic stimulation; diagnostic accuracy; decision tree; short interval intracortical inhibition; intracortical facilitation; short latency afferent inhibition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1009391
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