GELİŞMİŞ DİFÜZYON MRG TEKNİKLERİ: HIPPOKAMPAL MİKROYAPI İÇİN HARDI VE NODDI

Abstract

Hipokampus, medial temporal lobda bulunan ve hafıza, öğrenme ve uzamsal oryantasyon gibi temel bilişsel süreçlerde önemli bir rol oynayan bir beyin yapısıdır ve alt bölge düzeyinde önemli yapısal ve işlevsel heterojenlik gösterir. Geleneksel manyetik rezonans görüntüleme, hipokampusun şeklini, yapısını ve makroskopik bütünlüğünü değerlendirmek için öncelikle hacimsel ölçümlere dayanır; ancak bu ölçümler, nöronal ve dendritik organizasyondaki mikroyapısal değişiklikleri değerlendirmede sınırlıdır. Hacimsel olarak korunmuş görünen hipokampal alt bölgelerdeki mikroyapısal değişiklikleri tespit etmek için daha hassas görüntüleme yaklaşımları gereklidir. Difüzyon manyetik rezonans görüntüleme (dMRI), doku mikroyapısının in vivo değerlendirmesini sağlayan önemli bir nörogörüntüleme tekniğidir. Yaygın olarak tercih edilen difüzyon tensör görüntüleme (DTI) yöntemi, hipokampus gibi gri madde ağırlıklı ve önemli intravoxel heterojenliği gösteren yapılarda çeşitli sınırlamalara sahiptir. Yeni yaklaşımlar, tensör modelinin ötesine geçerek doku mikroyapısının daha gelişmiş ve spesifik özelliklerinin belirlenmesini sağlayan biyofiziksel modelleri entegre etmiştir. Bu metodolojik çerçeve içinde, özellikle HARDI gibi gelişmiş difüzyon teknikleri, çok bölmeli modelleme ile birleştirildiğinde, hipokampusun yapısal organizasyonunu daha ayrıntılı olarak inceleme yeteneğimizi geliştirmiştir. Özellikle NODDI, nörit yoğunluğu ve yönelim dağılımı gibi nicel ölçümler sağlayarak, alt bölge düzeyinde gri maddenin mikro yapısının daha incelikli bir şekilde yorumlanmasını kolaylaştırmaktadır. Bu derleme, hipokampal mikroyapının in vivo değerlendirmesinde HARDI ve NODDI kullanımına ilişkin güncel metodolojik ve klinik gelişmeleri özetlemektedir. Mevcut derleme, hipokampal alt bölge segmentasyonunun gelişmiş difüzyon MRI teknikleriyle entegrasyonunu incelemekte ve bu çerçevenin hacimsel değerlendirmenin ötesinde anlayışı nasıl ilerlettiğini ele almaktadır. Metodolojik kısıtlamalar ve ortaya çıkan araştırma yönelimleri de ele alınmaktadır.

Keywords

• hipokampal alt alan segmentasyonu
• gelişmiş difüzyon MRG
• yüksek açısal çözünürlüklü difüzyon görüntüleme
• nörit yönelim dağılımı ve yoğunluk görüntüleme
• gri madde mikro yapısı
• medial temporal lob

Supporting Institution

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Project Number

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Ethical Statement

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Thanks

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Advanced diffusion MRI techniques: Hardi and noddi for hippocampal microstructure

Abstract

The hippocampus is a brain structure located in the medial temporal lobe that plays a key role in fundamental cognitive processes such as memory, learning, and spatial orientation, exhibiting significant structural and functional heterogeneity at the subregional level. Conventional magnetic resonance imaging relies primarily on volumetric measurements to assess the shape, structure, and macroscopic integrity of the hippocampus; however, these measurements are limited in evaluating microstructural changes in neuronal and dendritic organization. Detecting microstructural alterations in hippocampal subregions that appear volumetrically preserved necessitates more advanced imaging approaches. Diffusion magnetic resonance imaging (dMRI) is an important neuroimaging technique that enables in vivo assessment of tissue microstructure. The commonly preferred diffusion tensor imaging (DTI) method has various limitations in structures such as the hippocampus, which are gray matter-dominant and exhibit significant intravoxel heterogeneity. New approaches have gone beyond the tensor model to integrate biophysical models that enable the determination of more advanced and specific features of tissue microstructure. Within this methodological framework, advanced diffusion techniques particularly High Angular Resolution Diffusion Imaging (HARDI) combined with multi-compartment modeling have improved our ability to investigate the structural organization of the hippocampus in greater detail. In particular, Neurite Orientation Dispersion and Density Imaging (NODDI) provides quantitative measures such as neurite density and orientation dispersion, facilitating a more nuanced interpretation of gray matter microstructure at the subregional level. This review summarizes current methodological and clinical developments regarding the use of HARDI and NODDI for the in vivo assessment of hippocampal microstructure. The present review examines the integration of hippocampal subregion segmentation with advanced diffusion MRI techniques and considers how this framework advances understanding beyond volumetric assessment. Methodological constraints and emerging research directions are also addressed.

Keywords

• hippocampal subfield segmentation
• advanced diffusion MRI
• high angular resolution diffusion imaging
• neurite orientation dispersion and density imaging
• gray matter microstructure
• medial temporal lobe

Supporting Institution

N/A

Project Number

N/A

Ethical Statement

N/A

Thanks

N/A

References

1. Zeidman P, Maguire EA. Anterior hippocampus: the anatomy of perception, imagination and episodic memory. Nat Rev Neurosci. 2016 Mar;17(3):173-82. doi: 10.1038/nrn.2015.24. Epub 2016 Feb 11.
2. Voss JL, Bridge DJ, Cohen NJ, Walker JA. A Closer Look at the Hippocampus and Memory. Trends Cogn Sci. 2017 Aug;21(8):577-588. doi: 10.1016/j.tics.2017.05.008. Epub 2017 Jun 15.
3. Small SA, Schobel SA, Buxton RB, Witter MP, Barnes CA. A pathophysiological framework of hippocampal dysfunction in ageing and disease. Nat Rev Neurosci. 2011 Sep 7;12(10):585-601.
4. Strange BA, Witter MP, Lein ES, Moser EI. Functional organization of the hippocampal longitudinal axis. Nat Rev Neurosci. 2014 Oct;15(10):655-69.
5. Pang H, Sun Z, Liang Z, Li C, Zhang J, Ge Y. Microstructural Changes in Aging Hippocampal Pathways: Insights From the HCP-Aging Diffusion MRI Study. Brain Behav. 2025;15:e709.
6. Yu S, Przybelski SA, Reid RI, Lesnick TG, Raghavan S, Graff-Radford J, Lowe VJ, Kantarci K, Knopman DS, et al. NODDI in gray matter is a sensitive marker of aging and early AD changes. Neurobiol Aging. 2024;137:45-54.
7. Jones DK, Knösche TR, Turner R. White matter integrity, fiber count, and other fallacies: the do's and don't's of diffusion MRI. Neuroimage. 2013 Jun;73:239-54.
8. Jelescu IO, Budde MD. Design and validation of diffusion MRI models of white matter. Front Phys. 2017 Nov;28:61.

9. Le Bihan D. Looking into the functional architecture of the brain with diffusion MRI. Nat Rev Neurosci. 2003 Jun;4(6):469-80.
10. Palombo M, Ianus A, Guerreri M, Nunes D, Alexander DC, Shemesh N, Zhang H. SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. Neuroimage. 2020 Jul 15;215:116835.
11. Tournier JD, Calamante F, Connelly A. Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage. 2007 May 1;35(4):1459-72.
12. Schilling KG, Nath V, Hansen C, Parvathaneni P, Blaber J, Gao Y, Neher P, Aydogan DB, Shi Y, Ocampo-Pineda M, Schiavi S, Daducci A, Girard G, Barakovic M, Rafael-Patino J, Romascano D, Rensonnet G, Pizzolato M, Bates A, Fischi E, Thiran JP, Canales-Rodríguez EJ, Huang C, Zhu H, Zhong L, Cabeen R, Toga AW, Rheault F, Theaud G, Houde JC, Sidhu J, Chamberland M, Westin CF, Dyrby TB, Verma R, Rathi Y, Irfanoglu MO, Thomas C, Pierpaoli C, Descoteaux M, Anderson AW, Landman BA. Limits to anatomical accuracy of diffusion tractography using modern approaches. Neuroimage. 2019 Jan 15;185:1-11
13. Jeurissen B, Leemans A, Tournier JD, Jones DK, Sijbers J. Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging. Hum Brain Mapp. 2013 Nov;34(11):2747-66.
14. Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage. 2012 Jul 16;61(4):1000-16.
15. Vos SB, Jones DK, Viergever MA, Leemans A. Partial volume effect as a hidden covariate in DTI analyses. Neuroimage. 2011 Apr 15;55(4):1566-76.
16. Novikov DS, Kiselev VG, Jespersen SN. On modeling. Magn Reson Med. 2018 Jun;79(6):3172-3193.
17. Yang W, Xiong Y, Ye H, Chen B. Investigating Hippocampal Microstructural Differences in Temporal Lobe Epilepsy Patients with Cognitive Impairment Using NODDI. Proc Int Soc Magn Reson Med. 2025.
18. Iglesias JE, Augustinack JC, Nguyen K, Player CM, Player A, Wright M, Roy N, Frosch MP, McKee AC, Wald LL, Fischl B, Van Leemput K; Alzheimer's Disease Neuroimaging Initiative. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI. Neuroimage. 2015 Jul 15;115:117-37.
19. Wisse LE, Biessels GJ, Geerlings MI. A Critical Appraisal of the Hippocampal Subfield Segmentation Package in FreeSurfer. Front Aging Neurosci. 2014 Sep 25;6:261.
20. Wisse LEM, Daugherty AM, Olsen RK, Berron D, Carr VA, Stark CEL, Amaral RSC, Amunts K, Augustinack JC, Bender AR, Bernstein JD, Boccardi M, Bocchetta M, Burggren A, Chakravarty MM, Chupin M, Ekstrom A, de Flores R, Insausti R, Kanel P, Kedo O, Kennedy KM, Kerchner GA, LaRocque KF, Liu X, Maass A, Malykhin N, Mueller SG, Ofen N, Palombo DJ, Parekh MB, Pluta JB, Pruessner JC, Raz N, Rodrigue KM, Schoemaker D, Shafer AT, Steve TA, Suthana N, Wang L, Winterburn JL, Yassa MA, Yushkevich PA, la Joie R; Hippocampal Subfields Group. A harmonized segmentation protocol for hippocampal and parahippocampal subregions: Why do we need one and what are the key goals? Hippocampus. 2017 Jan;27(1):3-11.
21. Yushkevich PA, Pluta JB, Wang H, Xie L, Ding SL, Gertje EC, Mancuso L, Kliot D, Das SR, Wolk DA. Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment. Hum Brain Mapp. 2015 Jan;36(1):258-87.
22. Colgan N, Siow B, O'Callaghan JM, Harrison IF, Wells JA, Holmes HE, Ismail O, Richardson S, Alexander DC, Collins EC, Fisher EM, Johnson R, Schwarz AJ, Ahmed Z, O'Neill MJ, Murray TK, Zhang H, Lythgoe MF. Application of neurite orientation dispersion and density imaging (NODDI) to a tau pathology model of Alzheimer's disease. Neuroimage. 2016 Jan 15;125:739-744.
23. Mueller SG, Schuff N, Yaffe K, Madison C, Miller B, Weiner MW. Hippocampal atrophy patterns in mild cognitive impairment and Alzheimer’s disease. Hum Brain Mapp. 2010;31(9):1339-1347. doi:10.1002/hbm.20934
24. Yassa MA, Muftuler LT, Stark CE. Ultrahigh-resolution microstructural diffusion tensor imaging reveals perforant path degradation in aged humans in vivo. Proc Natl Acad Sci U S A. 2010;107(28):12687-12691.
25. Parker DM, Adams JN, Kim S, McMillan L, Yassa MA. NODDI-derived measures of microstructural integrity in medial temporal lobe white matter pathways are associated with Alzheimer’s disease pathology and cognition. Imaging Neuroscience. 2025.
26. Lavrova A, Pham NTT, Reid RI, Boeve BF, Knopman DS, Petersen RC, Nguyen AT, Reichard RR, Dickson DW, Jack CR Jr, Whitwell JL, Josephs KA. Relation of Alzheimer’s disease-related TDP-43 proteinopathy to metrics from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). Neurobiol Aging. 2025;150:97-108.
27. Hodgetts CJ, Postans M, Williams AN, Graham KS, Lawrence AD. Fornix subdivisions and spatial learning: a diffusion MRI study. Neuropsychologia.2025;222:109350.
28. Daducci A, Canales-Rodríguez EJ, Zhang H, Dyrby TB, Alexander DC, Thiran JP. Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data. Neuroimage. 2015 Jan 15;105:32-44.
29. Tournier JD, Smith R, Raffelt D, Tabbara R, Dhollander T, Pietsch M, Christiaens D, Jeurissen B, Yeh CH, Connelly A. MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. Neuroimage. 2019 Nov 15;202:116137.
30. Lampinen B, Szczepankiewicz F, Novén M, van Westen D, Hansson O, Englund E, Mårtensson J, Westin CF, Nilsson M. Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling. Hum Brain Mapp. 2019 Jun 1;40(8):2529-2545.
31. Berron D, Schütze H, Maass A, Cardenas-Blanco A, Kuijf HJ, Kumaran D, Düzel E. Strong Evidence for Pattern Separation in Human Dentate Gyrus. J Neurosci. 2016 Jul 20;36(29):7569-79.
32. Seyedmirzaei H, Nabizadeh F, Arabi MH, Pini L. Neurite Orientation Dispersion and Density Imaging in Multiple Sclerosis: A Systematic Review. Mult Scler Relat Disord. 2024.
33. La Joie R, Visani AV, Baker SL, Brown JA, Bourakova V, Cha J, Chaudhary K, Edwards L, Iaccarino L, Janabi M, Lesman-Segev OH, Miller ZA, Perry DC, O'Neil JP, Pham J, Rojas JC, Rosen HJ, Seeley WW, Tsai RM, Miller BL, Jagust WJ, Rabinovici GD. Prospective longitudinal atrophy in Alzheimer's disease correlates with the intensity and topography of baseline tau-PET. Sci Transl Med. 2020 Jan 1;12(524):eaau5732.
34. Palombo M, Ianus A, Guerreri M, Nunes D, Alexander DC, Shemesh N, Zhang H. SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. NeuroImage. 2020;215:116835.
35. Kamiya K, Hori M, Aoki S. NODDI in clinical research. J Neurosci Methods. 2020;346:108908.