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Ahrens J, Zaher F, Rabin RA, Cassidy CM, Palaniyappan L. Neuromelanin levels in individuals with substance use disorders: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 161:105690. [PMID: 38678736 DOI: 10.1016/j.neubiorev.2024.105690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 04/15/2024] [Accepted: 04/23/2024] [Indexed: 05/01/2024]
Abstract
Dopamine's role in addiction has been extensively studied, revealing disruptions in its functioning throughout all addiction stages. Neuromelanin in the substantia nigra (SN) may reflect dopamine auto-oxidation, and can be quantified using neuromelaninsensitive magnetic resonance imaging (neuromelanin-MRI) in a non-invasive manner.In this pre-registered systematic review, we assess the current body of evidence related to neuromelanin levels in substance use disorders, using both post-mortem and MRI examinations. The systematic search identified 10 relevant articles, primarily focusing on the substantia nigra. An early-stage meta-analysis (n = 6) revealed varied observations ranging from standardized mean differences of -3.55 to +0.62, with a pooled estimate of -0.44 (95 % CI = -1.52, 0.65), but there was insufficient power to detect differences in neuromelanin content among individuals with substance use disorders. Our gap analysis highlights the lack of sufficient replication studies, with existing studies lacking the power to detect a true difference, and a complete lack of neuromelanin studies on certain substances of clinical interest. We provide recommendations for future studies of dopaminergic neurobiology in addictions and related psychiatric comorbidities.
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Affiliation(s)
- Jessica Ahrens
- Douglas Research Centre, Douglas Mental Health Research Institute, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Farida Zaher
- Douglas Research Centre, Douglas Mental Health Research Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Rachel A Rabin
- Douglas Research Centre, Douglas Mental Health Research Institute, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Clifford M Cassidy
- Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Lena Palaniyappan
- Douglas Research Centre, Douglas Mental Health Research Institute, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.
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Oshima S, Fushimi Y, Miyake KK, Nakajima S, Sakata A, Okuchi S, Hinoda T, Otani S, Numamoto H, Fujimoto K, Shima A, Nambu M, Sawamoto N, Takahashi R, Ueno K, Saga T, Nakamoto Y. Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance. Jpn J Radiol 2023; 41:1216-1225. [PMID: 37256470 PMCID: PMC10613599 DOI: 10.1007/s11604-023-01452-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/16/2023] [Indexed: 06/01/2023]
Abstract
PURPOSE Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson's disease (PD) by showing reduced signals in the substantia nigra (SN) and locus coeruleus (LC), but requires a long scan time. The aim of this study was to assess the image quality and diagnostic performance of NM-MRI with a shortened scan time using a denoising approach with deep learning-based reconstruction (dDLR). MATERIALS AND METHODS We enrolled 22 healthy volunteers, 22 non-PD patients and 22 patients with PD who underwent NM-MRI, and performed manual ROI-based analysis. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in ten healthy volunteers were compared among images with a number of excitations (NEX) of 1 (NEX1), NEX1 images with dDLR (NEX1 + dDLR) and 5-NEX images (NEX5). Acquisition times for NEX1 and NEX5 were 3 min 12 s and 15 min 58 s, respectively. Diagnostic performances using the contrast ratio (CR) of the SN (CR_SN) and LC (CR_LC) and those by visual assessment for differentiating PD from non-PD were also compared between NEX1 and NEX1 + dDLR. RESULTS Image quality analyses revealed that SNRs and CNRs of the SN and LC in NEX1 + dDLR were significantly higher than in NEX1, and comparable to those in NEX5. In diagnostic performance analysis, areas under the receiver operating characteristic curve (AUC) using CR_SN and CR_LC of NEX1 + dDLR were 0.87 and 0.75, respectively, which had no significant difference with those of NEX1. Visual assessment showed improvement of diagnostic performance by applying dDLR. CONCLUSION Image quality for NEX1 + dDLR was comparable to that of NEX5. dDLR has the potential to reduce scan time of NM-MRI without degrading image quality. Both 1-NEX NM-MRI with and without dDLR showed high AUCs for diagnosing PD by CR. The results of visual assessment suggest advantages of dDLR. Further tuning of dDLR would be expected to provide clinical merits in diagnosing PD.
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Affiliation(s)
- Sonoko Oshima
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
| | - Kanae Kawai Miyake
- Department of Advanced Medical Imaging Research, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Satoshi Nakajima
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Sachi Okuchi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Takuya Hinoda
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Sayo Otani
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Hitomi Numamoto
- Department of Advanced Medical Imaging Research, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Atsushi Shima
- Department of Regenerative Systems Neuroscience, Human Brain Research Center, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Masahito Nambu
- MRI Systems Division, Canon Medical Systems Corporation, 1385 Shimoishigami, Otawara-Shi, Tochigi, 324-0036, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Kentaro Ueno
- Department of Biomedical Statistics and Bioinformatics, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Tsuneo Saga
- Department of Advanced Medical Imaging Research, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan
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Fujii H, Sato N, Kimura Y, Mizutani M, Kusama M, Sumitomo N, Chiba E, Shigemoto Y, Takao M, Takayama Y, Iwasaki M, Nakagawa E, Mori H. MR Imaging Detection of CNS Lesions in Tuberous Sclerosis Complex: The Usefulness of T1WI with Chemical Shift Selective Images. AJNR Am J Neuroradiol 2022; 43:1202-1209. [PMID: 35835590 PMCID: PMC9575409 DOI: 10.3174/ajnr.a7573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 05/24/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE CNS lesions of tuberous sclerosis complex are diagnosed mainly by T2WI, FLAIR, and sometimes T1WI with magnetization transfer contrast. The usefulness of T1WI with chemical shift selective images was recently reported in focal cortical dysplasia type IIb, which has histopathologic and imaging features similar to those of tuberous sclerosis complex. We investigated the usefulness of the T1WI with chemical shift selective images in detecting CNS lesions of tuberous sclerosis complex. MATERIALS AND METHODS We retrospectively reviewed 25 consecutive patients with tuberous sclerosis complex (mean age, 11.9 [SD, 8.9] years; 14 males) who underwent MR imaging including T1WI, T1WI with magnetization transfer contrast, T1WI with chemical shift selective, T2WI, and FLAIR images. Two neuroradiologists assessed the number of CNS lesions in each sequence and compared them in 2 steps: among T1WI, T1WI with magnetization transfer contrast and T1WI with chemical shift selective images, and among T2WI, FLAIR, and T1WI with chemical shift selective images. We calculated the contrast ratio of the cortical tubers and of adjacent normal-appearing gray matter and the contrast ratio of radial migration lines and adjacent normal-appearing white matter in each sequence and compared them. RESULTS T1WI with chemical shift selective images was significantly superior to T1WI with magnetization transfer contrast for the detection of radial migration lines and contrast ratio of radial migration lines. There was no significant difference between T1WI with chemical shift selective images and T1WI with magnetization transfer contrast for the detection of cortical tubers and the contrast ratio of the cortical tubers. Both T2WI and FLAIR were statistically superior to T1WI with chemical shift selective images for the detection of cortical tubers. T1WI with chemical shift selective images was significantly superior to T2WI and FLAIR for the detection of radial migration lines. CONCLUSIONS The usefulness of T1WI with chemical shift selective images in detecting radial migration lines was demonstrated. Our findings suggest that the combination of T1WI with chemical shift selective images, T2WI, and FLAIR would be useful to evaluate the CNS lesions of patients with tuberous sclerosis complex in daily clinical practice.
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Affiliation(s)
- H Fujii
- From the Departments of Radiology (H.F., N.Sato, Y.K., M.K., E.C., Y.S.).,Department of Radiology (H.F., H.M.), Jichi Medical University, School of Medicine, Shimotsuke, Tochigi, Japan
| | - N Sato
- From the Departments of Radiology (H.F., N.Sato, Y.K., M.K., E.C., Y.S.)
| | - Y Kimura
- From the Departments of Radiology (H.F., N.Sato, Y.K., M.K., E.C., Y.S.)
| | - M Mizutani
- Pathology and Laboratory Medicine (M.M., M.T.)
| | - M Kusama
- From the Departments of Radiology (H.F., N.Sato, Y.K., M.K., E.C., Y.S.)
| | | | - E Chiba
- From the Departments of Radiology (H.F., N.Sato, Y.K., M.K., E.C., Y.S.)
| | - Y Shigemoto
- From the Departments of Radiology (H.F., N.Sato, Y.K., M.K., E.C., Y.S.)
| | - M Takao
- Pathology and Laboratory Medicine (M.M., M.T.)
| | - Y Takayama
- Neurosurgery (Y.T., M.I.), National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - M Iwasaki
- Neurosurgery (Y.T., M.I.), National Center Hospital, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | | | - H Mori
- Department of Radiology (H.F., H.M.), Jichi Medical University, School of Medicine, Shimotsuke, Tochigi, Japan
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