Correlation of subthalamic nuclei T2 relaxation times with neuropsychological symptoms in patients with Parkinson's disease

Watanabe, Shohei; Suenaga, Koichi; Yamamoto, Asami; Abe, Kazuo; Kotoura, Noriko; Ishikura, Reiichi; Hirota, Shun; Yoshikawa, Hiroaki

doi:10.1016/j.jns.2011.11.018

Cited by 3 publications

(2 citation statements)

References 21 publications

(27 reference statements)

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“…Demographics have been extensively considered and age [10] [11] and disease duration [10] are both predictive factors for motor improvement and for postoperative complications. In terms of imaging, T2 relaxation time in the STN is related to motor improvement [12] [13] and gray matter density maps have been shown to predict weak medication responders [14]. Peralta et al [15] have also shown that differences in the shape of the striatum also reflects differences in the underlying stage and type of Parkinson's disease.…”

Section: Introductionmentioning

confidence: 99%

PassFlow: a multimodal workflow for predicting deep brain stimulation outcomes

et al. 2021

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Purpose: Deep Brain Stimulation (DBS) is a proven therapy for Parkinson's Disease (PD), frequently resulting in an enhancement of motor function. Nonetheless, several undesirable side effects can occur after DBS, which can worsen the quality of life of the patient. Thus, the clinical team has to carefully select patients on whom to perform DBS. Over the past decade, there have been some attempts to relate pre-operative data and DBS clinical outcomes, with most focused on the motor symptomatology. In this paper, we propose a machine learning based method able to predict a large number of DBS clinical outcomes for PD. Methods: We propose a multimodal pipeline, referred to as PassFlow, which predicts 84 clinical post-operative clinical scores. PassFlow is composed of an artificial neural network to compress clinical information, an image processing method from the state-of-the-art to extract morphological biomarkers our of T1 imaging, and an SVM to perform the regressions. We validated PassFlow on 196 PD patients who undergone a DBS. Results: PassFlow showed correlation coefficients as high as 0.71 and were able to significantly predict 63 out of the 84 scores, outperforming a comparative linear method. The number of metrics that are predicted with this pre-operative information was also found to be correlated with the number of patients with this information available, indicating that the PassFlow method is still actively learning. Conclusion: We presented a novel, machine learning based pipeline to predict a variety of post-operative clinical outcomes of DBS for PD patients. PassFlow took into account various bio-markers, arising from different data modalities, showing high correlation coefficients for some scores from pre-operative data only. It indicates that many clinical outcomes of DBS can be predicted agnostic to the specific simulation parameters, as PassFlow has been validated without such stimulation-related information.

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Section: Introductionmentioning

confidence: 99%

PassFlow: a multimodal workflow for predicting deep brain stimulation outcomes

et al. 2021

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“…In research setting, arterial spin labeling and functional MRI using connectivity analysis have found profound differences between PD and HC (Detre et al, 2009, Robinson, et al, 2009). To our knowledge, no previous MRI study aimed at a prediction of DBS outcome, except of a seminal study (Watanabe et al, 2012) that correlated T2r in STN to neurophysiological parameters, disease duration and laterality.…”

Section: Introductionmentioning

confidence: 99%

T2-relaxometry predicts outcome of DBS in idiopathic Parkinson's disease

Lönnfors-Weitzel

Weitzel

Slotboom

et al. 2016

NeuroImage: Clinical

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IntroductionDeep brain stimulation (DBS) nowadays is a well-established treatment of motor symptoms in Parkinson's disease. The subthalamic nucleus (STN) is a common target for DBS, because motor improvements have been shown to be superior to best medical therapy, if DBS electrodes have been appropriately positioned. DBS target identification can be assisted by MRI beyond structural imaging by spatially resolved measurement of T2-relaxation times (T2r).AimWe pose the question, whether T2r of the STN is linked to the severity of the disease and whether outcome of DBS may be correlated to an asymmetric manifestation of the disease. Further, we investigated if abnormal T2r in the STN may be predictive for outcome of DBS.MethodsTwelve patients underwent preoperative MR imaging including a multi echo relaxometry sequence (3 Tesla, Siemens Medical Systems, Erlangen, Germany) ahead of DBS. T2r were determined for STN, substantia nigra (SN), red nucleus (RN) and centrum semiovale (CSO). Unified Parkinson's disease Rating Scale (UPDRS) scores were tested before and after DBS. Patients' T2r and deduced values representing left-right asymmetry of measurements were correlated with UPDRS scores and measures for outcome of DBS. Furthermore, patients' T2r were compared with T2r measurements in 12 healthy controls (HC).ResultsPatients' T2r for SN (mean 45.4 ms ± 4.4 ms) and STN (mean 56.4 ms ± 3.8 ms) were significantly shorter than T2r in HCs for SN (mean 60.7 ± 4.6) and STN (mean 66.1 ms ± 4.0 ms). While no mean T2r asymmetry was found in the SN, patients' mean T2r for STN showed a weakened left-right correlation (Pearson correlation coefficient 0.19 versus 0.72 in HC) indicating asymmetric degeneration. T2r asymmetry was not linked to the more severely affected hemisphere.The respective lower T2r within the left or right target region was significantly correlated to the outcome in terms of UPDRS III improvement in “off” state (Pearson correlation 0.82 corresponding to p ≪ 0.01). Patients with T2r of STN lower than 50 ms showed no response to DBS in the UPDRS.The maximum T2r for SN correlated to the improvement between UPDRS “off” minus and “on” (Dopamine response) but failed to predict DBS outcome.ConclusionsThe lower boundaries of T2r in the STN predict motor outcome in DBS. T2r asymmetry in the STN is not associated with increased clinical symptoms, but with response to therapy. Thus, patients with very low T2r may be inappropriate candidates for DBS.

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