Transcranial Sonography Imaging Research Articles

Prediction of Parkinson's disease by transcranial sonography-based deep learning.

Transcranial sonography has been used as a valid neuroimaging tool to diagnose Parkinson's disease (PD). This study aimed to develop a modified transcranial sonography (TCS) technique based on a deep convolutional neural network (DCNN) model to predict Parkinson's disease. This retrospective diagnostic study was conducted using 1529 transcranial sonography images collected from 854 patients with PD and 775 normal controls admitted to the Second Affiliated Hospital of Soochow University (Suzhou, Jiangsu, China) between September 2019 and May 2022. The data set was divided into training cohorts (570 PD patients and 541 normal controls), and the validation set (184 PD patients and 234 normal controls). Using these datasets, we developed four different DCNN models (ResNet18, ResNet50, ResNet152, and DenseNet121). We then assessed their diagnostic performance, including the area under the receiver operating characteristic (AUROC) curve, specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), and F1 score and compared with traditional diagnostic criteria. Among the 1529 TCS images, 570 PD patients and 541 normal controls from 4 of 6 sonographers of the TCS team were selected as the training cohort, and 184 PD patients and 234 normal controls from the other 2 sonographers were chosen as the validation cohort. There were no sex and age differences between PD patients and normal control subjects in the training and validation cohorts (P values > 0.05). All DCNN models achieved good performance in distinguishing PD patients from normal control subjects on the validation datasets, with diagnostic AUROCs and accuracy of 0.949 (95% CI 0.925, 0.965) and 86.60 for the RestNet18 model, 0.949 (95% CI 0.929, 0.971) and 87.56 for ResNet50, 0.945 (95% CI 0.931, 0.969) and 88.04 for ResNet152, 0.953 (95% CI 0.935, 0.971) and 87.80 for DenseNet121, respectively. On the other hand, the diagnostic accuracy of the traditional diagnostic method was 82.30. The accuracy of all DCNN models was higher than that of traditional diagnostic method. Moreover, the 5k-fold cross-validation results in train datasets showed that these DCNN models are robust. The developed transcranial sonography-based DCNN models performed better than traditional diagnostic criteria, thus improving the sonographer's accuracy in diagnosing PD.

Comparison between Transcranial Sonography and Computerized Tomography Scans to Assess the Midline Shift in Patients with Traumatic Brain Injury.

Midline shift (MLS) of the brain is an important clinical finding diagnosed on computed tomography (CT) imaging and transcranial sonography (TCS) can help diagnose MLS at the bedside and facilitate interventions to improve outcomes. The study aimed to find an association between TCS- and CT-based assessments of MLS in patients with traumatic brain injury (TBI). We included all adult patients with moderate-to-severe TBI of either gender, aged between 18 and 65 years, undergoing intracranial surgery under general anesthesia over a period of 3 months. Consciousness was assessed with the help of the Glasgow coma scale (GCS) and Glasgow coma scale-pupillary (GCS-P) score. We calculated MLS using a CT scan and TCS. Bland Altman graph along with Pearson's and Spearman's coefficient tests was used. A total of 17 patients were analyzed in this study. The MLS was 0.52 ± 0.90 cm using TCS and 0.58 ± 0.39 cm using CT scan. The Pearson's correlation coefficient (r 2) of the difference between MLS measured by TCS and CT imaging was 0.002 (p < 0.05). Transcranial sonography could detect MLS in patients with TBI, provided a minimum time window is used between MLS measurements by TCS and CT scan. Kapoor I, Pandit S, Prabhakar H, Mahajan C. Comparison between Transcranial Sonography and Computerized Tomography Scans to Assess the Midline Shift in Patients with Traumatic Brain Injury. Indian J Crit Care Med 2023;27(1):64-66.

Diagnostic Ability of Radiofrequency Ultrasound in Parkinson's Disease Compared to Conventional Transcranial Sonography and Magnetic Resonance Imaging.

We aimed to estimate tissue displacements’ parameters in midbrain using ultrasound radiofrequency (RF) signals and to compare diagnostic ability of this RF transcranial sonography (TCS)-based dynamic features of disease affected tissues with conventional TCS (cTCS) and magnetic resonance imaging (MRI) while differentiating patients with Parkinson’s disease (PD) from healthy controls (HC). US tissue displacement waveform parametrization by RF TCS for endogenous brain tissue motion, standard neurological examination, cTCS and MRI data collection were performed for 20 PD patients and for 20 age- and sex-matched HC in a prospective manner. Three logistic regression models were constructed, and receiver operating characteristic (ROC) curve analyses were applied. The model constructed of RF TCS-based brain tissue displacement parameters—frequency of high-end spectra peak and root mean square—revealed presumably increased anisotropy in the midbrain and demonstrated rather good diagnostic ability in the PD evaluation, although it was not superior to that of the cTCS or MRI. Future studies are needed in order to establish the true place of RF TCS detected tissue displacement parameters for the evaluation of pathologically affected brain tissue.

Transcranial sonography changes in heterozygotic carriers of the ATP7B gene

PurposeWilson’s disease (WD) is an autosomal recessive disorder of ATP7B gene leading to impaired copper metabolism. Brain imaging, such as magnetic resonance (MR) and transcranial sonography (TCS) in WD patients, shows changes mostly in the basal ganglia. Heterozygotic carriers of one faulty ATP7B gene should not exhibit symptoms of WD, but one in three heterozygotes has copper metabolism abnormalities. This study examined heterozygote ATP7B mutation carriers using TCS to assess any basal ganglia changes compared with healthy controls.MethodsHeterozygote carriers and healthy volunteers underwent the same standard MR and TCS imaging protocols. Heterozygotes were followed for 5 years and monitored for the development of neurological symptoms.ResultsThe study assessed 34 heterozygotes (21 women), with mean age of 43 years (range of 18 to 74 years) and 18 healthy controls (13 women), with mean age of 47 years (range of 20 to 73 years). Bilateral lenticular nucleus (LN) hyperechogenicity was found in 25 heterozygotes, but none of the controls (p < 0.001). Bilateral substantia nigra (SN) hyperechogenicity was found in 8 heterozygotes and one control; another 3 heterozygotes had unilateral SN hyperechogenicity (p = 0.039 for the right; p = 0.176 for the left). Heterozygotes had larger SN area on both sides compared with controls (p = 0.005 right; p = 0.008 left).ConclusionsSN and LN hyperechogenicity were more frequent in heterozygotes than in controls, probably due to copper accumulation, but it remains unknown if this predisposes to brain neurodegeneration.

Diagnostic Performance of Transcranial Sonography for Evaluating Substantia Nigra Hyper-echogenicity in Patients with Parkinson's Disease

To determine the diagnostic performance of transcranial sonography (TCS) in assessing increased echogenic area of the substantia nigra (SN) in patients with Parkinson's disease (PD). Institutional review board approval was obtained for this retrospective study. A total of 278 PD patients (mean age: 64.7 ± 9.8 y, 100 women) and 300 healthy control patients (mean age: 63.6 ± 9.3 y, 97 women) were referred for TCS assessment of SN hyper-echogenicity (SN+) from June 2016 to December 2018. Two sonographers independently measured the sizes of the echogenic areas of the SN by TCS imaging in both PD patients and healthy controls. The diagnostic sensitivity, specificity and accuracy of TCS imaging were compared between PD patients and healthy controls. Inter-rater agreement was assessed with the Cohen's κ statistic. The sensitivity, specificity and accuracy of readers 1 and 2, respectively, for the identification of SN+ in TCS were 90.3% and 89.6% (251 and 249 of 278), 89.3% and 88.3% (268 and 265 of 300) and 89.8% and 88.9% (519 and 514 of 578). Inter-observer agreement was excellent (к = 0.84). The area under the receiver operating characteristic curve (AUC) for differentiation of PD patients from healthy controls was 0.92 for reader 1 and 0.91 for reader 2. Cutoff values of 0.20 and 0.21 cm2 were derived from the assessments performed by readers 1 and 2, respectively. We defined 0.20 cm2 as the optimal cutoff value because it had a higher AUC. TCS is a promising diagnostic technique and can be very helpful in differentiating PD patients from healthy individuals.

P.483 Transcranial sonography imaging of brainstem raphe, substantia nigra and cerebral ventricles in patients with geriatric depression

P.483 Transcranial sonography imaging of brainstem raphe, substantia nigra and cerebral ventricles in patients with geriatric depression

Impact of region of interest size on transcranial sonography based computer-aided diagnosis for Parkinson's disease.

Transcranial sonography (TCS) has gained increasing application for diagnosis of Parkinson's disease (PD) in clinical practice in recent years, because most PD patients, even in the early stage of PD, have abnormal hyperechogenicity of the substantia nigra (SN) in brainstem shown in TCS images. Therefore, the region of interest (ROI) for feature extraction should cover the SN region in a computer-aided diagnosis (CAD) system. The ROI size naturally affects the feature representation. However, there currently exist no unified standard for determining the size of ROI. In this work, we quantitatively compare the performance of TCS-based CAD with three sizes of ROIs, namely the entire midbrain (EM) region, the half of midbrain (HoM) region and the SN region. The experimental results on the original extracted features and the features by dimensionality reduction show that ROI covering the EM region achieves the overall best diagnosis performance. The results indicates that the neighboring regions around SN might also have abnormal symptoms, which cannot be clearly observed with naked eyes. It suggests that the large ROI includes more information for feature representation to improve the diagnosis performance of TCS-based CAD for PD.

Multiple Kernel Learning Based Classification of Parkinson's Disease With Multi-Modal Transcranial Sonography.

Parkinson's Disease (PD) is the most common motor neurodegenerative disease in elderly population. Transcranial sonography (TCS) has become a popular imaging tool for diagnosis of PD in clinical practice. Moreover, several pioneering work have developed the computer-aided diagnosis (CAD) for PD with the transcranial B-mode sonography (TBS). It is worth noting that TCS not only has the TBS modality, but also can image the blood flow of major cerebral arteries, which is named transcranial Doppler sonography (TDS). TDS also has been applied to evaluate PD patients with orthostatic hypotension. However, the TDS-based CAD for PD has not been investigated. Since TBS and TDS provide the complementary structural and functional information about brain, it is feasible to develop a multi-modal TCS-based CAD for PD by combining both TBS and TDS. Therefore, in this work, we propose a multiple kernel learning (MKL) based CAD for PD with multi-modal TCS imaging. Particularly, the statistical and texture features are extracted from the midbrain region from TBS images, and the features about blood flow are calculated from the spectrum curves in TDS. The multi-modal features are then fed to a MKL classifier for classification of PD. The experimental results show that the multi-modal TCS-based method outperforms both the single-modal TBS- and TDS-based algorithm, which suggests the feasibility and effectiveness of combining TBS and TDS for diagnosis of PD.

Transcranial sonography image characteristics in different Parkinson's disease subtypes.

Recently, Parkinson's disease (PD) has been classified into three subtypes: postural instability gait difficulty (PIGD), tremor dominate (TD), and indeterminate PD. Transcranial sonography (TCS) is considered to be an important tool to diagnose PD. However, it is uncertain that whether there are differences in TCS image characteristics in different PD subtypes, so 373 idiopathic PD (188 PIGD, 108 TD, 77 indeterminate PD) were registered and received TCS in our investigation; also, the association between clinical characteristics and TCS results in different PD subtypes was analyzed. In accordance with several previous studies, we detected substantia nigra (SN) by TCS in 85.4% of patients with idiopathic PD; we concluded that PIGD patients had more serious disease than TD and indeterminate PD group (p<0.05). They always had larger SN hyperechogenicity areas on TCS (p<0.05), and we found that there was no correlation between SN hyperechogenicity and disease duration or severity (p>0.05). Similarly, abnormal brainstem raphe signal was also more often in PIGD group than in TD and indeterminate PD group (p<0.05), which might imply that PIGD group was vulnerable to suffer from depression in the future.

Transcranial Sonography in Mitochondrial Membrane Protein-Associated Neurodegeneration

IntroductionAlthough the nature of basal ganglia hyperechogenicity in transcranial sonography (TCS) examinations remains unclear, many studies have shown associations between hyperechogenicity and iron accumulation. The role of iron in basal ganglia hyperechogenicity raises interest in the use of TCS in forms of neurodegeneration with brain iron accumulation (NBIA). Here we analyzed TCS and magnetic resonance imaging (MRI) findings among patients affected by one type of NBIA, mitochondrial membrane protein-associated neurodegeneration (MPAN).MethodsInvestigations using MRI and TCS were performed on 13 patients exhibiting a C19orf12 gene mutation.ResultsThe use of T2/T2* MRI revealed hypointense lesions restricted to the globus pallidus and substantia nigra. Using TCS examination, 12 patients exhibited bilateral hyperechogenicity of the lenticular nucleus, while no patients showed substantia nigra hyperechogenicity.ConclusionInvestigations with TCS revealed a distinctive hyperechogenicity pattern of the basal ganglia in MPAN patients, which might be useful for differential diagnostics. The variable TCS imaging findings in NBIA patients may result from the presence of different iron content, iron binding partners, such as ferritin and neuromelanin, as well as structural changes, such as gliosis.

Use of Gray-Level Histograms to Assess Substantia Nigra Echogenicity in Transcranial Sonography Images of Parkinson Disease Patients

A substantial body of research has shown that Parkinson disease (PD) patients display an enlarged hyperechogenic substantia nigra (SN) by transcranial sonography (TCS). Nonetheless, the categorization of SN echogenicity is still subjective. A method is described to quantify SN echogenicity based on the gray-level histograms of digitized TCS images. In 31 PD patients and 57 controls, the gray-scale mean (GSM) of the SN, mesencephalon, and basal cisterns and their ratios were assessed using image-editing computer software. The GSM values were compared between the groups and correlated with age, SN area, and disease duration. The SN GSM was significantly higher in the PD group ( P &lt; .05) with a positive correlation with age but not with disease duration. In this cohort of participants, mesencephalon echogenicity was found to increase with disease duration. These results would suggest quantitatively SN hyperechogenicity in PD. Quantifying SN echogenicity is feasible and might minimize subjectivity in PD diagnosis by TCS. The method has the potential to disclose subtle changes in other midbrain structures’ echogenicity engendered by the disease process as well.

Transcranial sonography: an accurate and reliable diagnostic test for Parkinson’s disease

ABSTRACT Background: Transcranial sonography (TCS) provides two-dimensional sonographic images of the brain parenchyma through the intact skull. Objective: To determine the accuracy and reliability of TCS and of a novel methodology for echogenicity quantification in post hoc analysis of TCS images for the diagnosis of Parkinson’s disease (PD). Method: 227 participants had standardized TCS examination. Gray scale mean (GSM) of mesencephalic structures was determined from stored images. Results: 10.6% had no bone windows. The groups included 77 PD patients and [...]

Transcranial sonography (TCS) of brain parenchyma in movement disorders: quality standards, diagnostic applications and novel technologies.

Transcranial B-mode sonography (TCS) of brain parenchyma is being increasingly used as a diagnostic tool in movement disorders. Compared to other neuroimaging modalities such as magnetic resonance imaging (MRI) and computed tomography, TCS can be performed today with portable machines and has the advantages of noninvasiveness and high resistance to movement artifacts. In distinct brain disorders TCS detects abnormalities that cannot be visualized or can only be visualized with significant effort with other imaging methods. In the field of movement disorders, TCS has been established mainly as a tool for the early and differential diagnosis of Parkinson's disease. The postoperative position control of deep brain stimulation electrodes, especially in the subthalamic nucleus, can reliably and safely be performed with TCS. The present update review summarizes the current methodological standards and defines quality criteria of adequate TCS imaging and assessment of diagnostically relevant deep brain structures such as substantia nigra, brainstem raphe, basal ganglia and ventricles. Finally, an overview is given on recent technological advances including TCS-MRI fusion imaging and upcoming technologies of digitized image analysis aiming at a more investigator-independent assessment of deep brain structures on TCS.

Automated segmentation of transcranial sonographic images in the diagnostics of Parkinson’s disease

Images captured during routine clinical transcranial sonography (TCS) examination are of a low resolution, so can be confusing for diagnostic evaluations. Manual segmentation of brain structures (areas of the midbrain and substantia nigra (SN)) that are of special interest cause inter-observer and intra-observer variability, thus restricting the reliability of Parkinson disease (PD) diagnostics. This paper presents a new technique for automated segmentation applicable to low resolution sonographic images, and particularly to brain structures related to PD. The segmentation was performed by a modified shape-based active contour (AC) segmentation algorithm. In order to suppress the speckle noise and to improve the AC segmentation, a pre-processing technique based on the averaging of adjusted spatially varying TCS images is proposed. The latter technique was tested on clinical TCS images. The results of the automated segmentation were compared with the manual markings. Two experts on the 40TCS images performed these markings. The comparison showed that an automated method is effective when segmentation of the midbrain is performed (averaged overlap between regions obtained automatically and outlined manually was 73.10±7.45%). The results of the segmentation of the SN area showed that a sufficiently correct contour of this area could also be obtained, but the accuracy of the segmentation is related to the image quality. It should be emphasised that the main difficulty in evaluating the accuracy of automated segmentation of the SN was the indefinite “gold standard” (variation between the measurements of two experts with different experience was found). And, therefore, the diagnostic reliability of the proposed technique was inconclusive.

Intra- and post-operative monitoring of deep brain implants using transcranial ultrasound

Transcranial sonography (TCS) of the brain parenchyma meanwhile allows a high-resolution imaging of deep brain structures in the majority of adults. A new application of TCS is the intra- and post-operative visualization with TCS and the TCS-assisted insertion of deep brain stimulation (DBS) electrodes. In pilot studies it has been shown that the TCS-assisted insertion of DBS electrodes into the subthalamic nucleus and the globus pallidus interna is feasible and safe provided the exact knowledge on the extent of electrode TCS imaging artifacts. Even more, TCS can be recommended for the post-operative monitoring of DBS electrode position. Dislocation of a DBS electrode can be easily detected. In a recent longitudinal study we could demonstrate that TCS measures of lead coordinates agreed with MRI measures in anterior–posterior and medial–lateral axis, and that the TCS-based grading of optimal vs suboptimal lead location predicts the clinical 12 months outcome of patients with movement disorders. Currently, an international multi-center study is being planned to further prove the value of TCS in the post-operative monitoring of DBS electrode position. This trial is intended to start in 2012, and is still open for joining. The obvious advantages of TCS will promote its increasing use for the intra- and post-operative monitoring of deep brain implants.

Texture analysis of transcranial sonographic images for Parkinson disease diagnostics

Parkinson disease (PD) diagnostics based on transcranial sonography (TCS) images are quite subjective and dependent on competence of physician due to low quality of acquired images. The aim of this study is to evaluate potentiality of textural analysis of TCS images for separation between images obtained from healthy and PD affected people. Closer to scanning probe half of midbrain was manually selected as region of interest (ROI) for texture analysis in TCS image. Four hundred thirteen texture features of ROI (110 subjects) were calculated and used for classification during this study. Sequential feature selection method was applied in order to find optimal subset of features for such classification task. Linear support vector machine (SVM) classifier was used for determination of the optimal number of features for new subset. The classification rate 78.18% was obtained using the calculated texture features. It was concluded that discrimination power of these texture features is directly dependent on the image quality.http://dx.doi.org/10.5755/j01.u.66.3.656

GBA-associated PD presents with nonmotor characteristics

To evaluate whether there exists distinct characteristics in glucocerebrosidase (GBA)-associated Parkinson disease (PD) with regard to motor and nonmotor symptoms as well as imaging characteristics assessed by transcranial sonography (TCS). Twenty patients with PD with heterozygous GBA mutations (N370S, L444P) (GBA-PD) in comparison to 20 patients with sporadic PD negative for GBA mutations (sPD) were included. We assessed motor impairment with the Unified Parkinson's Disease Rating Scale-III. Nonmotor symptoms were evaluated using the Montreal Cognitive Assessment, Neuropsychiatric Inventory, revised form of the Beck Depression Inventory, Parkinson Disease Sleep Scale, Sniffin' Sticks, and Unified Multiple System Atrophy Rating Scale items 9-12. TCS imaging was used to detect morphologic characteristics. Patients with GBA-PD more often had a variety of nonmotor symptoms, namely dementia, neuropsychiatric disturbances, and autonomic dysfunction, and had more severe cases, than patients with sPD. They also demonstrated a higher prevalence of a reduced echogenicity of the brainstem raphe assessed by TCS. Especially nonmotor symptoms seem to be very common in GBA-PD. Further studies are needed to validate these observations in order to better understand the pathogenesis of GBA-PD and develop specific therapeutic concepts.

Transcranial Sonography Reveals Cerebellar, Nigral, and Forebrain Abnormalities in Friedreich’s Ataxia

Background: Friedreich’s ataxia (FA) is essentially characterized by degeneration of the dorsal root ganglia, the dorsal nuclei of Clarke, and the long spinal fiber tracts, yet there is accumulating evidence that neurodegeneration extends beyond these predilection sites. Transcranial sonography (TCS) has evolved as a valuable complementary neuroimaging tool in the assessment of neurodegenerative diseases due to its capacity to well depict structural changes and the accumulation of heavy metals. Its use for assessing cerebellar neurodegeneration, however, has not yet been investigated.Here we investigated whether TCS allows to assess particular features of cerebellar as well as midbrain and forebrain abnormalities in FA. Methods: Comprehensive TCS imaging of 34 FA patients and 34 age-matched healthy controls. Results: Hyperechogenicity of the dentate nucleus was very frequent in FA patients (85%) and could even be observed in patients with short disease duration, suggesting that dentate alterations are a common and probably early feature of FA. Substantia nigra was significantly hypoechogenic, possibly indicating regional changes in subcellular brain iron regulation. FA patients showed significantly enlarged 4th, 3rd, and lateral ventricles, thus corroborating earlier MRI and postmortem findings of substantial cerebellar and forebrain atrophy in FA. Conclusions: TCS provides a quick-to-apply and inexpensive in vivo assessment of both cerebellar and noncerebellar abnormalities in FA, in particular highlighting dentate hyperechogenicity as a core feature. It might serve as a promising tool for imaging aspects of cerebellar neurodegeneration also in other neurodegenerative disorders.

Contemporary ultrasound systems allow high-resolution transcranial imaging of small echogenic deep intracranial structures similarly as MRI: A phantom study

Transcranial sonography (TCS) of small deep brain structures, such as substantia nigra and brainstem raphe, is increasingly used for assessment of neurodegenerative disorders. Still, there are reservations against TCS because of the smallness of evaluated structures and constraints on image resolution that is discussed to be lower compared to magnetic resonance imaging (MRI). To evaluate two different-generation TCS systems in visualizing fine intracranial structures, we studied image resolution on a phantom consisting of 0.80 mm×1.05 mm regular meshwork of nylon threads embedded in a wet, gel-filled ex vivo human skull. Imaging was performed with a former-generation and a present-day clinical ultrasound system and for comparison with MRI. In axial direction of insonation both TCS systems resolved 0.80-mm and 1.05-mm thread-to-thread distance at depths between 55 and 120 mm using transmission frequencies ≥2.5 MHz. The meshwork, however, was recognizable as such only with the contemporary TCS system at depths between 60 and 85 mm due to its higher lateral resolution. MRI resolved the meshwork if image resolution was chosen sufficiently high but not if realistic clinical conditions were applied with its trade-offs between image SNR, resolution, total scan time, and unavoidable head motion during the latter. Hence, if the requirements for optimal TCS image resolution are fulfilled, i.e. sufficient acoustic bone window, increased echogenicity of target structure and its localization in a distance of maximum ±15 mm from midsagittal plane, findings suggest that contemporary TCS systems achieve higher image resolution of intracranial structures in comparison not only to former-generation systems, but also to MRI under clinical conditions.

Depression in Parkinson's disease: brainstem midline alteration on transcranial sonography and magnetic resonance imaging.

Recent studies using transcranial sonography (TCS) have provided evidence of alterations in the mesencephalic midline structures in patients with unipolar depression and depression in Parkinson's disease (PD), suggesting an involvement of the basal limbic system in primary and secondary mood disorders. This study tested the hypothesis of brainstem midline abnormality in depression and investigated 31 PD patients by magnetic resonance imaging (MRI) and TCS. Signal intensity of the pontine and mesencephalic brainstem midline was rated on T2-weighted images and measured by relaxometry. In addition, two blinded investigators assessed the echogenicity of the brainstem midline by TCS. The severity of motor symptoms and depression were graded independently using standard research scales. Rating of signal intensity and T2 relaxometry of the pontomesencephalic midline structures revealed significant difference between depressed and nondepressed PD patients (P < 0.05). This corresponded to a significant reduction in mesencephalic midline echogenicity of depressed PD patients on TCS images. No correlation was found between raphe signal intensity, T2 relaxation times, or TCS echogenicity and the severity of motor symptoms or depression. This study is the first to show changes in signal intensity and T2 relaxation time of the pontomesencephalic midline structures on MRI in depressed PD patients confirming previous TCS findings. As these midline structures comprise fiber tracts and nuclei of the basal limbic system, the findings may support the hypothesis of an alteration in the basal limbic system in mood disorders.