Article
Radiology, Nuclear Medicine & Medical Imaging
Hugh G. Pemberton, Olivia Goodkin, Ferran Prados, Ravi K. Das, Sjoerd B. Vos, James Moggridge, William Coath, Elizabeth Gordon, Ryan Barrett, Anne Schmitt, Hefina Whiteley-Jones, Christian Burd, Mike P. Wattjes, Sven Haller, Meike W. Vernooij, Lorna Harper, Nick C. Fox, Ross W. Paterson, Jonathan M. Schott, Sotirios Bisdas, Mark White, Sebastien Ourselin, John S. Thornton, Tarek A. Yousry, M. Jorge Cardoso, Frederik Barkhof
Summary: The study found that providing a quantitative report of regional brain volumes can significantly improve sensitivity for detecting volume loss and AD across all raters, with the consultant group showing the most improvement in accuracy. Agreement with the 'gold standard' was not significantly affected by the QReport overall, but the consultant group did show a significant improvement. In conclusion, referencing single-subject results to normative data alongside visual assessment can improve sensitivity, accuracy, and interrater agreement for detecting volume loss.
EUROPEAN RADIOLOGY
(2021)
Review
Radiology, Nuclear Medicine & Medical Imaging
Yi-En Quek, Yi Leng Fung, Mike W-L Cheung, Simon J. Vogrin, Steven J. Collins, Stephen C. Bowden
Summary: The study compared automated methods and manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD. The results showed that automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, but with substantial uncontrolled variance. Therefore, caution should be used when utilizing automated methods in measuring these regions in AD patients.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Qiang Zheng, Yiyu Zhang, Honglun Li, Xiangrong Tong, Minhui Ouyang
Summary: This study investigates how different hippocampal segmentation methods affect the accuracy of hippocampal radiomic features (HRFs) in Alzheimer's disease (AD) analysis. The results show that HRFs exhibit high consistency across different segmentation methods and the best performance in AD classification is obtained when HRFs are extracted using the naive majority voting method with a more sufficient segmentation and relatively low hippocampal segmentation accuracy.
EUROPEAN RADIOLOGY
(2022)
Article
Neurosciences
Ahmad Sibahi, Rushali Gandhi, Rami Al-Haddad, Joseph Therriault, Tharick Pascoal, Mira Chamoun, Krysta Boutin-Miller, Christine Tardif, Pedro Rosa-Neto, Clifford M. Cassidy
Summary: Researchers have developed an automated method to accurately segment the locus coeruleus (LC) and overcome limitations of manual segmentation. The method shows high agreement with manual segmentation and captures LC degeneration in Alzheimer's disease (AD).
HUMAN BRAIN MAPPING
(2023)
Article
Medicine, General & Internal
Andrea Sturchio, Alok K. Dwivedi, Christina B. Young, Tarja Malm, Luca Marsili, Jennifer S. Sharma, Abhimanyu Mahajan, Emily J. Hill, Samir El Andaloussi, Kathleen L. Poston, Fredric P. Manfredsson, Lon S. Schneider, Kariem Ezzat, Alberto J. Espay
Summary: The study found that high soluble Aβ42 levels are associated with normal cognition and hippocampal volume despite increasing brain amyloidosis, suggesting that preserving high soluble Aβ42 levels could be important for maintaining cognitive function and hippocampal health.
Article
Biochemistry & Molecular Biology
Stephanie Mangesius, Lukas Haider, Lukas Lenhart, Ruth Steiger, Ferran Prados Carrasco, Christoph Scherfler, Elke R. Gizewski
Summary: Brain volumetric software is widely used in clinical practice, but the agreement across different software applications is limited. This study found moderate to low agreement among different applications in categorizing hippocampal volumes. Despite the quantitative differences, the volumetric measures derived from different software still differed significantly from the mean value.
Article
Biology
Jordan DeKraker, Roy A. M. Haast, Mohamed D. Yousif, Bradley Karat, Jonathan C. Lau, Stefan Kohler, Ali R. Khan
Summary: The article introduces an automated and robust BIDS-App tool called HippUnfold, which can be used to define and index individual-specific hippocampal folding in MRI for more detailed neuroimaging analysis.
Article
Neurosciences
Satya V. V. N. Kothapalli, Tammie L. Benzinger, Andrew J. Aschenbrenner, Richard J. Perrin, Charles F. Hildebolt, Manu S. Goyal, Anne M. Fagan, Marcus E. Raichle, John C. Morris, Dmitriy A. Yablonskiy
Summary: This study utilizes qGRE MRI technique to evaluate neuronal loss in the human hippocampus. The results show that neuronal loss exceeds tissue atrophy in mild AD patients, providing new biomarkers for early AD diagnosis.
JOURNAL OF ALZHEIMERS DISEASE
(2022)
Article
Neurosciences
Jonas Alexander Jarholm, Atle Bjornerud, Turi Olene Dalaker, Mehdi Sadat Akhavi, Bjorn Eivind Kirsebom, Lene Palhaugen, Kaja Nordengen, Goril Rolfseng Grontvedt, Arne Nakling, Lisa F. Kalheim, Ina S. Almdahl, Sandra Tecelao, Tormod Fladby, Per Selnes
Summary: This study examined the clinical utility of automated volumetry in a well-defined and biomarker-classified longitudinal predementia cohort. The results showed that individuals with positive A/T/N classification had smaller entorhinal cortex and hippocampus compared to those with negative classification. Longitudinally, participants with SCD A+ and MCI A+ had greater hippocampal atrophy compared to controls, and this atrophy was also observed in A+/T-/N- and A+/T+orN+ individuals.
JOURNAL OF ALZHEIMERS DISEASE
(2023)
Article
Neurosciences
Nandakumar Nagaraja, Wei-en Wang, Ranjan Duara, Steven T. DeKosky, David Vaillancourt
Summary: This study aimed to evaluate whether cerebral amyloid angiopathy (CAA) pathology mediates hippocampal atrophy in Alzheimer's disease (AD) patients. The results showed that severe CAA was associated with smaller left hippocampal volume on T1-MRI in patients with neuropathologically confirmed AD, and this relationship was dependent on APOE ε4 genotype.
JOURNAL OF ALZHEIMERS DISEASE
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Robert J. Holtackers, Joachim E. Wildberger, Bernd J. Wintersperger, Amedeo Chiribiri
Summary: Cardiac magnetic resonance imaging (MRI) is commonly used for noninvasive assessment of cardiac structure and function, with 1.5 T traditionally being the preferred field strength. While 3 T systems have seen significant growth in the past decade, there are still challenges hindering their widespread clinical use for cardiac applications. Different clinical benefits exist for each field strength and there is no universal recommendation for the ideal field strength for cardiac MRI. The review discusses the physical differences between 1.5 and 3 T, their impact on various cardiac MRI applications, and provides solutions to overcome potential limitations.
INVESTIGATIVE RADIOLOGY
(2021)
Article
Biochemical Research Methods
Jie Lu, Yuxuan Cheng, Jianqing LI, Ziyu Liu, Mengxi Shen, Qinqin Zhang, Jeremy Liu, Gissel Herrera, Farhan E. Hiya, Rosalyn Morin, Joan Joseph, Giovanni Gregori, Philip J. Rosenfeld, Ruikang K. Wang, Philip J. Rosenfeld, Ruikang K. Wang
Summary: This paper presents the development of an automated algorithm for segmenting and quantifying calcified drusen on SS-OCT images. The algorithm utilizes the higher scattering property of calcified drusen and combines the optical attenuation coefficient (OAC) within drusen and the choroidal hypotransmission defects (hypoTDs) under drusen to achieve accurate segmentation. The study demonstrates good agreement between the automated method and human expert graders in identifying the area of calcified drusen.
BIOMEDICAL OPTICS EXPRESS
(2023)
Article
Clinical Neurology
Nacim Betrouni, Jiyang Jiang, Marco Duering, Marios K. Georgakis, Lena Oestreich, Perminder S. Sachdev, Michael O'Sullivan, Paul Wright, Jessica W. Lo, Regis Bordet
Summary: This study examined the reliability of texture features against imaging settings using data from different centers and found that texture features obtained from routine clinical MR images are robust early predictors of poststroke cognitive impairment and can be combined with other demographic and clinical predictors to build an accurate prediction model.
Article
Engineering, Electrical & Electronic
Mamta Juneja, Sumindar Kaur Saini, Rajarshi Acharjee, Sambhav Kaul, Niharika Thakur, Prashant Jindal
Summary: This article proposes a deep learning-based methodology called prostate cancer segmentation network (PC-SNet) for accurate segmentation of the region of interest from MRI sub-modalities. By analyzing the performance using various parameters, PC-SNet is found to outperform other conventional methods and network architectures.
INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Christian Rubbert, Luisa Wolf, Bernd Turowski, Dennis M. Hedderich, Christian Gaser, Robert Dahnke, Julian Caspers
Summary: This study evaluated the impact of different defacing procedures on automated brain atrophy estimation, and found that most defacing methods have an impact on atrophy estimation, especially in accelerated 3D T1 imaging. Only PyDeface performed well with negligible impact on atrophy estimation.
INSIGHTS INTO IMAGING
(2022)
Article
Clinical Neurology
Jonathan Voeglein, Nicolai Franzmeier, John C. Morris, Marianne Dieterich, Eric McDade, Mikael Simons, Oliver Preische, Anna Hofmann, Jason Hassenstab, Tammie L. Benzinger, Anne Fagan, James M. Noble, Sarah B. Berman, Neill R. Graff-Radford, Bernardino Ghetti, Martin R. Farlow, Jasmeer P. Chhatwal, Stephen Salloway, Chengjie Xiong, Celeste M. Karch, Nigel Cairns, Richard J. Perrin, Gregory Day, Ralph Martins, Raquel Sanchez-Valle, Hiroshi Mori, Hiroyuki Shimada, Takeshi Ikeuchi, Kazushi Suzuki, Peter R. Schofield, Colin L. Masters, Alison Goate, Virginia Buckles, Nick C. Fox, Patricio Chrem, Ricardo Allegri, John M. Ringman, Igor Yakushev, Christoph Laske, Mathias Jucker, Gunter Hoglinger, Randall J. Bateman, Adrian Danek, Johannes Levin
Summary: Autosomal dominant Alzheimer's disease (ADAD) has distinct neurological examination findings that are useful for estimating prognosis and guiding clinical care and therapeutic trial designs.
ALZHEIMERS & DEMENTIA
(2023)
Article
Clinical Neurology
Patrick H. Luckett, Charlie Chen, Brian A. Gordon, Julie Wisch, Sarah B. Berman, Jasmeer P. Chhatwal, Carlos Cruchaga, Anne M. Fagan, Martin R. Farlow, Nick C. Fox, Mathias Jucker, Johannes Levin, Colin L. Masters, Hiroshi Mori, James M. Noble, Stephen Salloway, Peter R. Schofield, Adam M. Brickman, William S. Brooks, David M. Cash, Michael J. Fulham, Bernardino Ghetti, Clifford R. Jack, Jonathan Voeglein, William E. Klunk, Robert Koeppe, Yi Su, Michael Weiner, Qing Wang, Daniel Marcus, Deborah Koudelis, Nelly Joseph-Mathurin, Lisa Cash, Russ Hornbeck, Chengjie Xiong, Richard J. Perrin, Celeste M. Karch, Jason Hassenstab, Eric McDade, John C. Morris, Tammie L. S. Benzinger, Randall J. Bateman, Beau M. Ances
Summary: This study analyzed 19 biomarkers of Alzheimer's disease using hierarchical clustering and feature selection, and found that amyloid and tau measures were the primary predictors. Emerging biomarkers of neuronal integrity and inflammation showed weaker predictive ability.
ALZHEIMERS & DEMENTIA
(2023)
Article
Acoustics
L. Joyeux, J. van der Merwe, M. Aertsen, P. A. Patel, A. Khatoun, M. G. M. C. Mori da Cunha, S. De Vleeschauwer, J. Parra, E. Danzer, M. McLaughlin, D. Stoyanov, T. Vercauteren, S. Ourselin, E. Radaelli, P. de Coppi, F. Van Calenbergh, J. Deprest
Summary: This study aimed to investigate the neurostructural and neurofunctional efficacy of watertight prenatal spina bifida aperta (SBA) repair in a fetal lamb model. The results showed that lambs with watertight repair achieved better neuroprotection and improved brain and spinal cord structure and function compared to lambs without repair. This research has important clinical implications for improving neuroprotection in fetal centers.
ULTRASOUND IN OBSTETRICS & GYNECOLOGY
(2023)
Letter
Clinical Neurology
Antoinette O'Connor, Emily Abel, Andrea Lessa Benedet, Teresa Poole, Nicholas Ashton, Philip Simon John Weston, Amanda J. Heslegrave, Natalie Ryan, Suzie Barker, James M. Polke, Kaj Blennow, Henrik Zetterberg, Nick C. Fox
JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY
(2023)
Letter
Clinical Neurology
Antoinette O'Connor, Helen Rice, Josephine Barnes, Natalie S. Ryan, Kathy Y. Liu, Ricardo Francisco Allegri, Sarah Berman, John M. Ringman, Carlos Cruchaga, Martin R. Farlow, Jason Hassenstab, Jae-Hong Lee, Richard J. Perrin, Chengjie Xiong, Brian Gordon, Allan Levey, Alison Goate, Neil Graff-Radford, Johannes Levin, Mathias Jucker, Tammie Benzinger, Eric McDade, Hiroshi Mori, James M. Noble, Peter R. Schofield, Ralph N. Martins, Stephen Salloway, Jasmeer Chhatwal, John C. Morris, Randall Bateman, Rob Howard, Suzanne Reeves, Nick C. Fox
JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY
(2023)
Article
Biology
Peter R. Millar, Brian A. Gordon, Patrick H. Luckett, Tammie L. S. Benzinger, Carlos Cruchaga, Anne M. Fagan, Jason J. Hassenstab, Richard J. Perrin, Suzanne E. Schindler, Ricardo F. Allegri, Gregory S. Day, Martin R. Farlow, Hiroshi Mori, Georg Nuebling, Randall J. Bateman, John C. Morris, Beau M. Ances
Summary: Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored.
Article
Engineering, Biomedical
Charlie Budd, Luis C. Garcia-Peraza C. Herrera, Martin Huber, Sebastien Ourselin, Tom Vercauteren
Summary: This paper addresses the estimation problem of endoscopic content area and proposes two algorithms based on edge detection and circle fitting. A dataset of manually annotated and pseudo-labelled content areas is provided for research. The proposed algorithm shows significant improvement in both accuracy and computational time compared to state-of-the-art methods.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
(2023)
Article
Engineering, Biomedical
Luis C. Garcia Peraza C. Herrera, Conor Horgan, Sebastien Ourselin, Michael Ebner, Tom Vercauteren
Summary: Traditional RGB imaging poses challenges in visual discrimination of clinical tissue types, while hyperspectral imaging (HSI) provides rich spectral information beyond three-channel RGB imaging. Our study examines the performance of deep learning image segmentation methods when trained on HSI and RGB images, as well as HSI and RGB pixels. Using the Oral and Dental Spectral Image Database (ODSI-DB) with 215 manually segmented dental reflectance spectral images, we emphasize the significance of spectral resolution, range, and spatial information for the development and application of clinical HSI.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
(2023)
Article
Clinical Neurology
Rebecca E. Green, Jodie Lord, Marzia A. Scelsi, Jin Xu, Andrew Wong, Sarah Naomi-James, Alex Handy, Lachlan Gilchrist, Dylan M. Williams, Thomas D. Parker, Christopher A. Lane, Ian B. Malone, David M. Cash, Carole H. Sudre, William Coath, David L. Thomas, Sarah Keuss, Richard Dobson, Cristina Legido-Quigley, Nick C. Fox, Jonathan M. Schott, Marcus Richards, Petroula Proitsi
Summary: By analyzing the associations between blood metabolites and brain volume, hippocampal volume, and amyloid-beta status among the participants of Insight 46, this study identifies key metabolites related to brain health and preclinical pathology, providing insights into early disease mechanisms and potential intervention strategies.
ALZHEIMERS RESEARCH & THERAPY
(2023)
Article
Clinical Neurology
Antoinette O'Connor, David M. Cash, Teresa Poole, Pawel J. Markiewicz, Maggie R. Fraser, Ian B. Malone, Jieqing Jiao, Philip S. J. Weston, Shaney Flores, Russ Hornbeck, Eric McDade, Michael Schoell, Brian A. Gordon, Randall J. Bateman, Tammie L. S. Benzinger, Nick C. Fox
Summary: Cortical tau accumulation is a crucial pathological event in Alzheimer's disease, and understanding the timing and pattern of tau deposition can help track the disease progression. This study used data from participants in AD cohort studies to investigate if tau PET can detect early changes in presymptomatic carriers and found that there were regional differences in tau accumulation prior to symptom onset, particularly in posterior regions.
ALZHEIMERS RESEARCH & THERAPY
(2023)
Article
Clinical Neurology
Sarah-Naomi James, Emily N. Manning, Mathew Storey, Jennifer M. Nicholas, William Coath, Sarah E. Keuss, David M. Cash, Christopher A. Lane, Thomas Parker, Ashvini Keshavan, Sarah M. Buchanan, Aaron Wagen, Mathew Harris, Ian Malone, Kirsty Lu, Louisa P. Needham, Rebecca Street, David Thomas, John Dickson, Heidi Murray-Smith, Andrew Wong, Tamar Freiberger, Sebastian J. Crutch, Nick C. Fox, Marcus Richards, Frederik Barkhof, Carole H. Sudre, Josephine Barnes, Jonathan M. Schott
Summary: This study investigates the associations between normal-appearing white matter microstructural integrity, brain health, cognition, demographics, genetics, and cardiovascular health in cognitively normal adults in their seventies. The results show that measures of brain health, cognition, demographics, genetics, and cardiovascular health are associated with the microstructural integrity of normal-appearing white matter. Additionally, sex, blood pressure, and cardiovascular health in females were found to have an impact on white matter integrity.
BRAIN COMMUNICATIONS
(2023)
Article
Clinical Neurology
William Coath, Marc Modat, M. Jorge J. Cardoso, Pawel J. A. Markiewicz, Christopher A. D. Lane, Thomas D. Parker, Ashvini M. Keshavan, Sarah M. E. Buchanan, Sarah E. J. Keuss, Matthew J. Harris, Ninon Burgos, John Dickson, Anna L. Barnes, David L. Thomas, Daniel B. Beasley, Ian B. Malone, Andrew Wong, Kjell A. Erlandsson, Benjamin A. Thomas, Michael Scholl, Sebastien Ourselin, Marcus C. Richards, Nick C. M. Fox, Jonathan M. M. Schott, David M. Cash
Summary: The Centiloid scale aims to harmonize Aβ PET measures across different analysis methods. This study investigated the Centiloid transformation with PET/MRI data, finding that the transformation is valid but further understanding of the effects of acquisition or biological factors on using white matter as a reference is needed.
ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING
(2023)
Article
Clinical Neurology
Julie K. K. Wisch, Ganesh M. Babulal, Kalen Petersen, Peter R. R. Millar, Enbal Shacham, Stephen Scroggins, Anna H. H. Boerwinkle, Shaney Flores, Sarah Keefe, Brian A. A. Gordon, John C. C. Morris, Beau M. M. Ances
Summary: This article presents a practical guide for applying geospatial methods to a neuroimaging cohort, aiming to evaluate the impact of the environment on the brain. The authors used structural magnetic resonance imaging data from 239 city-dwelling participants in St. Louis, Missouri, and compared them to population-level estimates from the American Community Survey to identify neighborhoods associated with altered brain structure. They observed a relationship between neighborhoods and brain health, suggesting the potential for neighborhood-based interventions.
ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING
(2023)
Article
Computer Science, Interdisciplinary Applications
Jianghao Wu, Guotai Wang, Ran Gu, Tao Lu, Yinan Chen, Wentao Zhu, Tom Vercauteren, Sebastien Ourselin, Shaoting Zhang
Summary: Domain Adaptation is crucial for deep learning models in medical image segmentation to handle testing images from new target domains. Source-Free Domain Adaptation (SFDA) is an appealing approach for efficient adaptation to the target domain without source-domain data. However, existing SFDA methods suffer from limited performance due to lack of sufficient supervision with unavailable source-domain images and unlabeled target-domain images. In this study, we propose a novel Uncertainty-aware Pseudo Label guided SFDA method for medical image segmentation, which improves performance by enhancing diversity in the target domain and using reliable pseudo labels.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)