News | Neuro Imaging | September 27, 2017

Brain Disconnections May Contribute to Parkinson's Hallucinations

fMRI study finds areas focused on attention and visual processing more disconnected from the rest of the brain in Parkinson’s patients

Brain Disconnections May Contribute to Parkinson's Hallucinations

September 27, 2017 — Researchers have found that disconnections of brain areas involved in attention and visual processing may contribute to visual hallucinations in individuals with Parkinson’s disease, according to a new study published online in the journal Radiology. The disconnected brain areas seen on functional magnetic resonance imaging (fMRI) may be valuable in predicting the development of visual hallucinations in patients with Parkinson’s disease. 

Hallucinations are sensations that seem real but are created in a person’s mind. A person having a hallucination may see, hear or feel something that is not actually there. According to the National Parkinson Foundation, visual hallucinations can be a complication of Parkinson’s disease.

“Visual hallucinations in Parkinson’s disease are frequent and debilitating,” said study author Dagmar H. Hepp, M.D., from the Department of Neurology and the Department of Anatomy and Neurosciences at VU University Medical Center (VUMC) in Amsterdam, the Netherlands. “Our aim was to study the mechanism underlying visual hallucinations in Parkinson’s disease, as these symptoms are currently poorly understood.”

Studies using fMRI to investigate visual hallucinations in patients with Parkinson’s disease are rare and have been mainly limited to task-based methods using activities that involve visual stimulation or cognitive tasks. However, the authors note that the presence of visual hallucinations is strongly linked to the development of cognitive decline in patients with Parkinson’s disease. Cognitive deficits may influence a patient’s ability to perform specific tasks during an fMRI exam.

For this study, researchers used resting-state fMRI to examine the connectivity, or communication, between brain areas. Resting-state fMRI is a method of brain imaging that can be used to evaluate patients not performing an explicit task. The connectivity was measured in 15 patients with visual hallucinations, 40 patients without visual hallucinations, and 15 healthy controls by calculating the level of synchronization between activation patterns of different brain areas.

The results showed that in all the patients with Parkinson’s disease, multiple brain areas communicated less with the rest of the brain as compared to the control group. However, in patients suffering from visual hallucinations, several additional brain areas showed this decreased connectivity with the rest of the brain, especially those important in maintaining attention and processing of visual information.

“We found that the areas in the brain involved in attention and visual processing were less connected to the rest of the brain,” said study author Menno M. Schoonheim, Ph.D., from the Department of Anatomy and Neurosciences at VUMC. “This suggests that disconnection of these brain areas may contribute to the generation of visual hallucinations in patients with Parkinson’s disease.”

While there are no direct therapeutic implications for patient care based on the research, the authors note that future studies could indicate whether techniques that could stimulate the areas with decreased connectivity could be helpful to treat visual hallucinations in people with Parkinson’s disease.

For more information: www.pubs.rsna.org/journal/radiology

Related Content

United Imaging's uMR OMEGA is designed to provide greater access to magnetic resonance imaging (MRI) with the world’s first ultra-wide 75-cm bore 3T MRI.
News | Magnetic Resonance Imaging (MRI) | May 27, 2020
May 27, 2020 — United Imaging's...
a Schematic of the system. The entire solid tumour is illuminated from four sides by a four-arm fibre bundle. A cylindrically focused linear array is designed to detect optoacoustic signals from the tumour. In vivo imaging is performed in conical scanning geometry by controlling the rotation and translation stages. The sensing part of the transducer array and the tumour are submerged in water to provide acoustic coupling. b Maximum intensity projections of the optoacoustic reconstruction of a phantom of pol

a Schematic of the system. The entire solid tumour is illuminated from four sides by a four-arm fibre bundle. A cylindrically focused linear array is designed to detect optoacoustic signals from the tumour. In vivo imaging is performed in conical scanning geometry by controlling the rotation and translation stages. The sensing part of the transducer array and the tumour are submerged in water to provide acoustic coupling. b Maximum intensity projections of the optoacoustic reconstruction of a phantom of polyethylene microspheres (diameter, 20 μm) dispersed in agar. The inset shows a zoomed-in view of the region boxed with a yellow dashed line. In addition, the yellow boxes are signal profiles along the xy and z axes across the microsphere centre, as well as the corresponding full width at half-maximum values. c Normalized absorption spectra of Hb, HbO2 and gold nanoparticles (AuNPs). The spectrum for the AuNPs was obtained using a USB4000 spectrometer (Ocean Optics, Dunedin, FL, USA), while the spectra for Hb and HbO2 were taken from http://omlc.org/spectra/haemoglobin/index.html. The vertical dashed lines indicate the five wavelengths used to stimulate the three absorbers: 710, 750, 780, 810 and 850 nm. Optoacoustic signals were filtered into a low-frequency band (red) and high-frequency band (green), which were used to reconstruct separate images.

News | Breast Imaging | May 26, 2020
May 26, 2020 — Breast cancer is the most common cancer in women.
A new technique developed by researchers at UC Davis offers a significant advance in using magnetic resonance imaging to pick out even very small tumors from normal tissue. The team created a probe that generates two magnetic resonance signals that suppress each other until they reach the target, at which point they both increase contrast between the tumor and surrounding tissue

A new technique developed by researchers at UC Davis offers a significant advance in using magnetic resonance imaging to pick out even very small tumors from normal tissue. The team created a probe that generates two magnetic resonance signals that suppress each other until they reach the target, at which point they both increase contrast between the tumor and surrounding tissue. Image courtesy of Xiandoing Xue, UC Davis

News | Magnetic Resonance Imaging (MRI) | May 26, 2020
May 26, 2020 — Researchers at the University of California, Davis offers a...
Researchers from Tokyo Metropolitan University have surveyed the amount of gadolinium found in river water in Tokyo. Gadolinium is contained in contrast agents given to patients undergoing medical magnetic resonance imaging (MRI) scans, and it has been shown in labs to become toxic when exposed to ultraviolet rays. The researchers found significantly elevated levels, particularly near water treatment plants, highlighting the need for new public policy and removal technologies as MRI become even more commonp

Samples were taken along rivers around Tokyo. Measurements of rare earth element quantities indicate a clearly elevated amount of gadolinium compared to that in natural shale. Graphics courtesy of Tokyo Metropolitan University

News | Magnetic Resonance Imaging (MRI) | May 26, 2020
May 26, 2020 — Researchers from Tokyo Metropolitan...
Remote reading of imaging studies on home picture archiving and communication systems (PACS) workstations can contribute to social distancing, protect vulnerable radiologists and others in the hospital, and ensure seamless interpretation capabilities in emergency scenarios, according to an open-access article published ahead-of-print by the American Journal of Roentgenology (AJR).

Srini Tridandapani, M.D., Ph.D.

News | PACS | May 21, 2020
May 21, 2020 — 
Examples of chest CT images of COVID-19 (+) patients and visualization of features correlated to COVID-19 positivity. For each pair of images, the left image is a CT image showing the segmented lung used as input for the CNN (convolutional neural network algorithm) model trained on CT images only, and the right image shows the heatmap of pixels that the CNN model classified as having SARS-CoV-2 infection (red indicates higher probability). (a) A 51-year-old female with fever and history of exposure to SARS-

Figure 1: Examples of chest CT images of COVID-19 (+) patients and visualization of features correlated to COVID-19 positivity. For each pair of images, the left image is a CT image showing the segmented lung used as input for the CNN (convolutional neural network algorithm) model trained on CT images only, and the right image shows the heatmap of pixels that the CNN model classified as having SARS-CoV-2 infection (red indicates higher probability). (a) A 51-year-old female with fever and history of exposure to SARS-CoV-2. The CNN model identified abnormal features in the right lower lobe (white color), whereas the two radiologists labeled this CT as negative. (b) A 52-year-old female who had a history of exposure to SARS-CoV-2 and presented with fever and productive cough. Bilateral peripheral ground-glass opacities (arrows) were labeled by the radiologists, and the CNN model predicted positivity based on features in matching areas. (c) A 72-year-old female with exposure history to the animal market in Wuhan presented with fever and productive cough. The segmented CT image shows ground-glass opacity in the anterior aspect of the right lung (arrow), whereas the CNN model labeled this CT as negative. (d) A 59-year-old female with cough and exposure history. The segmented CT image shows no evidence of pneumonia, and the CNN model also labeled this CT as negative.  

News | Coronavirus (COVID-19) | May 19, 2020
May 19, 2020 — Mount Sinai researchers are the first in the country to use...
Advanced imaging data exchange is now live in Colorado due to the partnership of Health Images and the Colorado Regional Health Information Organization

Getty Images

News | Radiology Business | May 18, 2020
May 18, 2020 — 
Now a research team — led by Tohoku University Professor, Wataru Yashiro — has developed a new method using intense synchrotron radiation that produces higher quality images within milliseconds.

How the bent crystal changes the direction of the X-rays. Image courtesy of Tohoku University

News | Computed Tomography (CT) | May 15, 2020
May 15, 2020 — Many will undergo a computed tomogr...
Colored areas of the brain represent regions where the loss of brain synapses in people with early-stage Alzheimer’s was greater than people with normal cognitive function.

Colored areas of the brain represent regions where the loss of brain synapses in people with early-stage Alzheimer’s was greater than people with normal cognitive function. Image courtesy of YaleNews.

News | PET Imaging | May 14, 2020
May 14, 2020 — New imaging technology allows scientists to see the widespread loss of brain synapses in early stages
Experimental Protocol and Representative MRI of Brains at Various Key Points in That Protocol.

Experimental Protocol and Representative MRI of Brains at Various Key Points in That Protocol. (A) Experimental timeline. (B) Representative T2WI (using an 11.7T MRI) of the brain of a postnatal day (PND) 11 pup, 1 day after inducing left HII and prior to hNSC transplantation. Note the beginning of an increasingly intense “water signal” (white) on the left (“HII lesion”). (C) Representative T2WI (using an 11.7T MRI) 3 days post-HII, shortly after implantation of SPIO pre-labeled hNSCs into the contralateral cerebral ventricle (“Lateral Vent”). Note the “HII lesion” on the left becoming hyperintense (white) and the black signal void of the SPIO-labeled hNSCs in the lateral ventricle (black arrow). Red arrows denote the needle track. In contrast to what occurs in the intact brain (Figure S4), in a brain subjected to left HII, the implanted SPIO-labeled hNSCs (black signal void) (black arrow) migrate from the right (“R”) to the left (“L”) hemisphere to enter the lesion. (D and E) Shown here (using a 4.7T MRI) are SPIO-labeled hNSCs (black signal void) (black arrow) at 1 month post-implantation into the contralateral ventricle (D) and, in the same representative animal, at 3 months post-implantation (E)–stably integrated and surrounding a much-reduced residual lesion, with no interval enlargement of the graft or ventricles.

News | Magnetic Resonance Imaging (MRI) | May 13, 2020
May 13, 2020 — Scientists at Sanford Burnham Prebys Medical Discov...