scholarly journals Signal-to-noise assessment for diffusion tensor imaging with single data set and validation using a difference image method with data from a multicenter study

2014 ◽  
Vol 41 (9) ◽  
pp. 092302 ◽  
Author(s):  
Zhiyue J. Wang ◽  
Jonathan M. Chia ◽  
Shaheen Ahmed ◽  
Nancy K. Rollins
Keyword(s):  
Diffusion Tensor Imaging ◽  
Multicenter Study ◽  
Diffusion Tensor ◽  
Image Method ◽  
Signal To Noise ◽  
Data Set ◽  
Difference Image ◽  
Noise Assessment ◽  
Single Data

scholarly journals Signal-to-noise ratio assessment of muscle diffusion tensor imaging using single image set and validation by the difference image method

2019 ◽  
Vol 92 (1102) ◽  
pp. 20190133 ◽  
Author(s):  
Zhiyue J. Wang ◽  
Jin Yamamura ◽  
Sarah Keller
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Signal To Noise Ratio ◽  
Image Method ◽  
Single Image ◽  
Signal To Noise ◽  
Difference Image ◽  
Thigh Muscles ◽  
Image Set ◽  
The Difference

Objective: Signal-to-noise ratio (SNR) assessment is essential for accurate quantification of diffusion tensor imaging (DTI) metrics and usually requires the use of a difference image method using duplicate images. We aimed to estimate the SNR of DTI of thigh muscles using a single image set without duplicate images. Methods: DTI of one thigh were acquired on a 3 T scanner from 15 healthy adults, and scans with number of signal averages (NSA) = 4 and 8 were repeatedly acquired. SNR were evaluated for six thigh muscles. For SNR calculation from a single image set, diffusion-weighted images with similar diffusion encoding directions were grouped into pairs. The difference image of each pair was high-pass filtered in k-space to yield noise images. Noise images were also calculated with a difference method using two image sets as a reference. Subjects were divided into two groups for filter optimization and validation, respectively. The coefficient of repeatability (CR) of the SNR obtained from the two methods was also evaluated separately. Results: Bland–Altman analysis comparing the single image set method and the reference showed 95% limits of agreement of −9.2 to 9.2% for the optimization group and −12.5 to 12.6% for the validation group. The SNR measurement had a CR of 21.1% using the reference method, and 13.8% using the single image set method. Conclusion: The single image method can be used for DTI SNR assessment and offers better repeatability. Advances in knowledge: SNR of skeletal muscle DTI can be assessed for any data set without duplicate images.

Optic Radiation Fiber Tracking Using Anteriorly Angulated Diffusion Tensor Imaging: A Tested Algorithm for Quick Application

Neurosurgery ◽  
2011 ◽  
Vol 68 (5) ◽  
pp. 1239-1251 ◽  
Author(s):  
Lennart H. Stieglitz ◽  
Wolf O. Lüdemann ◽  
Mario Giordano ◽  
Andreas Raabe ◽  
Rudolf Fahlbusch ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Fiber Tracking ◽  
Minimal Length ◽  
Slice Thickness ◽  
Optic Radiation ◽  
Data Set ◽  
3 Dimensional ◽  
Optimal Setting ◽  
Optic Pathways

Abstract BACKGROUND: Fiber tracking (FT) of the optic pathways (OPs) is difficult because there is no standard for the parameters of diffusion tensor imaging (DTI), placement of seed volumes, or interpreting the results. OBJECTIVE: To determine optimal conditions and parameters for DTI and FT of the optic radiation under intraoperative conditions, we performed a multivariate prospective study. METHODS: A healthy man underwent magnetic resonance imaging and DTI scans using various scan parameters. The slice thicknesses were 2.7 mm, 5 mm, and 7 mm, and the gantry of the slices was 0 degrees and 44 degrees. The OPs were tracked using different settings for focal anisotropy and minimal length of the visualized fibers. The time needed for DTI, image processing, and uploading as well as the difficulty of depicting the OPs, the time needed for FT, quality, and volume of the tracked fiber object were registered and analyzed. RESULTS: The DTI took between 2 minutes 14 seconds for the axial scan with 7-mm slice thickness and 6 minutes 14 seconds for the 44-degree angulated scan with 2.7-mm slice thickness. Splitting the data into a 3-dimensional mosaic data set took between 1 minute 42 seconds (44 degrees, 7 mm; 0 degrees, 7 mm) and 4 minutes 21 seconds (44 degrees, 2.7 mm). The best results were achieved using 44-degree, 2.7-mm DTI. The optimal setting for focal anisotropy was 0.1 and 11 mm for minimal length. Using these parameters, tracking of the OPs was possible in 1 minute 22 seconds and with high quality and correlating with anatomic studies. CONCLUSION: The use of anteriorly angulated DTI improves the FT work flow and the results of tractography of the OP. The quality of the resulting objects can be judged by anatomic landmarks.

scholarly journals Signal to noise ratio and uncertainty in diffusion tensor imaging at 1.5, 3.0, and 7.0 Tesla

2011 ◽  
Vol 33 (6) ◽  
pp. 1456-1463 ◽  
Author(s):  
Daniel L. Polders ◽  
Alexander Leemans ◽  
Jeroen Hendrikse ◽  
Manus J. Donahue ◽  
Peter R. Luijten ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals MAGNETIC RESONANCE NEUROGRAPHY AND DIFFUSION TENSOR IMAGING

Neurosurgery ◽  
2009 ◽  
Vol 65 (suppl_4) ◽  
pp. A29-A43 ◽  
Author(s):  
Aaron Filler
Keyword(s):  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
The Body ◽  
Diagnostic Methods ◽  
Outcome Studies ◽  
Clinical Indication ◽  
Magnetic Resonance Neurography ◽  
Data Set ◽  
And Diffusion

Abstract OBJECTIVE Methods were invented that made it possible to image peripheral nerves in the body and to image neural tracts in the brain. The history, physical basis, and dyadic tensor concept underlying the methods are reviewed. Over a 15-year period, these techniques—magnetic resonance neurography (MRN) and diffusion tensor imaging—were deployed in the clinical and research community in more than 2500 published research reports and applied to approximately 50 000 patients. Within this group, approximately 5000 patients having MRN were carefully tracked on a prospective basis. METHODS A uniform Neurography imaging methodology was applied in the study group, and all images were reviewed and registered by referral source, clinical indication, efficacy of imaging, and quality. Various classes of image findings were identified and subjected to a variety of small targeted prospective outcome studies. Those findings demonstrated to be clinically significant were then tracked in the larger clinical volume data set. RESULTS MRN demonstrates mechanical distortion of nerves, hyperintensity consistent with nerve irritation, nerve swelling, discontinuity, relations of nerves to masses, and image features revealing distortion of nerves at entrapment points. These findings are often clinically relevant and warrant full consideration in the diagnostic process. They result in specific pathological diagnoses that are comparable to electrodiagnostic testing in clinical efficacy. A review of clinical outcome studies with diffusion tensor imaging also shows convincing utility. CONCLUSION MRN and diffusion tensor imaging neural tract imaging have been validated as indispensable clinical diagnostic methods that provide reliable anatomic pathological information. There is no alternative diagnostic method in many situations. With the elapsing of 15 years, tens of thousands of imaging studies, and thousands of publications, these methods should no longer be considered experimental.

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