Tia LaMore

University of California, San Francisco

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Lea T. Grinberg

University of California, San Francisco

Yuheng Chen

Hong Kong University of Science and Technology

Song Hua Li

University of California, San Francisco

Yonggang Shi

Beijing Normal University

Wing Hung Lee

University of California, San Francisco

Helmut Heinsen

University of Würzburg

Maria Concepción Gracía Otaduy

Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo

Luzia Lima Carreira

Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo

Shuo Huang

Zhejiang Chinese Medical University

Caroline Lew

University Memory and Aging Center

Cooperative Institutions

University of California, San Francisco

University Memory and Aging Center

Center for Neurosciences

Universidade de São Paulo

Alzheimer’s Disease Neuroimaging Initiative

Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo

Global Brain Health Institute

University of California, Berkeley

Trinity College Dublin

San Francisco VA Medical Center

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Validation of locus coeruleus histological reconstructions to MRI

Alzheimer s & Dementia (2021)

Tia LaMore Yuheng Chen Song Li Duygu Tonsun Maria Concepción García Otaduy

Abstract Background The Locus coeruleus(LC) is one of the first sites of tau aggregation and suffers from dramatic volume loss early on. Due to the shrinking of the LC preceding the onset of clinical symptoms of AD by decades, a precise understanding of the neurobiological correlates of MRI signal may turn LC neuroimaging into an early non‐invasive staging biomarker for AD. Though there are many efforts to image the LC in‐vivo, first, it is vital to confirm postmortem validation of the MRI signal. In this study, we are attempting to validate postmortem histological reconstructions of the LC to its corresponding postmortem MRI reconstructions, voxel‐to‐voxel. Method We used a pipeline developed in‐house employing brainstem processing, staining, and computer‐based algorithms for 2D and 3D registration to reconstruct the histological volume of the brainstem with structural detail. This pipeline allows for precise alignment of histology‐based cytoarchitectural 3Dreconstructions (Fig. 1A) of the brainstem to its 7T‐MRI counterpart (Fig. 1B). Photoshop and Freeview were used to manually segment the LC in digital images of cross sections of the brainstem labeled with Nissl staining (Fig. 2), to generate 2D LC masks in all 4 cases. We then registered the stained cross sections and their corresponding LC masks to the cross sections’ blockface to correct for any deformation of tissue during the staining process. We applied Freeview commands to reconstruct the 3D brainstems and their 3D LC masks. We registered the resulting 3D reconstruction and LC mask to matching MRI coordinates, enabling voxel‐to‐voxel comparisons. We will continue to demonstrate the value of our pipeline in regards to validating neuroimaging methods in AD with these structural masks of the postmortem LC registered to the MRI counterpart in 3 more cases. Result The histological 3D LC masks were registered onto the parallel 3D MRIs. In Freeview, we plan to run correlation analysis with an output of dice coefficient ranging from 0‐1, with a coefficient of 1 translating to the voxels of the LC masks and the MRI signal overlapping exactly. Conclusion Our pipeline enables voxel‐to‐voxel correlation analysis between histology and MRI scans for validation of LC neuroimaging. Current finalization of 3 other cases is ongoing.

Locus coeruleus

Nissl body

Voxel-based morphometry

10.1002/alz.055774

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Validation of high resolution subcortical MRI signal using voxel to voxel histology to neuroimaging correlation in AD continuum: advancing neuroimaging biomarker tools for early AD staging

Alzheimer s & Dementia (2023)

Tia LaMore Shuo Huang Yuheng Chen Song Hua Li Wing Hung Lee

Abstract Background Studies suggest a decrease in LC volume by 8% each Braak stage, starting at Braak 0‐1, while in normal aging the LC volume remains intact. Thus, LC volumetry is an attractive potential biomarker to monitor AD progression from precognitive stages. However, precise LC volumetry neuroimaging is challenging due to the LC’s small size and location in the brainstem that’s prone to artifacts. To validate the precision/utility of neuroimaging sequences designed for LC volumetry, we developed a pipeline allowing voxel‐to‐voxel histology to neuroimaging comparisons. We tested this pipeline to analyze the neuro‐histological counterpart of an LC volume obtained from manual segmentation from a MRI neuromelanin(NM)sensitive GRE image. Method Whole brain high resolution(0.7mm)3D‐T1 images and 2D‐2mm thick NM‐sensitive axial GRE images of the brainstem were obtained postmortem in situ before brain removal from a single subject using a 7T MRI(Siemens Magnetom). We combined celloidin‐based histological processing and 3D reconstructions of the histology volume at microscopic resolution which was then aligned to T1. We used structures visible in structural MRI(T1)(brainstem surface, red nucleus, and 4th ventricle) to calculate Dice coefficient to measure registration accuracy. Next, we performed an overlap percentage analysis to investigate how well GRE sequence detected LC borders compared to histology. Result We ran Dice coefficient analysis for brainstem structures to measure histology to MRI registration accuracy(Table1). The LC GRE to histology masks overlap percentage was 35.29% and 10.77% compared to the MRI and histology mask total voxels(voxel size = 0.34mm3). The overlap percentage obtained for the rostral and middle LC thirds ranged from 9.43% to 75%when compared to total voxels in MRI/histology masks, while the caudal third had zero overlap(Table2,Fig.1). Conclusion Our pipeline enables voxel‐to‐voxel correlation analysis between histology and high resolution LC MRIs for neuroimaging validation. The caudal third of the LC in our case has shown a clear lack of overlap potentially due to lack of signal specificity in MRI when compared to the gold standard that is histology. Current analysis of another five other cases is ongoing. Validation of LC MRI signal will inform interpretations of signal results in living patients with the potential to act as a diagnostic tool for ADRD.

Histology

10.1002/alz.080106

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Locus Coeruleus Neuroimaging compared Voxel by Voxel to Histology‐ a postmortem human validation study

Alzheimer s & Dementia (2024)

Tia LaMore Shuo Huang Pedro Burlacchini S. Marinho Yuheng Chen Song Hua Li

Abstract Background Neuropathological studies indicate that locus coeruleus(LC) volume decreases in Alzheimer’s disease(AD) by 8% at each stage, (from Braak 0‐1), whereas in normal aging, the LC remains unchanged. These changes make LC volumetry by neuroimaging a promising way to track AD progression even before symptoms appear. However, LC’s small size and location make it prone to imaging artifacts. To assess the accuracy of neuroimaging sequences designed for LC volumetry, we used an in‐house histological computational method to compare histology and neuroimaging on a voxel‐by‐voxel basis. Method We investigated three cases (two Braak 1s, and a Braak 5). The whole brain underwent 7T MRI postmortem, pre‐autopsy, at the University of Sao Paulo. Upon autopsy, the brains were processed at UCSF and the histological LC was 3D reconstructed. In parallel, the GRE and TFL MRI sequence LCs were segmented (Figure 1). We applied affine& spline registration to match histology to MRI‐T1 volumes (voxel size=0.75mm)(Figure 1). To measure registration accuracy, we calculated DICE coefficients using T1 visible structures (Figure 2). Next, we analyzed the percentage overlap of voxels to investigate how accurately MRI sequences detected histology LC borders. Result Overall, the DICE values for brainstem registration are high. Table 1 shows the overlapping percentages that are quite low, from 2.5%‐23%. For our Braak 1 cases, the least overlap of GRE MRI and histology LC borders is in rostral region, while in both TFL and GRE sequence for the Braak 5 case, the least LC overlap was in the caudal region (Table 1). Conclusion These results suggest that accurately detecting LC borders using MRI remains a challenging task due to small size, imaging artifacts, and neuromelanin dependency, which is low at baseline in caudal LC. However, our overlap results did match previous findings on specific regional LC volume loss seen rostrally in early AD, despite no neuronal loss, and in later stages of AD, volume loss caudally. This points to the MRI LC signal being potentially clinically useful for disease monitoring. Our study will continue to examine the MRI signal picked up in the LC across Braak as regions of LC degeneration shift compared to the histology counterpart.

Locus coeruleus

Voxel-based morphometry

Human brain

10.1002/alz.092115

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Locus Coeruleus Neuroimaging compared Voxel by Voxel to Histology‐ a postmortem human validation study

Alzheimer s & Dementia (2024)

Tia LaMore Shuo Huang Pedro Burlacchini S. Marinho Yuheng Chen Song Hua Li

Abstract Background Neuropathological studies indicate that locus coeruleus(LC) volume decreases in Alzheimer’s disease(AD) by 8% at each stage, (from Braak 0‐1), whereas in normal aging, the LC remains unchanged. These changes make LC volumetry by neuroimaging a promising way to track AD progression even before symptoms appear. However, LC’s small size and location make it prone to imaging artifacts. To assess the accuracy of neuroimaging sequences designed for LC volumetry, we used an in‐house histological computational method to compare histology and neuroimaging on a voxel‐by‐voxel basis. Method We investigated three cases (two Braak 1s, and a Braak 5). The whole brain underwent 7T MRI postmortem, pre‐autopsy, at the University of Sao Paulo. Upon autopsy, the brains were processed at UCSF and the histological LC was 3D reconstructed. In parallel, the GRE and TFL MRI sequence LCs were segmented (Fig 1). We applied affine& spline registration to match histology to MRI‐T1 volumes(voxel size = 0.75mm)(Fig 1). To measure registration accuracy, we calculated DICE coefficients using T1 visible structures (Fig 2). Next, we analyzed the percentage overlap of voxels to investigate how accurately MRI sequences detected histology LC borders. Result Overall, the DICE values for brainstem registration are high. Table 1 shows the overlapping percentages that are quite low, from 2.5%‐23%. For our Braak 1 cases, the least overlap of GRE MRI and histology LC borders is in rostral region, while in both TFL and GRE sequence for the Braak 5 case, the least LC overlap was in the caudal region (Table 1). Conclusion These results suggest that accurately detecting LC borders using MRI remains a challenging task due to small size, imaging artifacts, and neuromelanin dependency, which is low at baseline in caudal LC. However, our overlap results did match previous findings on specific regional LC volume loss seen rostrally in early AD, despite no neuronal loss, and in later stages of AD, volume loss caudally. This points to the MRI LC signal being potentially clinically useful for disease monitoring. Our study will continue to examine the MRI signal picked up in the LC across Braak as regions of LC degeneration shift compared to the histology counterpart.

Histology

Voxel-based morphometry

10.1002/alz.094027

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Subcortical Neuronal Correlates of Sleep in Neurodegenerative Diseases

JAMA Neurology (2022)

Jun Yeop Oh Christine M. Walsh Kamalini G. Ranasinghe Mihovil Mladinov Felipe Luiz Pereira

Sleep disturbance is common among patients with neurodegenerative diseases. Examining the subcortical neuronal correlates of sleep disturbances is important to understanding the early-stage sleep neurodegenerative phenomena.

Sleep

10.1001/jamaneurol.2022.0429

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Voxel to voxel validation of brainstem MRI novel sequences to postmortem tissue reconstruction

Alzheimer s & Dementia (2022)

Tia LaMore Yuheng Chen Maria Concepción García Otaduy Song Hua Li Wing Hung Lee

Abstract Background Neuroimaging of brainstem structures has gained importance in ADRD as these regions degenerate early in AD. In recent years there has been an explosion of novel neuroimaging sequences to image the brainstem. However, most of these methods lack validation against the ground truth, i.e tissue visualization, making these methods less attractive for clinical use. Among the new proposed methods, high‐definition connectome promises to revolutionize BS imaging as it overcomes several limitations of standard structural MRI, including a high level of imaging deformation. In this project we have developed a pipeline to validate BS connectome sequences using a voxel to voxel comparison between 3D histological volumes and connectome signal. To this date we applied this pipeline to 6 human brains. Method We used 6 AD cases collected by the Neuroradiology Lab at the University of Sao Paulo. Patients underwent postmortem MRI prior to autopsy.We used a pipeline developed in‐house that allows for precise alignment of histology‐based cytoarchitectural 3D reconstructions of the brainstem to its T2 weighted 7T‐MRI counterpart. Upon procurement, the brains were fixed in formalin, embedded in celloidin, and cut in horizontal sections of 300um. Selected BS structures were delineated on these slides stained for Nissl(gallocyanin)(Fig.1). Delineated images underwent manual quality checks, a series of alignment and registration processes to recover original coordinates. The stained sections and corresponding ROI masks were registered to the blockface to correct for any deformation of tissue during the staining process. Freeview commands applied to reconstruct the brainstems and masks. We registered the resulting 3D reconstruction to the matching MRI coordinates(Fig. 2), enabling voxel‐to‐voxel comparisons. Result 6 cases went through the pipeline with ROIs reconstructed on block reconstructions(Fig. 3). Currently, dice coefficient analysis between MRI signal and the manually outlined ROIs on histology are being finalized. Conclusion Our pipeline enables voxel‐to‐voxel correlation analysis between histology and MRI scans for validation of brainstem neuroimaging. Current finalization of a total 9 cases is ongoing. Validation of such correlation maps will inform interpretations of connectome results in living patients with the potential to act as an eventual diagnostic tool for ADRD.

10.1002/alz.068233

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Neuronal correlates of sleep in neurodegenerative diseases

Alzheimer s & Dementia (2021)

Jun Yeop Oh Christine M. Walsh Mihovil Mladinov Cathrine Petersen Felipe Pereira

Sleep plays a key role in the origination and progression of neurodegenerative diseases. We have recently shown that the key areas that regulate sleep and wakefulness in the subcortical nuclei are particularly vulnerable to tau-inclusion and neuronal loss even in the early stages in AD. Nevertheless, it remains uncertain whether the pathological lesion of specific nuclei directly contributes to the patient's clinical sleep impairment. Here, we correlate quantitative sleep measurements with post-mortem stereological neuronal analysis in neurodegenerative diseases.Twenty-two patients (50% female; mean age: 70.65 ± 1.54) completed overnight polysomnography and/or MEG at the Memory and Aging Center at UCSF. Of 22 patients, 12 were neuropathologically diagnosed with AD, and 10 were PSP (progressive supranuclear palsy)(Table 1). Locus coeruleus (LC), lateral hypothalamus (LHA), and tuberomammillary nuclei (TMN) were immunostained for their respective primary neurotransmitter (TH, orexin, or histamine) and tau inclusions, followed by stereological neuronal count and Spearman correlation analysis.The number of orexinergic and histaminergic neurons showed a significant correlation with the objective sleep measurements, including total sleep time (TST), wake-after sleep onset (WASO), sleep maintenance, NREM2 sleep, and REM sleep (Figure 1).Loss of neurons involved in the sleep-wake network may play a direct role in impairing sleep architecture and function in neurodegenerative disease. This is the first study to use a quantitative, systematic approach to correlate pathological lesions and sleep parameters in AD and PSP. Understanding the neuronal basis of sleep impairment in neurodegenerative diseases is crucial in designing the next generation of sleep medications and even slowing down the progress of neurodegenerative diseases through early inventions.

Tauopathy

Sleep

Locus coeruleus

10.1002/alz.057450

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