A neuroimaging atlas of the nigrosomes in the substantia nigra based on 3D histology

Put up mortem tissue processing

We used beforehand printed block-face photos and anti-calbindin immunohistochemistry for 3D ultra-high-resolution delineations and gold-standard definitions of nigrosomes and the SN^20,23. Within the following, we summarize the tissue processing, whereas for an in depth description, we discuss with the unique publications^20,23. 4 beforehand described publish mortem specimens (specimens 1, 6, 7, and eight, see Desk 1 in²³) had been histologically processed [(73 ± 10)years old (mean  ± standard deviation), 2 men] (Desk 1). The tissue specimens had been sourced by means of the whole-body donation program on the College of Maastricht, the Netherlands, with written knowledgeable consent for whole-body donation earlier than the donors’ dying and ready as described earlier than²³. No donor had a scientific report of neurological illness. Extra approval from the Ethics Committee of the Medical School of the College of Leipzig, Germany (153/17-ek), was obtained for the MRI scans in Leipzig. Tissue was perfusion-fixed inside 24h after the donor’s demise with a formaldehyde-ethanol combination adopted by postfixation for 30 days.

Tissue chopping and 3D block-face imaging

We obtained 3D block-face photos (BFI) with a decision of 150 × 150 × 200 μm³ as described intimately earlier than^20,23 (Fig. 3A-C). In brief, brains had been extracted, saturated in sucrose, slowly frozen to −20^°, and embedded in TissueTek OCT resin earlier than they had been lower into 200 μm thick coronal sections utilizing a cryomacrotome. Block-face photos had been acquired earlier than chopping every part, attaining an isotropic in-plane decision of (150 μm)². One tissue specimen broke throughout chopping, however the substantia nigra remained intact, permitting us to make use of it for segmenting the nigrosomes. 3D BFI had been reconstructed by stacking BFI with out additional alignment and changing BFI from colour to a gray-scale lightness index. To enhance the visibility of nigrosomes, an edge-preserving median picture filter was utilized to the 3D BF²³.

Gold-standard anti-calbindin immunohistochemistry validates 3D ultra-high-resolution nigrosome 1 (N1) and substantia nigra (SN) segmentations in 3D block-face photos (BFI) of publish mortem specimens. (A),(B), (C) The nigrosomes had been recognized as areas of low anti-calbindin immunoreaction in two publish mortem mind specimens (areas indicated with dotted coloured outlines in (C). A black arrow in B signifies the stripe-like look of N1. The SN was recognized as a area of elevated calbindin immunoreactivity (D–F). The nigrosomes had been recognized and segmented in 3D in gray-valued BFI as darkish areas with excessive DN density and morphology consistent with Damier et al.^3,5. As in B, a black arrow in E signifies N1. The SN was segmented as an space darker than the encircling tissue. C was manually affinely registered to F for simpler comparability.

Anti-calbindin-D28K immunohistochemistry

To confirm the nigrosome and substantia nigra delineation, we used 200 μm sections stained with an antibody directed towards calbindin-D28K¹ at an 1:6 interval (donor 3 and 4), as described beforehand²³ (Fig. 3D–F). After thawing and rinsing of the sections, they had been incubated in a single day within the major antibody. A biotinylated secondary antibody was used, and the sign was amplified utilizing an avidine-biotinylated complicated. The sign was visualised utilizing 3,3({prime} )-diaminobenzidine as a chromogen. After mounting, dehydration, and coverslipping utilizing Entellan, sections had been imaged at a 21 μm in-plane decision. The ensuing photos had been co-registered to the BFI utilizing a forward-backward method throughout slices²⁰, using the ANTs SyN algorithm²⁴.^{Footnote 1}

Histological gold-standard segmentations

To acquire gold-standard definitions of the substantia nigra and the nigrosomes, we used 3D-reconstructed anti-calbindin immunohistochemistry obtained on two publish mortem tissue specimens described within the earlier part, following the nigrosome and SN definitions of Damier et al.³ (Fig. 3A–C). Calbindin staining was out there at a 1:6 interval. All out there calbindin sections of the SN had been included in our analyses. We segmented the nigrosomes and the SN solely in these sections of the 3D-reconstructed photos that corresponded to calbindin-stained sections. All segmentations had been carried out utilizing the 3D Slicer²⁵ and FSLeyes²⁶ software program.

Substantia nigra

Completely different histochemical methods have been proposed to supply gold-standard outlines of the SN, which produce barely totally different outcomes². These approaches are based mostly on the expression of calbindin, enkephalin, and substance P². For constant SN segmentation on the sub-millimeter size scale, we used certainly one of these definitions, based mostly on the picture distinction in 3D-reconstructed anti-calbindin microscopy photos, to delineate the SN. Within the space between the nucleus ruber and the crus cerebri, we discovered an space of elevated immunoreactivity within the anti-calbindin microscopy photos, which we outlined because the SN.

Nigrosomes

We delineated the nigrosomes in 2D histological sections on which anti-calbindin immunohistochemistry had been carried out, following their authentic definition^3,5. On coronal sections, the most important nigrosome, N1, appeared as an elongated, diagonally oriented band extending throughout the SN from its inferomedial to its superolateral side, curving barely medially at its inferior finish and superiorly at its superior finish. N2, the second-largest nigrosome, was positioned on the inferomedial extremity of the SN, largely coinciding with the SN border in that area. N3 introduced as a small, spherical area on the superolateral extremity of the SNc, roughly alongside the trajectory outlined by the superolateral phase of N1. N4 and N5 had been positioned medial to N1, with N4 located posterior to N5. All anatomical instructions are given relative to the coronal chopping aircraft of the 3D block-face photos and histology.

Extremely-high-resolution 3D delineations

We created ultra-high-resolution 3D delineations of the substantia nigra and the nigrosomes utilizing the picture distinction in 3D block-face photos (Fig. 3D–F).

Nigrosomes

Areas with a excessive density of neuromelanin-pigmented DN and the morphology of the nigrosomes³ had been segmented on BFI. A neuroanatomy professional (M.M.) segmented NM-rich areas in each tenth coronal part from posterior to anterior and instructed two non-expert raters in segmentation (C.Jan. and M.B.). These segmentation had been subsequently stuffed and refined by one rater for every case and reviewed by the neuroanatomy professional. The process was iterated a number of instances to make sure a high-quality segmentation, precisely reflecting the spatial association of the nigrosomes³. We outlined these DN-rich areas as nigrosomes following their spatial association described above. Whereas most nigrosomes have a transparent boundary, the border between N4 and N5 was troublesome to delineate exactly as each nigrosomes have a reticular look and not using a clearly outlined boundary.

Substantia nigra

In 3D BFI, the SN was delineated as a hypointense construction enveloped rostromedially by the nucleus ruber and ventrolaterally by the crus cerebri. Within the posterior portion of the SN, the ventro-lateral border was sharp apart from essentially the most medial portion, which displays a pointy improve in myelin content material within the crus cerebri. There, we adopted the bending of the hypointense, pigmented arc of nigrosome 1 (N1) and N2 (Fig. 3E), utilizing N2 to outline the medial border of the SN. The rostromedial border was extra diffuse. For a constant definition of this border, we adopted the road between the rostromedial borders of N2 and N4. This resulted in a constant segmentation within the posterior portion of the SN the place the nigrosomes are located. Within the anterior portion of the SN, it was tougher to outline constant, sharp borders in BFI and calbindin. We used the mamillary physique as an anatomical reference for the SN’s constant most anterior extent.

Segmentation validation

To validate the 3D nigrosome and substantia nigra delineations, we in contrast them to the gold-standard calbindin immunohistochemistry in two specimens. To validate this 3D ultra-high-resolution SN delineation, we quantitatively in contrast it to the histological gold normal SN delineation described above. We calculated the Cube coefficients of each delineations on the sections within the BFI on which calbindin immunohistochemistry was out there.

Multimodal registration for creating the nigrosome atlas

We employed automated registration methods to co-align the multi-modal histological and MRI information used on this research. First, we registered 4 publish mortem datasets to a typical area utilizing substantia nigra delineations and created chance maps of the 5 nigrosomes. Second, we registered these nigrosome chance maps to the AHEAD template^6,27 within the MNI152 2009b area^21,28 (retrieved on 13.07.2026 from https://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009) to create a neuroimaging atlas of the nigrosomes. Third, to validate the nigrosome atlas, we registered an unbiased BigBrain dataset to the AHEAD template and in contrast our atlas of nigrosome 1 to it’s established distinction on publish mortem MRI. Fourth, to show the applying of our atlas, we registered the in vivo quantitative MRI dataset to the AHEAD template. For all registrations, we relied on the SyN algorithm in ANTs²⁴, embedded within the ANTsPy²⁹ and Nighres³⁰ toolboxes.

Registration of nigrosome segmentations to create nigrosome chance maps

To deliver the nigrosome segmentations to a typical area, we co-registered the ultra-high-resolution 3D SN delineations of the 4 particular person datasets to a typical area, which was outlined by the block face picture of donor 3 (specimen # 7 in²³). To this finish, we utilized a two-step registration process utilizing AntsPy. We first used a smaller, then a bigger gradient step of 0.1 and 0.2 as outlined in AntsPy, respectively, to carry out registrations with excessive and low regularization, respectively. We used the imply squared distinction as a metric and the AntsPy default values of all different parameters. This registration enabled us to remodel the nigrosome delineations of 4 circumstances into a typical area, utilizing nearest-neighbor interpolation. On this area, we created chance maps for every of the 5 nigrosomes by summing the binary nigrosome segmentations of the 4 circumstances and dividing the maps by the variety of specimens. We utilized the identical process to the ultra-high-resolution 3D SN segmentations to acquire an SN chance map.

Registration of nigrosome chance maps to AHEAD template to create nigrosome atlas

To deliver the nigrosome and SN chance maps to the usual MNI152 2009b area²¹, we co-registered the block-face picture with the most effective picture high quality (specimen 3) to the multi-contrast quantitative MRI AHEAD template⁶ utilizing the focused_antsreg operate in Nighres³⁰ (Fig. 4A). This operate contains a two-step ANTs registration process: First, it aligns whole-brain photos and, second, focuses the registration round a given area. We registered the BFI to the quantitative proton density (PD), susceptibility (χ), R₁ = 1/T₁, the place T₁ is the longitudinal rest time, and ({R}_{2}^{* }=1/{T}_{2}^{* }) of the AHEAD template utilizing cross-correlation as a registration metric (Fig. 4B–E). We first registered with excessive after which with low regularization. We used the SN masks of the MASSP atlas¹² for making a registration focus with easily lowering depth exterior of the SN masks. We utilized the ensuing transformation to the 3D ultra-high-resolution nigrosome and SN chance maps, yielding histological nigrosome and SN atlases in MNI152 2009b area.

The nigrosome atlas aligned to the AHEAD template⁶ in MNI152 2009b template area²¹. (A) A 3-dimensional illustration of the nigrosome atlas (coloured volumes) inside the substantia nigra (clear brown quantity). The view follows the anterior-posterior axis by means of the mind. For an accessible 3D view, we included a video of the nigrosome atlas within the information repository (https://osf.io/gsphy/files/nzxp2). The anatomical reference body is indicated, the place the anterior path factors towards the viewer. (B–E). The chance maps (p) of the nigrosomes 1-4 (N1-N4) are proven overlaid on the proton density (PD), susceptibility (χ), longitudinal rest charge (R₁), and efficient transverse rest charge (({R}_{2}^{* })) maps of the AHEAD template. Because the nigrosomes don’t prolong over your entire SN, solely nigrosomes N1-4 are seen on this part, which corresponds roughly to the histological part displayed in Fig. 1A. Whereas some asymmetry of the chance maps is clear, the positions of the nigrosomes and their spatial relationship to one another and the boundary between SN and the encircling white matter are in step with the unique nigrosome definition (Fig. 1B). Furthermore, N1 crosses and extends past the dorsolateral hypointensity in χ and ({R}_{2}^{* }) maps, as anticipated from earlier analysis¹⁰.

Nigrosome atlas validation towards classical SN parcellations

To validate the ensuing nigrosome atlas, we in contrast its topology with classical neuroanatomical descriptions by Halliday et al.². We developed a way for automated parcellation of the three anatomical layers inside the substantia nigra (SN). The chance maps of the 5 nigrosomes had been projected onto these layers, and their relative positions had been visualized in layer projections and in contrast with classical qualitative parcellations based mostly on 2D histology.

Laplacian embedding of nigrosomes into layered SN representations

To outline three discrete anatomical layers inside SN comparable to their dorsal tier, ventral tier, and pars reticulata subdivisions, we outlined a coordinate system intrinsic to the SN with one axis aligned to SN’s thinnest dimension. A graph between all voxels contained in the SN was created with distances outlined as a weighted mixture of Euclidean distance and distance to the SN boundary as in³¹, utilizing the spectral_voxel_thickness_embedding operate in Nighres³⁰. The obtained graph was remodeled by approximate Laplacian embedding³², the place the primary three dimensions of embedding outline a curved coordinate system following the form of the SN (Fig. 5). The embedding throughout the thickness of the SN was subdivided into three layers approximating the anatomically outlined tiers, based mostly on histograms of the nigrosome relative depths (Fig. 5A), and the probabilistic maps of every nigrosome had been averaged inside every layer and displayed alongside the 2 orthogonal embedding instructions (Fig. 5B).

Validation of the anatomical plausibility of the 3D nigrosome atlas towards classical substantia nigra (SN) delineations. A: Prime: Translation of the classical delineations into the area of the 3D atlas. Anatomical layers inside the substantia nigra (SN) had been outlined based mostly on form evaluation. The thinnest dimension was routinely decided, and the SN was subdivided into three layers approximating the ventral and dorsal tiers (pars compacta) and pars reticulata. Backside: Automated segmentation of the SN into three layers based mostly on geometric evaluation in a coronal slice. B: Left: Projection of the 3D nigrosome atlas onto the outlined layers. Proper: Association of nigrosomes inside the dorsal tier (nigrosome 1) and ventral tier (nigrosomes 2–5). The schematic was tailored from². The relative spatial association of the nigrosomes in our atlas corresponds nicely to qualitative histological delineations, demonstrating the anatomical plausibility of the 3D atlas.

Unbiased multi-modal dataset for technical validation

To evaluate the accuracy of the automated registration process ultra-high decision nigrosome atlas, we employed an unbiased dataset comprising ultra-high-field and -resolution publish mortem MRI ³³ (Fig. 6). Right here, we define tissue processing and MRI acquisition. The publish mortem mind was obtained from the physique donor program of the Anatomical Institute of the College of Düsseldorf, Germany (moral vote of the medical school of the Heinrich-Heine-College Düsseldorf #4863).

Validating the nigrosome atlas utilizing a BigBrain dataset²². To validate the accuracy of our nigrosome atlas, we reproduce a discovering that we beforehand reported: nigrosome 1 seems as a hyperintense stripe in ({R}_{2}^{* }) maps of publish mortem mind specimens¹⁰. In an ({R}_{2}^{* }) map acquired on the BigBrain specimen ((A)), a hyperintense stripe is seen within the substantia nigra (marked in pink in B). After utilizing the registration routine, we aligned our nigrosome atlas to a BigBrain dataset. Nigrosome 1 (blue space in C) overlaps strongly with the hyperintense stripe (overlay in D). This implies that the proposed registration routine is exact sufficient to allow neuroimaging of the nigrosomes. Moreover, the nigrosome anatomy captured by our atlas captures the anatomy on this unbiased dataset precisely.

Tissue processing

A publish mortem human mind (feminine, age of dying: 73 years, explanation for dying: acute respiratory syndrome, publish mortem time earlier than fixation: 7 hours) was fastened in 4 % paraformaldehyde resolution for 4 months. Tissue acquisition, dealing with, and fixation procedures adopted the process described intimately in²².

MRI

The mind was transferred to a phosphate-buffered resolution (PBS, pH 7.4) 72 hours earlier than scanning to take away formaldehyde monomers, thereby bettering picture distinction. The mind was coated and padded with cotton tissues for MRI scanning to stop cortical injury. Then, it was positioned in a custom-made head-shaped container full of degassed PBS. The container was uncovered to 1mbar vacuum for 12hours to take away air bubbles. Multi-parameteric mapping (MPM)³⁴ information had been acquired on a 7 T system (7 T Terra, Siemens Healthineers, Erlangen, Germany), utilizing a 32-channel radio-frequency head coil (Nova Medical, Wilmington, USA). 4 multi-echo 3D FLASH acquisitions had been obtained with totally different weightings: proton-density-weighted, longitudinal-relaxation-time (T₁)-weighted, magnetization-transfer (MT)-weighted, and a scan at Ernst angle. The next parameters had been used: repetition time (T_R) = 50 ms; eight equidistant echoes with echo instances T_E1…8 = 3.66…22.56 ms acquired utilizing bipolar readout; isotropic decision of 0.3mm (field-of-view (FOV) = 192 mm, matrix 640 × 640); and a bandwidth of BW = 434 Hz/pixel. Excitation flip angles (FA) had been FA = 11^° for the proton density and magnetization transfer-weighted scans, FA = 25^° for the Ernst angle scan, and FA = 59^° for the T₁-weighted scan. A further calibration scan for FA mapping was obtained utilizing the Bloch-Siegert-Shift methodology³⁵. The quantitative maps (PD, R₁, ({R}_{2}^{* })) had been reconstructed utilizing a custom-made model of the hMRI toolbox (hMRI.data), tailored for publish mortem and seven T imaging³⁶, utilizing a three-flip-angle calculation with out making use of a small-flip-angle approximation.

Registration of nigrosome atlas to unbiased publish mortem dataset

To validate the nigrosome atlas, we mapped it onto an unbiased, newly acquired BigBrain dataset that was histologically processed in line with²². This dataset contains quantitative maps of R₁ and ({R}_{2}^{* }), and a semi-quantitative PD map, all with 0.3mm isotropic decision.

Using the focused_antspy operate in Nighres as above, we registered these maps to the corresponding maps of the AHEAD template. We used the registration outcome to remodel the nigrosome atlas to the area of the BigBrain dataset.

In vivo quantitative MRI for utilization illustration

To show the utilization of the nigrosome atlas, we aligned it to in vivo MRI datasets acquired on 4 wholesome volunteers, utilizing the registration process described above (Figs. 7–9).

A utilization instance of the nigrosome atlas. Utilizing the proposed devoted registration, we aligned the nigrosome atlas to 4 in vivo quantitative MRI datasets, certainly one of which is proven as a consultant instance in coronal view. The dataset contains quantitative maps of magnetization switch saturation MTsat (A,B), proton density PD (C,D), susceptibility χ (E,F), longitudinal rest charge R₁ (G,H), and efficient transverse rest charge ({R}_{2}^{* }) (I,J). The accuracy of the nigrosome atlas and the used registration is underscored by the alignment of N1 with the border between the hypointense substantia nigra and hyperintense crus cerebri within the MTsat map: N1 is positioned exactly on the border however contained in the substantia nigra. Word that the hyperintense area encompassing the substantia nigra within the ({R}_{2}^{* }) map exhibits a extra lateral border to crus cerebri, as has been reported earlier than⁴⁹.

The utilization instance of the nigrosome atlas, introduced in Fig. 7, is proven in axial view. Labels are as in Fig. 7. The accuracy of the nigrosome atlas and the used registration is underscored by the alignment of N1 with the border between the hypointense substantia nigra and hyperintense crus cerebri within the MTsat map: N1 is positioned exactly on the border however contained in the substantia nigra, just like the coronal view. Furthermore, the nigrosomes are nicely inside the iron-rich space of the SN, seen as areas of elevated values in χ and ({R}_{2}^{* }).

The utilization instance of the nigrosome atlas, introduced in Fig. 7, is proven in sagittal view. Labels are as in Fig. 7. The accuracy of the nigrosome atlas and the used registration is underscored by the alignment of N1 with the border between the hypointense substantia nigra and hyperintense crus cerebri within the MTsat map: N1 is positioned exactly on the border however contained in the substantia nigra, just like the coronal and axial views. Furthermore, the nigrosomes are nicely inside the iron-rich space of the SN, seen as areas of elevated values in χ and ({R}_{2}^{* }).

MRI

4 wholesome grownup members (1 feminine, imply age 45.25 ± 6.3years), every took half in no less than two scanning classes on a 7 T system (7 T Terra, Siemens Healthineers, Erlangen, Germany) utilizing parallel transmission (pTx) and an 8 transmit-/32 receive-channel radiofrequency head coil (Nova Medical, Wilmington, USA). Scanning was carried out throughout two websites: the MPI CBS in Leipzig, Germany, and the GIGA-Institute in Liége, Belgium. The research at MPI CBS was authorised by the Ethics Committee of the School of Drugs, Leipzig College (approval no. 187/22-ek; authorised on 22.06.2022).

MPM acquisition consisted of three whole-brain multi-echo 3D FLASH acquisitions with totally different weightings (PD, T₁ and MT-weighted) with parallel transmit (pTx) kT-points excitation at an isotropic decision of 0.6 mm (FOV = 218 mm × 250 mm × 173 mm, matrix  = 364 × 416 × 288). The next parameters had been used: T_R = 22.4 ms, FA for PDw/MTw/T₁w had been 7°/7°/22°, with six (4 for MT-weighted) equidistant echoes T_E1…6 = 3.00…15.6 ms. Parallel imaging utilizing CAIPIRINHA with an acceleration issue R = 2 × 2 enabled acquisition time 8.25 min per distinction. B₁ mapping for transmit subject correction was carried out utilizing the AFI methodology with kT-points excitation³⁷. The B₁ mapping was repeated with a traditional excitation pulse to appropriate for spatial inhomogeneity within the MT saturation. The overall acquisition time, together with shimming, was round 35 min.

Photographs had been reconstructed with AC-LORAKS^38,39 and MCPC-3D-S⁴⁰ adopted by LCPCA denoising¹². The photographs had been processed with the open supply hMRI toolbox³⁶, yielding ({R}_{2}^{* }), PD, MTsat, and R₁ maps. Subcortical buildings had been routinely parcellated by MASSP utilizing all three contrasts as enter¹². QSM was moreover calculated for every distinction by QSMxT⁴¹ and mixed utilizing the strong mixture function of the hMRI toolbox⁴², weighting the contrasts by the inverse of the standard maps produced by QSMxT’s phase-unwrapping step, speedy open-source minimal spanning tree algorithm (ROMEO)⁴³.

To check the robustness of the proposed pipeline, we carried out a number of comparisons of registration accuracy. First, we examined the test-retest reliability of the nigrosome alignment by making use of the above protocol twice to all 4 members. Second, to check the robustness between acquisition protocols, we acquired one dataset utilizing one other multi-parametric MRI methodology, the MP2RAGEME sequence⁴⁴, at 7 T, and a decision of 0.7mm (acquisition parameters are given in⁴⁴). Third, to check robustness throughout totally different subject strengths, certainly one of these members was moreover scanned utilizing the identical MPM methodology applied at 3 T, and a decrease decision of 0.8mm. For all these checks, we assessed the registration accuracy by evaluating the SN masks included within the nigrosome atlas utilizing Nighres³⁰. We calculated quantity variations, Cube overlaps, dilated Cube overlaps, and common floor distances for every SN masks in comparison with the one obtained for the MPM acquisition at 7 T.

Registration nigrosome atlas to in vivo dataset

To show the utilization of the nigrosome atlas, we utilized it to an in vivo MRI dataset comprising quantitative maps of proton density, R₁, and ({R}_{2}^{* }) with an isotropic decision of 0.6mm.

To align the in vivo MRI information to the AHEAD template, we employed the focused_antspy operate in Nighres as above, registering the in vivo quantitative maps to the corresponding map of the AHEAD template. We used the registration outcome to remodel the nigrosome atlas to the area of the in vivo MRI dataset.

To show that our pipeline works on scientific populations, we aligned the nigrosome atlas to MRI information acquired on a PD affected person, who was scanned utilizing the 7 T MPM protocol on the GIGA-Institute in Liége, Belgium (Fig. 10). The participant was a 73-year-old lady with a 1-year historical past of Parkinson’s illness. Motor symptom severity was assessed utilizing Half III of the Motion Dysfunction Society-Unified Parkinson’s Illness Ranking Scale (MDS-UPDRS), on which she obtained a rating of 31. On the time of evaluation, she was categorised as Hoehn and Yahr (H&Y) stage 2, indicating bilateral involvement with out impairment of steadiness. The research at GIGA-CRC Human Imaging of the Université de Liége was authorised by the School-Hospital ethics committee of the College Liége (approval 2022/05; authorised on 04/13/2022).

The nigrosome atlas utilized to MRI information acquired on a affected person with Parkinson’s illness. The proposed devoted registration was used as for the wholesome controls. The dataset contains quantitative maps of susceptibility χ (A,B), longitudinal rest charge R₁ (C,D), and efficient transverse rest charge ({R}_{2}^{* }) (E,F). As for the wholesome controls, the atlas’ nigrosome areas are principally contained inside the hyperintense area encompassing the iron-rich substantia nigra within the χ and ({R}_{2}^{* }) maps, indicating a stable registration efficiency.