Automatic detection of neuromelanin and iron in the midbrain nuclei using a magnetic resonance imaging‐based brain template

Abstract

Parkinson disease (PD) is a chronic progressive neurodegenerative disorder characterized pathologically by early loss of neuromelanin (NM) in the substantia nigra pars compacta (SNpc) and increased iron deposition in the substantia nigra (SN). Degeneration of the SN presents as a 50 to 70% loss of pigmented neurons in the ventral lateral tier of the SNpc at the onset of symptoms. Also, using magnetic resonance imaging (MRI), iron deposition and volume changes of the red nucleus (RN), and subthalamic nucleus (STN) have been reported to be associated with disease status and rate of progression. Further, the STN serves as an important target for deep brain stimulation treatment in advanced PD patients. Therefore, an accurate in-vivo delineation of the SN, its subregions and other midbrain structures such as the RN and STN could be useful to better study iron and NM changes in PD. Our goal was to use an MRI template to create an automatic midbrain deep gray matter nuclei segmentation approach based on iron and NM contrast derived from a single, multiecho magnetization transfer contrast gradient echo (MTC-GRE) imaging sequence. The short echo TE = 7.5 ms data from a 3D MTC-GRE sequence was used to find the NM-rich region, while the second echo TE = 15 ms was used to calculate the quantitative susceptibility map for 87 healthy subjects (mean age ± SD: 63.4 ± 6.2 years old, range: 45-81 years). From these data, we created both NM and iron templates and calculated the boundaries of each midbrain nucleus in template space, mapped these boundaries back to the original space and then fine-tuned the boundaries in the Zhijia Jin, Ying Wang, and Mojtaba Jokar contributed equally to this study.

Automated volumetric determination of high R2* regions in substantia nigra: A feasibility study of quantifying substantia nigra atrophy in progressive supranuclear palsy

“…2,[28][29][30] In most previous studies, measured bilateral SN volumes range from 110 to 700 mm 3 , showing a high degree of variation. 3,10,30,31 In one previous paper investigating susceptibility-related MRI, average SN volumes of 541 and 621 mm 3 for HC and PD, respectively, were reported from manually segmented masks surrounding the hypointense area in T 2 * -weighted images. 3 By comparison, the bilateral SN volumes in our study ranges from 1128 to 1527 mm 3 .…”

“…One recent study reported the segmentation of SN using QSM data by advanced image analysis with DSC values of 0.75 and 0.76 in left and right SN, respectively 11 . Different neuromelanin‐ and iron‐containing midbrain nuclei were also segmented using a template of the brain from QSM data and achieved a DSC of 0.85 and 0.87 for neuromelanin‐ and iron‐containing SN, respectively 10 . 3D SN segmentation on neuromelanin‐sensitive MRI and SWI using a V‐net convolutional neural network yielded an average DSC in five‐fold cross‐validation of 0.7 8 .…”

“…Because SN is very small in whole‐brain structural MRI and each MRI contrast shows a disparate boundary, accurate SN segmentation is challenging and remains controversial 2,28–30 . In most previous studies, measured bilateral SN volumes range from 110 to 700 mm 3 , showing a high degree of variation 3,10,30,31 . In one previous paper investigating susceptibility‐related MRI, average SN volumes of 541 and 621 mm 3 for HC and PD, respectively, were reported from manually segmented masks surrounding the hypointense area in T 2 * ‐weighted images 3 .…”

“…Because unbiased and reproducible methods involving deep learning can potentially contribute to accurate segmentation, previous studies have investigated the automatic segmentation of SN using a convolutional neural network 7–10 . The segmentation of the SN has been mostly performed on qualitative MRI, such as neuromelanin‐sensitive MRI and susceptibility‐weighted imaging (SWI), whose contrasts may vary depending on the subjects, scanner, and scanning parameters 7–9 .…”

“…The segmentation of the SN has been mostly performed on qualitative MRI, such as neuromelanin‐sensitive MRI and susceptibility‐weighted imaging (SWI), whose contrasts may vary depending on the subjects, scanner, and scanning parameters 7–9 . In recent years, for reasons of necessity, segmentation of SN was also performed using one of quantitative MRI, quantitative susceptibility mapping (QSM) 10,11 . To maximize the diagnostic efficacy of PSP through investigating morphological changes in the iron‐rich SN region, a comparative study on the accuracy and diagnostic ability of automated measurements of SN volume and surface area between quantitative ( R 2 * map) and qualitative (SWI) MRI is required, where both show iron‐sensitive MR contrasts and are reconstructed from one gradient‐based sequence 12 .…”