Publications

@article{Oltra2024,

title = {A multi-site study on sex differences in cortical thickness in non-demented Parkinson’s disease},

author = {Javier Oltra and Barbara Segura and Antonio P. Strafella and Thilo van Eimeren and Naroa Ibarretxe-Bilbao and Maria Diez-Cirarda and Carsten Eggers and Olaia Lucas-Jiménez and Gemma C. Monté-Rubio and Natalia Ojeda and Javier Peña and Marina C. Ruppert and Roser Sala-Llonch and Hendrik Theis and Carme Uribe and Carme Junque},

doi = {10.1038/s41531-024-00686-2},

issn = {2373-8057},

year  = {2024},

date = {2024-12-00},

urldate = {2024-12-00},

journal = {npj Parkinsons Dis.},

volume = {10},

number = {1},

publisher = {Springer Science and Business Media LLC},

abstract = {<jats:title>Abstract</jats:title><jats:p>Clinical, cognitive, and atrophy characteristics depending on sex have been previously reported in Parkinson’s disease (PD). However, though sex differences in cortical gray matter measures in early drug naïve patients have been described, little is known about differences in cortical thickness (CTh) as the disease advances. Our multi-site sample comprised 211 non-demented PD patients (64.45% males; mean age 65.58 ± 8.44 years old; mean disease duration 6.42 ± 5.11 years) and 86 healthy controls (50% males; mean age 65.49 ± 9.33 years old) with available T1-weighted 3 T MRI data from four international research centers. Sex differences in regional mean CTh estimations were analyzed using generalized linear models. The relation of CTh in regions showing sex differences with age, disease duration, and age of onset was examined through multiple linear regression. PD males showed thinner cortex than PD females in six frontal (bilateral caudal middle frontal, bilateral superior frontal, left precentral and right pars orbitalis), three parietal (bilateral inferior parietal and left supramarginal), and one limbic region (right posterior cingulate). In PD males, lower CTh values in nine out of ten regions were associated with longer disease duration and older age, whereas in PD females, lower CTh was associated with older age but with longer disease duration only in one region. Overall, male patients show a more widespread pattern of reduced CTh compared with female patients. Disease duration seems more relevant to explain reduced CTh in male patients, suggesting worse prognostic over time. Further studies should explore sex-specific cortical atrophy trajectories using large longitudinal multi-site data.</jats:p>},

keywords = {Cortical thickness, Parkinson, Sex differences, Structural MRI},

pubstate = {published},

tppubtype = {article}

}

@article{Dzialas2024,

title = {Houston, We Have AI Problem! Quality Issues with Neuroimaging‐Based Artificial Intelligence in Parkinson's Disease: A Systematic Review},

author = {Verena Dzialas and Elena Doering and Helena Eich and Antonio P. Strafella and David E. Vaillancourt and Kristina Simonyan and Thilo van Eimeren},

doi = {10.1002/mds.30002},

issn = {1531-8257},

year  = {2024},

date = {2024-12-00},

urldate = {2024-12-00},

journal = {Movement Disorders},

volume = {39},

number = {12},

pages = {2130--2143},

publisher = {Wiley},

abstract = {In recent years, many neuroimaging studies have applied artificial intelligence (AI) to facilitate existing challenges in Parkinson's disease (PD) diagnosis, prognosis, and intervention. The aim of this systematic review was to provide an overview of neuroimaging‐based AI studies and to assess their methodological quality. A PubMed search yielded 810 studies, of which 244 that investigated the utility of neuroimaging‐based AI for PD diagnosis, prognosis, or intervention were included. We systematically categorized studies by outcomes and rated them with respect to five minimal quality criteria (MQC) pertaining to data splitting, data leakage, model complexity, performance reporting, and indication of biological plausibility. We found that the majority of studies aimed to distinguish PD patients from healthy controls (54%) or atypical parkinsonian syndromes (25%), whereas prognostic or interventional studies were sparse. Only 20% of evaluated studies passed all five MQC, with data leakage, non‐minimal model complexity, and reporting of biological plausibility as the primary factors for quality loss. Data leakage was associated with a significant inflation of accuracies. Very few studies employed external test sets (8%), where accuracy was significantly lower, and 19% of studies did not account for data imbalance. Adherence to MQC was low across all observed years and journal impact factors. This review outlines that AI has been applied to a wide variety of research questions pertaining to PD; however, the number of studies failing to pass the MQC is alarming. Therefore, we provide recommendations to enhance the interpretability, generalizability, and clinical utility of future AI applications using neuroimaging in PD. },

keywords = {Artificial Intelligence, DaT imaging, Guidelines, Parkinson, Structural MRI},

pubstate = {published},

tppubtype = {article}

}

@article{Giehl2024b,

title = {Working Memory Training Responsiveness in Parkinson’s Disease Is Not Determined by Cortical Thickness or White Matter Lesions},

author = {Kathrin Giehl and Hendrik Theis and Anja Ophey and Jochen Hammes and Paul Reker and Carsten Eggers and Gereon R. Fink and Elke Kalbe and Thilo van Eimeren},

doi = {10.3233/jpd-230367},

issn = {1877-718X},

year  = {2024},

date = {2024-02-03},

urldate = {2024-02-03},

journal = {Journal of Parkinson’s Disease},

volume = {14},

number = {2},

pages = {347--351},

publisher = {SAGE Publications},

abstract = {<jats:p> Patients with Parkinson’s disease are highly vulnerable for cognitive decline. Thus, early intervention by means of working memory training (WMT) may be effective for the preservation of cognition. However, the influence of structural brain properties, i.e., cortical thickness and volume of white matter lesions on training responsiveness have not been studied. Here, behavioral and neuroimaging data of 46 patients with Parkinson’s disease, 21 of whom engaged in home-based, computerized adaptive WMT, was analyzed. While cortical thickness and white matter lesions volume were associated with cognitive performance at baseline, these structural brain properties do not seem to determine WMT responsiveness. </jats:p>},

keywords = {Memory training, Parkinson, Structural MRI},

pubstate = {published},

tppubtype = {article}

}

@article{Doering2023,

title = {MRI or^{18}F-FDG PET for Brain Age Gap Estimation: Links to Cognition, Pathology, and Alzheimer Disease Progression},

author = {Elena Doering and Georgios Antonopoulos and Merle Hoenig and Thilo van Eimeren and Marcel Daamen and Henning Boecker and Frank Jessen and Emrah Düzel and Simon Eickhoff and Kaustubh Patil and Alexander Drzezga},

doi = {10.2967/jnumed.123.265931},

issn = {2159-662X},

year  = {2024},

date = {2024-01-00},

urldate = {2024-01-00},

journal = {J Nucl Med},

volume = {65},

number = {1},

pages = {147--155},

publisher = {Society of Nuclear Medicine},

keywords = {Artificial Intelligence, Brain age, FDG PET, Structural MRI},

pubstate = {published},

tppubtype = {article}

}

@article{Banwinkler2022b,

title = {Gray Matter Volume Loss in Proposed <scp>Brain‐First</scp> and <scp>Body‐First</scp> Parkinson's Disease Subtypes},

author = {Magdalena Banwinkler and Verena Dzialas and and Merle C. Hoenig and Thilo van Eimeren},

doi = {10.1002/mds.29172},

issn = {1531-8257},

year  = {2022},

date = {2022-10-00},

urldate = {2022-10-00},

journal = {Movement Disorders},

volume = {37},

number = {10},

pages = {2066--2074},

publisher = {Wiley},

abstract = {<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>α‐Synuclein pathology is associated with neuronal degeneration in Parkinson's disease (PD) and considered to sequentially spread across the brain (Braak stages). According to a new hypothesis of distinct α‐synuclein spreading directions based on the initial site of pathology, the “brain‐first” spreading subtype would be associated with a more asymmetric cerebral and nigrostriatal pathology than the “body‐first” subtype.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>Here, we tested if proposed markers of brain‐first PD (ie, higher dopamine transporter [DaT] asymmetry; absence of rapid eye movement sleep behavior disorder [RBD]) are associated with a greater or more asymmetric reduction in gray matter volume (GMV) in comparison to body‐first PD.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Data of 255 de novo PD patients and 110 healthy controls (HCs) were retrieved from the Parkinson's Progression Markers Initiative. Structural magnetic resonance images were preprocessed, and GMVs and their hemispherical asymmetry were obtained for each of the neuropathologically defined Braak stages. Group and correlation comparisons were performed to assess differences in GMV and GMV asymmetry between PD subtypes.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>PD patients demonstrated significantly smaller bilateral GMVs compared to HCs, in a pattern denoting stage‐dependent disease‐related brain atrophy. However, the degree of putaminal DaT asymmetry was not associated with reduced GMV or higher GMV asymmetry. Furthermore, RBD‐negative and RBD‐positive patients did not demonstrate a significant difference in GMV or GMV asymmetry.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>Our findings suggest that putative brain‐first and body‐first patients do not present diverging brain atrophy patterns. Although certainly not disproving the brain‐first/body‐first spreading hypothesis, this study fails to provide evidence in support of it. © 2022 The Authors. <jats:italic>Movement Disorders</jats:italic> published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society</jats:p></jats:sec>},

keywords = {Brain-First Body-First, Parkinson, Structural MRI},

pubstate = {published},

tppubtype = {article}

}