Neurite orientation and dispersion density imaging: clinical utility, efficacy, and role in therapy

Figures & data

Table 1 NODDI findings in Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and epilepsy

	Target	Study population	Tesla	b-values	Directions	Main findings relevant to NODDI
Alzheimer’s disease
Slattery, et al 2017^Citation10	AD	37YOAD, 23HV	3	300, 700, 2000	8, 32, 64	Association with APOEε4 status.
						Regional ND was correlated with cognition.
Parker, et al 2018^Citation18	AD	38YOAD, 22HV	3	300, 700, 2000	8, 32, 64	OD↓, widely ND↓ in cortex
Fu, et al 2019^Citation19	AD, MCI	14AD, 14MCI, 14HV	3	1000, 2000	64 each	OD↓, widely ND↓. Better diagnosis than FA
Parkinson’s disease
Kamagata, et al 2016^Citation21	PD	58PD, 36HV	3	1000, 2000	32 each	ND↓ in SN and putamen. Correlation with severity.
Kamagata, et al 2017^Citation22	PD	30PD, 28HV	3	1000, 2000	32 each	ND↓ in gray matter. Better diagnostic value.
Andica, et al 2018^Citation23	PD	29PD, 29 HV	3	1000, 2000	32 each	ND↓ in nigrostriatal pathway.
Multiple sclerosis
Schneider, et al 2017^Citation25	MS	5MS, 5HV	3	300, 711, 2000	6, 15, 30	Greater specificity than DTI parameters.
Granberg, et al 2017^Citation27	MS	26MS, 24HV	3	1000, 5000	64, 128	ND↓ in cortical lesion. ND↓/OD↑ in white matter lesion.
By, et al 2017^Citation26	MS (spine)	6MS, 8HV	3	711, 2855	32, 64	ND↓ in lesion
Spano, et al 2018^Citation28	MS	20RRMS, 15SPMS, 20HV	3	711, 2855	30, 60	ND↓ and OD↑. SPMS showed more widespread abnormalities
De Santis et al 2019^Citation30	MS	7MS, 6HV	3, 7	700, 2000	27, 45	Specificity↑, Sensitivity↑ by NODDI. 7-T NODDI viable.
Mustafi, et al 2019^Citation29	MS	6MS	3	250, 1000, 2250, 4000, 6250	6, 21, 24, 30, 61	Microstructural alterations from normal-appearing white matter to perilesion areas and lesions
Epilepsy
Winston et al 2014^Citation31	FE	5FE	3	700, 2000	24, 48	ND↓ in focal lesion.
Lemkaddem, et al 2014^Citation35	TLE	22TLE, 21HV	3	Up to 6400	128 in total	Impaired connectivity.
Rostampour, et al 2018^Citation33	FE	17FE	3	700, 2000	30, 64	Abnormal OD in 8 patients.
Sone, et al 2018^Citation32	TLE	33TLE, 33HV	3	1000, 2000	32 each	ND↓ in focus side.
Sone, et al 2018^Citation36	IGE	141GE, 16HV	3	1000, 2000	16 each	OD↓ in mediofrontal area.

Figure 1 Sample images (A, T1-weighted; B, FLAIR; C, neurite density) of a 48-year-old patient with relapsing-remitting multiple sclerosis. Reduced neurite density can be seen in the demyelinating white matter lesions (arrows).

Figure 2 (A) In a 46-year-old patient with focal epilepsy, reduced neurite density is evident in the focal cortical dysplasia (circles). (B) A 17-year-old patient with tuberous sclerosis. Reduced neurite density can be seen in the multiple cortical tubers (arrows). (C) A 37-year-old patient with left temporal lobe epilepsy and hippocampal sclerosis. The abnormal hippocampus shows reduced neurite density and orientation dispersion (arrowheads). (D) A 47-year-old patient with right temporal lobe without any visible lesions on conventional MRI. The right temporal lobe shows reduced neurite density in accordance with the hypometabolic areas of ¹⁸F-FDG-PET (broken circles).

Table 2 NODDI findings in stroke, tumor, and trauma

	Target	Study population	Tesla	b-values	Directions	Main findings relevant to NODDI
Stroke
Adluru, et al 2014^Citation40	Stroke	2 strokes	3	500, 1000, 2000, 5000	20, 30, 64, 64	Specific marker for reconstruction in recovery
Hodgson, et al 2019^Citation41	Stroke	9 strokes, 9HV	3	Up to 4000	203 in total	More predictive of motor outcome.
Wang, et al 2019^Citation43	Stroke	71 strokes	3	1250, 2500	25 each	ND↑ OD↑. OD correlated with duration.
Mastropietro, et al 2019^Citation42	Stroke	17 strokes	3	700, 2000	20, 64	OD↑ in ipsilateral corticospinal tract.
Hara, et al 2019^Citation44	Moyamoya	33MMD, 20HV	3	700, 2850	30, 60	Correlation with PET and severity.
Tumor
Wen, et al 2015^Citation45	Glioma	20 gliomas, 5HV	7	1000, 2000	30, 60	Unique contrast reflecting microstructure.
Maximov, et al 2017^Citation46	Glioma	24 gliomas	3	1000, 2500	60 each	Effectively used as glioma grade biomarkers.
Figini, et al 2018^Citation47	Glioma	192 gliomas	3	700, 2000	20, 40	Correlation with isocitrate dehydrogenase status. No additional value to DTI.
Zhao, et al 2018^Citation48	Glioma	42 gliomas	3	1000, 2000	30 each	Highly valuable for glioma grading.
Kadota, et al 2018^Citation50	G B&Meta	9GB, 6Meta	3	1000, 2000	32 each	Extra cellular volume fraction ↑ in GB
Masjoodi, et al 2018^Citation49	Edema	12 tumors	3	1000, 2000	30, 64	ND had the best distinguishing normal tumoral and edematous areas
Trauma
Wu, et al 2018^Citation51	Mild TBI	19mTBI, 23Ctrl	3	250, 1000,2250,4000,6250	6, 21, 24, 30, 61	Only intra-axonal volume fraction showed significant group difference.
Churchill, et al 2017^Citation52	Concussion	31 concussion, 37Ctrl	3	700, 2000	30, 64	ND ↑ OD↓ in concussion.
Churchill, et al 2019^Citation53	Concussion	33concussion, 33Ctrl	3	700, 2000	30, 64	Intra-neurite water volume ↓, in both injury and recovery phases.

Table 3 NODDI findings in psychiatry and brain development

	Target	Study population	Tesla	b-values	Directions	Main findings relevant to NODDI
Psychiatry
Nazeri, et al 2017^Citation9	SC, BPAD	36SC, 29BPAD, 35HV	3	1000, 3000, 4500	30 each	ND↓ in SC. Intermediate findings in BPAD.
Rae, et al 2017^Citation54	FEP	35FEP, 10HV	1.5	300, 800, 2400	9, 30, 60	Correlation with spatial working memory. ND↓ in FEP. OD↑ along with aging in FEP.
Spray, et al 2018^Citation56	Hallucination	38HV	3	1000, 2000	60 each	OD correlated with hallucination proneness
Spray, et al 2018^Citation57	Hallucination	25 HV	3	1000, 2000	60 each	OD correlated with hallucination proneness
Ota, et al 2018^Citation58	MDD	23MDD, 26HV	3	1000, 2000	16 each	ND↓, OD↓ in MDD.
Ota, et al 2019^Citation59	BPAD	31 BPAD, 28HC	3	1000, 2000	16 each	ND↓, OD↓ in BPAD.
Sarrazin, et al 2019^Citation60	BPAD	41 BPAD, 40HV	3	200, 1500, 2700	30, 60, 60	ND↓ in BPAD without lithium than HV and BPAD with lithium.
Kraguljac, et al 2019^Citation55	SC	42SC, 42HV	3	600, 1000, 1400 1000	30, 30, 30 30	OD ↑ in SC. Correlation with drug response.
Brain development
Nazeri, et al 2015^Citation64	Healthy	45 HV	3	1000, 3000, 4500	30 each	Age-related changes of OD.
Dean, et al 2016^Citation61	Healthy	18HV(children)	3	700, 2000	30 each	Good indicator for brain myelination
Mah, et al 2017^Citation62	Healthy	27HV(children)	3	900, 2000	30 each	ND strongly correlated with age
Ota, et al 2017^Citation65	Healthy	23 HV	3	1000, 2000	16 each	ND correlated with age
Eaton-Rosen, et al 2015^Citation66	Preterm	12 preterm	3	750, 2000	16, 32	Region-dependent changes over preterm period
Murner-Lavanchy, et al 2018^Citation67	Very preterm	145 very preterm, 33 term-born	3	1200, 3000	25, 45	Axon density ↑, associated with semantic performance.
Karmacharya, et al 2018^Citation69	CHD	19CHD, 16HV	3	1000, 2000	30 each	ND↓ in neonates with CHD
Caverzasi, et al 2018^Citation70	DD	39DD, 56TD	3	700, 2000	30, 64	Correlation with age-related gyrification.
Geeraert, et al 2019^Citation63	Healthy	48HV(children)	3	900, 2000	30 each	Age-related ND↑
Young, et al 2019^Citation68	Very preterm	23 very preterm, 24 term-born	3	700, 1000, 2850	60 each	OD↑ in very preterm. ND correlated with IQ.

Table 4 NODDI findings in other brain diseases and spine

	Target	Study population	Tesla	b-values	Directions	Main findings relevant to NODDI
Others (brain)
Billiet, et al 2014^Citation82	NFI	17NFI	3	700, 1000,2800	25, 40, 75	ND↓ in unidentified bright objects in NFI
Timmers, et al 2015^Citation76	Galactosemia	8 galactosemia, 8HV	3	1000, 2000	64 each	ND↓. Correlation with behavioral outcome.
Kansagra, et al 2016^Citation83	Encephalopathy	25 encephalopathy	3	700, 2000	30, 55	More details of microstructural maturation
Suzuki, et al 2017^Citation78	Hypertension	2337HT, 2322non-HT	3	1000, 2000	100 in total	ND↓ in HT
Irie, et al 2017^Citation72	iNPH	19iNPH, 12HV	3	500, 1000, 1500,2000,2500	32 each	ND↓, OD↓ in corticospinal tract.
Kami/a, et al 2017^Citation73	iNPH	10iNPH, 14HV	3	500, 1000, 1500,2000,2500	32 each	Axon density ↓, unchanged after surgery.
Zhang, et al 2018^Citation74	HD	38pre-HD, 45HV	3	300, 700, 2000	8, 32, 64	Axon density ↓, correlation with progression.
Song, et al 2018^Citation75	WD	24WD, 25 HV	3	1000, 2000	30 each	ND↓, OD↓ in BG and thalamus.
Stotesbury, et al 2018^Citation79	Sickle cell anemia	46PT, 32Ctrl	3	1000, 2200	N/A	Correlation with processing speed.
Cabana, et al 2018^Citation84	SYNIQ555X	13 carriers, 13HV	3	300, 1000,2000	8, 32, 60	Alterations in language-related regions.
Sieurs, et al 2018^Citation86	Sarcoma survivor	34 sarcoma survivors, 34HV	3	700, 1000, 2800	25, 40, 75	NODDI abnormalities suggesting chemotherapy-related changes.
Broad, et al 2019^Citation71	ALS	23ALS, 23 HV	1.5	300, 800, 2400	9, 30, 60	ND↓ in corticospinal tract, etc.
Kimura et al 2019^Citation81	ME/CFS	20ME/CFS, 23 HV	3	1000, 2000	32 each	ND↓, OD↓↑ in ME/CFS
Dowell, et al 2019^Citation80	IFN-α fatigue	18 IFN-α treated PT	1.5	300, 800, 2400	8, 30, 60	ND↑ in IFN-α-induced fatigue
Xiong, et al 2019^Citation77	DM-MCI	20DM-MCI, 18DM-NC, 28HV	3	1250, 2500	25 each	ND↓ in DM-MCI
Wen, et al 2019^Citation85	C9orf72	38 carriers, 29HV	3	300, 700, 2200	9, 32, 60	ND↓ in 10 tracts.
Spine
Jiang, et al 2018^Citation89	CSM	57 postoperative CSM	3	1000, 2000	32 each	ND correlated with severity.
Ma, et al 2018^Citation90	CSM	58 postoperative CSM	3	1000, 2000	32 each	ND correlated with severity.
Okita, et al 2018^Citation91	CSM	27 pre/post CSM	3	500, 1000, 2000, 3000	6 each	Preoperative ND correlated with outcomes

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