Comparison of Region-of-Interest Delineation Methods for Diffusion Tensor Imaging in Patients with Cervical Spondylotic Radiculopathy

Comparison of Region-of-Interest Delineation Methods for Diffusion Tensor Imaging in Patients with Cervical Spondylotic Radiculopathy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparison of Region-of-Interest Delineation Methods for Diffusion Tensor Imaging in Patients with Cervical Spondylotic Radiculopathy Penghuan Wu, Chengyan Huang, Benchao Shi, Anmin Jin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1023507/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Diffusion tensor imaging is a promising technique for determining the responsible lesion of cervical radiculopathy, but the selection and delineation of the region of interest (ROI) affects the results. To explore the impact of different ROI sketching methods on the repeatability and consistency of DTI measurement values in patients with cervical spondylotic radiculopathy (CSR). Methods This was a retrospective study that included CSR patients who underwent DTI imaging. The images were analyzed independently by two radiologists. Four delineation methods were used: free-hand method, maximum roundness, quadrilateral method, and multi-point averaging method. They re-examined the images 6 weeks later. To investigate the consistency between the two measurements and the reproducibility between two radiologists, the intra-class correlation coefficient (ICC) was used. Results A total of 42 CSR patients were enrolled in this study. The distribution of compressed nerve roots was five C4, eight C5, sixteen C6, eleven C7, and two C8. No difference was found among the four methods in fractional anisotropy (FA) or apparent diffusion coefficient (ADC), irrespective of radiologists. (all P>0.05). Similar results were observed between the first and second measurements (all P>0.05), but some significant differences were observed for radiologist 2 for the four-small rounds method (P=0.033). Between the two measurements and the two radiologists, the free-hand and single largest circle methods were the two methods with the highest ICC (all ICC >0.90). Conclusion For the delineation of DTI ROI in patients with CSR, the free-hand and single largest circle methods were the most consistent methods. Orthopedics diffusion tensor imaging cervical radiculopathy imaging parameters Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Cervical radicular pain is an impingement of cervical spinal nerve and/or nerve root typically characterized by unilateral shooting electric pain in the upper limb, and, if radiculopathy, sensory, motor, and/or reflex deficits; nonspecific symptoms include neck pain etc. [ 1 – 3 ]. When neurological symptoms appear or if conservative treatment is ineffective, neurodecompression surgery has to be performed in time [ 4 , 5 ]. Patients with cervical nerve root radiation pain often encounter the following problems during management. First, preoperative imaging findings are inconsistent with the symptoms and signs [ 6 ]. Second, because of multi-segment cervical disc herniation or spinal canal stenosis, the exact responsible segment cannot be determined [ 7 ]. Third, even though electrophysiological tests are widely used, it is difficult to distinguish the responsible lesion from other cervical peripheral nerve injury diseases (such as ulnar neuritis, cubital tunnel syndrome, carpal tunnel syndrome, etc.) and shoulder joint-related diseases. With the continuous development of minimally invasive spine surgery, how to accurately identify the responsible lesion, accurately judge the responsible segment and location, and achieve accurate diagnosis and treatment are challenges and for spinal surgeons. At present, clinical routine computed tomography (CT) and magnetic resonance imaging (MRI) examinations can reveal the location of cervical disc herniation and fibrous bone canal stenosis, thereby indirectly determining whether the nerve is compressed and injured, but cannot provide direct evidence of nerve root injury [ 8 – 10 ]. In addition, in order to better judge the responsible segment, imaging can be assisted by neuroelectrophysiological examination and nerve root block. Nevertheless, these examinations are invasive, and their specificity and sensitivity are open to question [ 11 ], and their clinical application is limited due to the risk of complications [ 12 ]. Therefore, there is an urgent need for a non-invasive, accurate, and operable examination methods that could qualitatively and quantitatively reflect the degree and location of nerve root injury. Diffusion tensor imaging (DTI) is a diffusion-weighted imaging (DWI) sequence based on multiple b-values and can quantitatively analyze the diffusion of water molecules in living tissues [ 13 ]. The main parameters include fractional anisotropy (FA) and apparent diffusion coefficient (ADC). Since the movement of water molecules in the nerve tissue is along the nerve fibers with anisotropic dispersion, the DTI technique can be used in theory to better evaluate the pathological changes of nerve roots [ 14 ] and quantify the changes [ 15 ]. DTI has been widely used for the diagnosis of central nervous system diseases [ 16 ]. Chen et al. [ 17 ] reported that DTI could potentially be used to assess the microstructural abnormalities in the cervical nerve roots in patients with disc herniation. The study of the cervical nerve root system by the DTI technique is still in the initial stage. The one of most challenging aspect is the proper selection and delineation of the region of interest (ROI) [ 18 , 19 ]. Indeed, the ROI size has a considerable influence on tumors’ ADC values [ 20 , 21 ]. Therefore, this study aimed to explore the impact of different ROI sketching methods on the repeatability and consistency of DTI measurement values in patients with cervical spondylotic radiculopathy. The results could help develop the appropriate method and lay an objective and solid theoretical foundation for subsequent studies. Methods Study design and patients This was a retrospective study that included CSR patients who underwent imaging from May 2016 to May 2018 at the Department of Spine Surgery, Zhujiang Hospital of Southern Medical University. The diagnostic criteria of cervical spondylotic radiculopathy were typical root symptoms (arm numbness or pain), the area of which was consistent with the area of a cervical spinal nerve, and the brachial plexus tension test or foraminal compression test was positive [ 2 ]. In all the patients, the location of symptoms (e.g., dermatomal pain or neurological deficit) matched the evaluated nerve root on the DTI images. This study was approved by the Institutional Review Board of Zhujiang Hospital of South Medical University (Guangzhou, China). The need for individual consent was waived by the committee because of the retrospective nature of the study. The inclusion criteria were: 1) diagnosis of cervical spondylotic radiculopathy, as above; 2) symptoms and signs of unilateral cervical nerve root compression; and 3) radiological clues of single-level, unilateral posterolateral protrusion into the intervertebral foramen of the intervertebral disc. The exclusion criteria were: 1) a previous history of spinal trauma or surgery; 2) a history of neurological disease; 3) a history of chronic infection; or 4) a history of claustrophobia or any psychological problems. DTI procedure All included patients underwent DTI in the supine position using a 3-T scanner (Ingenia, Philips, The Netherlands) with a 6-channel head and neck coil. The coil was positioned at the center of the mandible, and the scanning interval was between C2 and T1. The DTI scan was at the axial position before the sagittal and coronal planes constructed. Two radiologists (6 and 5.5 years of experience in spine MRI) supervised the imaging. The imaging parameters were: b value, 0 and 800 s/mm 2 ; directions, 32; TR/TE, 4500/67 ms; orientation, axial; slice thickness/gap, 2/1 mm; FOV, 224×224 mm 2 ; actual voxel size, 2.5×2.9×2 mm 3 ; total slices, 30; and scan time, 9 min 49 s. Axial T2-weighted anatomical images were also obtained using the T2 turbo-spin-echo (TSE) sequence: variable flip angle radiofrequency excitations; TR/TE, 2500/110 ms; FOV, 155×155 mm; and section thickness/ga,p 15/1.2 mm. A typical case was shown in Figure 1 A-B. Image processing and analysis The DTI images were transferred to the EWS4.1 workstation and measured by two radiologists (6 and 5.5 years of experience in spine MRI) independently using the Philips post-processing software (Figure 1 C). To determine the level of entrance to the intervertebral foramen, an anatomic fusion of DTI and T2WI-weighted images was performed for the intersection of the attachment of the medial edge of the affected superior pedicle to the inferior pedicle and the nerve root (Figure 1 D). The ROI was set on the B0 images. The FA and ADC values were measured as follows: B=800 image high signal area, fusing 3D-FFE image to assist localization and sketched four ROIs at the level of entrance to the intervertebral foramen. Four delineation methods were used: 1) free-hand method (Figure 2 A): manually tracing the ROI along the nerve root contour to avoid cerebrospinal fluid interference; 2) maximum roundness (Figure 2 B): the round ROI was drawn as large as possible, tangential to the edge of the nerve root, covering the maximum nerve root area and not exceeding the edge; 3) quadrilateral method (Figure 2 C): the longest axis of the nerve root section area is first drawn, followed by the vertical axis, and then the endpoints of the two axes are connected clockwise to form a quadrilateral; and 4) the multi-point averaging method (Figure 2 D): the above two axes above divide the nerve roots into four quadrants, the largest circle is drawn in each quadrant, the average value of the four circles is taken as the measured value of DTI. The corresponding cervical 4-8 nerve root reconstructions were generated. Six weeks later, the two radiologists repeated the measurements. The size of the free-hand method ROIs was 34.7±12.48 mm 2 , maximum roundness was 34.2±11.25mm 2 , quadrilateral method was 33.9±10.8 mm 2 , and the multi-point averaging method was 33.6±13.4 mm 2 . Statistical analysis All analyses were performed using SPSS 25.0 (IBM, Armonk, NY, USA). The continuous data were presented as means ± standard deviations (SD). The categorical data were presented as n (%). For the repeated measurements between the two radiologists, the comparisons were made using the paired t-test. For the overall differences among the four methods, one-way repeated measurement ANOVA was used, with the LSD. post hoc test. To investigate the consistency between the two measurements and the reproducibility between the two radiologists, the intra-class correlation coefficient (ICC) was used. The model of ICC was set as two-way random, which considers both rater and participant error. The ICC type was set as an absolute agreement. The R software (version 3.5.2) and ‘BlandAltmanLeh’ package were used to obtain the Bland-Altman plots. A P-value <0.05 was considered statistically significant (two-tailed). Results Baseline characteristics of the patients 56 patients were enrolled, and after screening, 42 patients were finally included. The exclusion reasons were: 6 patients, because the nerve root volume was too small, so the DTI image was not clear enough to accurately delineate the nerve root boundary; 5 patients, DTI and the T2 images showed poor fusion image quality; 3 patients,the scanning time was too long to tolerate, so the scanning was stopped, resulting in partial image loss. Their baseline characteristics were shown in Table 1 . Their age was 51.8±6.1 years (range: 37 to 65), and the sex ratio was 1:0.83 (male/female=23/19). The distribution of compressed nerve roots was five C4, eight C5, 16 C6, 11 C7, and two C8. Table 1 Clinical characteristics of the patients Parameters Mean ± SD / n (%) Age, years 51.8±6.1 Sex Male 23 (54.8%) Female 19 (45.2%) Compressed nerve root C4 5 (11.9%) C5 8 (19.1%) C6 16 (38.1%) C7 11 (26.2%) C8 2 (4.8%) SD: standard deviation. FA and ADC measurement results Table 2 shows the results of all FA and ADC measurements. As indicated, no significant difference was found among the four methods in FA or ADC, irrespective of radiologists. (all P>0.05). Similar results were observed between the first and second measurements (all P>0.05), but some significant differences were observed for radiologist 2 for the four-small rounds method (P=0.033). Table 2 FA and ADC results of the two technicians and two time points FA ADC Pre Post P ICC* Pre Post P ICC* Radiologist 1 Free hand 0.22±0.04 0.22±0.03 0.479 0.904 (0.829 to 0.947) 1.54±0.21 1.54±0.18 0.949 0.934 (0.880 to 0.964) The single largest round 0.22±0.03 0.22±0.03 0.623 0.975 (0.955 to 0.987) 1.56±0.15 1.56±0.15 0.121 0.984 (0.971 to 0.991) Single rectangle 0.21±0.03 0.21±0.03 0.916 0.892 (0.807 to 0.940) 1.56±0.16 1.57±0.15 0.572 0.920 (0.856 to 0.956) Four-small rounds 0.22±0.03 0.21±0.03 0.213 0.793 (0.648 to 0.883) 1.55±0.15 1.56±0.14 0.369 0.796 (0.652 to 0.885) P 0.955 0.942 0.941 0.847 Radiologist 2 Free hand 0.22±0.03 0.22±0.03 0.914 0.905 (0.829 to 0.948) 1.54±0.18 1.55±0.18 0.533 0.937 (0.886 to 0.966) The single largest round 0.22±0.03 0.22±0.03 0.781 0.916 (0.849 to 0.954) 1.56±0.15 1.56±0.14 0.709 0.960 (0.927 to 0.978) Single rectangle 0.21±0.03 0.22±0.03 0.215 0.671 (0.466 to 0.808) 1.57±0.16 1.55±0.16 0.133 0.866 (0.764 to 0.926) Four-small rounds 0.21±0.03 0.21±0.02 0.726 0.779 (0.624 to 0.875) 1.56±0.16 1.53±0.15 0.033 0.755 (0.580 to 0.862) P 0.867 0.930 0.882 0.737 FA: fractional anisotropy; ADC: apparent diffusion coefficient; ICC: intra-class correlation coefficient. *ICC analysis for both FA and ADC of different measurements were all significant (P<0.001). Within each radiologist, the ICC was used to investigate the consistency of the repeated measurements. As indicated in Table 2 , all results were positively significant (all P0.90). FA and ADC measurement consistency between two radiologists The ICC between the two radiologists was used to investigate the reproducibility of the measurements between investigators. As indicated in Table 3 , all results were significant (all P0.90). The Bland-Altman plots in Figures 3 and 4 also indicated similar results to the numeric statistics. The free-hand method had differences gathered around zero (mean of -0.010±0.105 to 0.001±0.016), fewer outliers (n=1-4), and well-distributed plots. The same was observed for the single largest round method (mean of -0.001±0.012 to -0.000±0.064; 2-3 outliers), compared with the other two methods. Table 3 ICC results between radiologists 1 and 2 FA ADC Radiologists 1 and 2 ICC P ICC P Measurement 1 Free hand 0.889 (0.804 to 0.939) <0.001 0.918 (0.853 to 0.955) <0.001 The single largest round 0.914 (0.846 to 0.953) <0.001 0.973 (0.950 to 0.985) <0.001 Single rectangle 0.839 (0.720 to 0.910) <0.001 0.817 (0.686 to 0.897) <0.001 Four-small rounds 0.832 (0.709 to 0.906) <0.001 0.872 (0.775 to 0.929) <0.001 Measurement 2 Free hand 0.858 (0.751 to 0.921) <0.001 0.833 (0.711 to 0.907) <0.001 The single largest round 0.926 (0.866 to 0.959) <0.001 0.904 (0.828 to 0.947) <0.001 Single rectangle 0.734 (0.559 to 0.847) <0.001 0.684 (0.484 to 0.817) <0.001 Four-small rounds 0.642 (0.421 to 0.791) <0.001 0.650 (0.432 to 0.796) <0.001 FA: fractional anisotropy; ADC: apparent diffusion coefficient; ICC: intra-class correlation coefficient. Discussion DTI is a promising technique for determining the responsible lesion of cervical radiculopathy [ 22 ], but the selection and delineation of the ROI influence the results [ 20 , 21 ]. Unlike normal nerve roots, diseased nerve roots are compressed in different directions, resulting in different degrees of edema inside the nerve root (nerve fibers), so the signals of the nerve root cross-section are heterogeneous. Different drawing methods cover different signal areas which may lead to different DTI values. Therefore, it is of clinical significance to discuss the ROI sketching method of diseased nerve roots. This study aimed to explore the impact of different ROI sketching methods on the repeatability and consistency of DTI measurement values in patients with cervical spondylotic radiculopathy. The results suggest that for the delineation of DTI ROI in patients with cervical spondylotic radiculopathy, the free-hand and single largest circle methods were the most consistent methods. In this study, we found that when measuring FA and ADC in patients with cervical spondylotic radiculopathy, intra- and interobserver variabilities were dependent upon the methods of ROI delineation. FA and ADC measurements obtained by the largest circle and the free-hand methods were more reproducible than those obtained from the rectangle or four small rounds measurements. Ma et al. [ 23 ] found that the ROI size had a considerable influence on the ADC measurements of PDACs and suggested that the largest round ROI yielded the best intra- and interobserver reproducibility. At the same time, Jafari-Khouzani et al. [ 24 ] believe that increasing the ROI size can reduce the variance of the FA and ADC values. This is consistent with our results. We think that a larger circle will yield high repeatability and consistency. Of course, the nerve root cross-section is mostly a circle. A round ROI covering the cross-sectional nerve area will include most of the pixels, leading to the highest homogeneity. Moreover, the maximum circular ROI is easier to operate in practice with less time and better controllability, which greatly reduces the measurement errors caused by the circle sketched beyond the actual boundary of the nerve root during the actual operation. Therefore, the ICCs are high. The ROIs area of the free-hand method is greater than the maximum roundness method, nevertheless, due to the time-consuming drawing process, the contour method requires the operator to continuously judge and identify the actual boundary of the nerve roots. Therefore, the result is greatly affected by the operator's subjective factors. The quadrilateral and four small circles ROI methods have high central variability and lower ICCs. It takes longer to include fewer pixels. Nogueira et al. [ 20 ] report that small ROIs show high ADC reproducibility in the DTI diagnosis of breast lesions. Inoue et al. [ 25 , 26 ] showed that the ROI shape has no marked influence on the ICC in endometrial carcinoma. These are contrary to our conclusions and may be due to the different nature of the subjects and lesions. Moreover, an important advantage of using the largest round ROIs is that its placement is much less time-consuming compared to having to delimit the whole slice. Lambregts et al. [ 18 ] and Ma et al. [ 23 ] showed that the ROI has a considerable influence on tumor DTI values. Sun et al. [ 27 ] showed that the ADC and FA values derived from outline ROIs are higher than those from round ROIs. Inconsistent with those previous studies, we found that there were no significant differences in the FA values and ADC values of the four methods, which may be related to the small sample size. Moreover, FA and ADC values may be correlated with age, sex, and BMI. The cross-sectional areas of the nerve roots included in the four methods were similar, that is, the number of axons did not differ significantly, so there was no significant difference in the measured values. The obtained FA measurements of four ROIs are lower than those reported in the previous literature [ 17 , 22 ], which may be because included patients had more severe root compression than the reported patients. In this present study, the mean FA values in entrapped nerve roots were lower than they were in intact nerve roots, indicating that diffusion in the tissue had become more isotropic because of edema, in which fluid is trapped in the tissue, creating an isotropic environment and a reduction in FA. Of course, there are limitations in this study. First, in order to obtain the typical diseased nerve root, we adopted very strict case inclusion criteria, leading to small sample size. Second, due to the limited sample size, we did not group the patients according to sex, age, body mass index, and other factors, and did not study the possible influence of different factors on the results. Therefore, in future studies, we will combine multiple centers to screen and include typical cases, and assess the influence of relevent factors on the results. Conclusions In conclusion, the results suggest that for the delineation of DTI ROI in patients with cervical spondylotic radiculopathy, the free-hand and single largest circle methods were the most consistent methods. The results provide a reliable and objective basis for the use of DTI in the diagnosis and treatment of cervical spondylotic radiculopathy. Abbreviations ROI: region of interest CSR: cervical spondylotic radiculopathy ICC: intra-class correlation coefficient FA: fractional anisotropy ADC: apparent diffusion coefficient CT: computed tomography MRI: magnetic resonance imaging DTI: Diffusion tensor imaging DWI: diffusion-weighted imaging SD: standard deviations Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Board of Zhujiang Hospital of South Medical University (Guangzhou, China), approval number 2019-20. The need for individual consent was waived by the committee because of the retrospective nature of the study. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the National Natural Science Foundation of China [grant number 31701048]; and Science and Technology project of Shao Guan, China [grant number 200807124532992]. Authors' contributions PHW contributed to acquisition of data, interpretation of data, and drafted the manuscript; CYH contributed to acquisition and analysis of data; BCS contributed to design, and critically revised the manuscript; AMJ contributed to conception, design, interpretation of data, and critically revised the manuscript; All authors read and approved the final manuscript. Acknowledgements Not applicable. References Childress MA, Becker BA. Nonoperative Management of Cervical Radiculopathy. Am Fam Physician. 2016;93:746-54. Bono CM, Ghiselli G, Gilbert TJ, Kreiner DS, Reitman C, Summers JT, et al. An evidence-based clinical guideline for the diagnosis and treatment of cervical radiculopathy from degenerative disorders. Spine J. 2011;11:64-72. 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Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 08 Feb, 2022 Reviews received at journal 21 Jan, 2022 Reviewers agreed at journal 10 Jan, 2022 Reviews received at journal 24 Dec, 2021 Reviewers agreed at journal 20 Dec, 2021 Reviewers agreed at journal 27 Nov, 2021 Reviewers invited by journal 19 Nov, 2021 Editor assigned by journal 04 Nov, 2021 Editor invited by journal 01 Nov, 2021 Submission checks completed at journal 01 Nov, 2021 First submitted to journal 27 Oct, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1023507","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":60397788,"identity":"4bedaebe-66fd-4838-85ed-225c5cb602b5","order_by":0,"name":"Penghuan Wu","email":"","orcid":"","institution":"Shaoguan First People’s Hospital, Affiliated Shaoguan First People’s Hospital, Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Penghuan","middleName":"","lastName":"Wu","suffix":""},{"id":60397789,"identity":"2623ca0a-abe2-4b95-a1b2-5174372c6c5e","order_by":1,"name":"Chengyan Huang","email":"","orcid":"","institution":"Department of Radiology, Zhujiang Hospital, Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chengyan","middleName":"","lastName":"Huang","suffix":""},{"id":60397791,"identity":"47f513a7-4343-43b1-881b-eedd9f7e1eb3","order_by":2,"name":"Benchao Shi","email":"","orcid":"","institution":"Department of Spinal Surgery, Orthopedics Center, Zhujiang Hospital, Southern Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Benchao","middleName":"","lastName":"Shi","suffix":""},{"id":60397793,"identity":"2ceb8937-9662-4a5d-8d72-c14e5fae6998","order_by":3,"name":"Anmin Jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYBACxmYwJcHAz8zY+OCDgY0d8Vok25sPG84oSEsm3jqDM8fSpHk+HGJsIKSSuZ334OfCHIs8hhs5ZtI2BgeYGdgPH92A32F8ydIzt0kUM87IMbbOMbjDx8CTlnYDvxYeA2nebRKJzRI5hrdzDJ4xM0jwmBHSYvwbpKVNIsdA2sLgMGMDEVrMwLb08BxLkmYgVos1SMsMdmAg9xikJbMR8oth/xnj27zb6hL3HwZG5Y8/Nnb87IeP4dfSgC7Chk85CMgTUjAKRsEoGAWjgAEAn4lGKt80fFAAAAAASUVORK5CYII=","orcid":"","institution":"Department of Spinal Surgery, Orthopedics Center, Zhujiang Hospital, Southern Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Anmin","middleName":"","lastName":"Jin","suffix":""}],"badges":[],"createdAt":"2021-10-27 10:14:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1023507/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1023507/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":15158217,"identity":"81af5aea-400b-4497-9907-f3f007ab1596","added_by":"auto","created_at":"2021-11-02 18:21:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":606231,"visible":true,"origin":"","legend":"The patient was 45 years old, male, with left upper limb pain and numbness for 8 months. The cervical 5-6 disc was herniated and presented with numbness and pain in the left lateral forearm and left middle finger. (A) Cervical 5-6 disc herniation, sagittal plane. (B) Left intervertebral foramen stenosis, axial plane. (C) Diffusion-tensor imaging (DTI) positioned the injured nerve root at 5-6 cervical segments. (D) The measuring plane of regions of interest (ROI) was placed at the entrance to the intervertebral foramen, i.e., the intersection of the attachment of the medial edge of the affected superior pedicle to the inferior pedicle and the nerve root.","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1023507/v1/6950c0a851dd6d3fa8a5cd9c.png"},{"id":15157853,"identity":"4f1f73f3-5ace-4739-ac12-b0d5715703f3","added_by":"auto","created_at":"2021-11-02 18:18:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":503764,"visible":true,"origin":"","legend":"Four methods of region of interest (ROI) sketching. (A) The free hand method. (B) The maximum roundness method. (C) The quadrilateral method. (D) The multi-point averaging method.","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1023507/v1/b9b87aaa416e43d4c55ecf72.png"},{"id":15157850,"identity":"3054d5b4-4f79-4749-b5b1-2787ff5f9e28","added_by":"auto","created_at":"2021-11-02 18:18:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2080041,"visible":true,"origin":"","legend":"Bland-Altman plots of fractional anisotropy (FA) between the two technicians, including pre-measurements of free hand (A), the single largest round (B), single rectangle (C), four-small rounds (D); and post-measurements of free hand (E), the single largest round (F), single rectangle (G), four-small rounds (H).","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1023507/v1/37a4c0086e9dffbc78550951.png"},{"id":15158280,"identity":"dccca775-8fa6-4480-89ab-fc5eb0931f55","added_by":"auto","created_at":"2021-11-02 18:24:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2109863,"visible":true,"origin":"","legend":"Bland-Altman plots of apparent diffusion coefficient (ADC) between the two technicians, including pre-measurements of free hand (A), the single largest round (B), single rectangle (C), four-small rounds (D); and post-measurements of free hand (E), the single largest round (F), single rectangle (G), four-small rounds (H).","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-1023507/v1/c2796aa8f3af070344aadc45.png"},{"id":15158297,"identity":"2cb567d5-f8b5-44de-83ab-180bd6e9eafb","added_by":"auto","created_at":"2021-11-02 18:24:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1366296,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1023507/v1/d609bc0f-9b85-4f6c-915c-1ff8358ed359.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eComparison of Region-of-Interest Delineation Methods for Diffusion Tensor Imaging in Patients with Cervical Spondylotic Radiculopathy\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eCervical radicular pain is an impingement of cervical spinal nerve and/or nerve root typically characterized by unilateral shooting electric pain in the upper limb, and, if radiculopathy, sensory, motor, and/or reflex deficits; nonspecific symptoms include neck pain etc. [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. When neurological symptoms appear or if conservative treatment is ineffective, neurodecompression surgery has to be performed in time [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatients with cervical nerve root radiation pain often encounter the following problems during management. First, preoperative imaging findings are inconsistent with the symptoms and signs [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Second, because of multi-segment cervical disc herniation or spinal canal stenosis, the exact responsible segment cannot be determined [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Third, even though electrophysiological tests are widely used, it is difficult to distinguish the responsible lesion from other cervical peripheral nerve injury diseases (such as ulnar neuritis, cubital tunnel syndrome, carpal tunnel syndrome, etc.) and shoulder joint-related diseases. With the continuous development of minimally invasive spine surgery, how to accurately identify the responsible lesion, accurately judge the responsible segment and location, and achieve accurate diagnosis and treatment are challenges and for spinal surgeons.\u003c/p\u003e \u003cp\u003eAt present, clinical routine computed tomography (CT) and magnetic resonance imaging (MRI) examinations can reveal the location of cervical disc herniation and fibrous bone canal stenosis, thereby indirectly determining whether the nerve is compressed and injured, but cannot provide direct evidence of nerve root injury [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In addition, in order to better judge the responsible segment, imaging can be assisted by neuroelectrophysiological examination and nerve root block. Nevertheless, these examinations are invasive, and their specificity and sensitivity are open to question [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and their clinical application is limited due to the risk of complications [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Therefore, there is an urgent need for a non-invasive, accurate, and operable examination methods that could qualitatively and quantitatively reflect the degree and location of nerve root injury.\u003c/p\u003e \u003cp\u003eDiffusion tensor imaging (DTI) is a diffusion-weighted imaging (DWI) sequence based on multiple b-values and can quantitatively analyze the diffusion of water molecules in living tissues [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The main parameters include fractional anisotropy (FA) and apparent diffusion coefficient (ADC). Since the movement of water molecules in the nerve tissue is along the nerve fibers with anisotropic dispersion, the DTI technique can be used in theory to better evaluate the pathological changes of nerve roots [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and quantify the changes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. DTI has been widely used for the diagnosis of central nervous system diseases [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Chen et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] reported that DTI could potentially be used to assess the microstructural abnormalities in the cervical nerve roots in patients with disc herniation.\u003c/p\u003e \u003cp\u003eThe study of the cervical nerve root system by the DTI technique is still in the initial stage. The one of most challenging aspect is the proper selection and delineation of the region of interest (ROI) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Indeed, the ROI size has a considerable influence on tumors\u0026rsquo; ADC values [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Therefore, this study aimed to explore the impact of different ROI sketching methods on the repeatability and consistency of DTI measurement values in patients with cervical spondylotic radiculopathy. The results could help develop the appropriate method and lay an objective and solid theoretical foundation for subsequent studies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and patients\u003c/h2\u003e \u003cp\u003eThis was a retrospective study that included CSR patients who underwent imaging from May 2016 to May 2018 at the Department of Spine Surgery, Zhujiang Hospital of Southern Medical University. The diagnostic criteria of cervical spondylotic radiculopathy were typical root symptoms (arm numbness or pain), the area of which was consistent with the area of a cervical spinal nerve, and the brachial plexus tension test or foraminal compression test was positive [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In all the patients, the location of symptoms (e.g., dermatomal pain or neurological deficit) matched the evaluated nerve root on the DTI images. This study was approved by the Institutional Review Board of Zhujiang Hospital of South Medical University (Guangzhou, China). The need for individual consent was waived by the committee because of the retrospective nature of the study.\u003c/p\u003e \u003cp\u003eThe inclusion criteria were: 1) diagnosis of cervical spondylotic radiculopathy, as above; 2) symptoms and signs of unilateral cervical nerve root compression; and 3) radiological clues of single-level, unilateral posterolateral protrusion into the intervertebral foramen of the intervertebral disc. The exclusion criteria were: 1) a previous history of spinal trauma or surgery; 2) a history of neurological disease; 3) a history of chronic infection; or 4) a history of claustrophobia or any psychological problems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDTI procedure\u003c/h2\u003e \u003cp\u003eAll included patients underwent DTI in the supine position using a 3-T scanner (Ingenia, Philips, The Netherlands) with a 6-channel head and neck coil. The coil was positioned at the center of the mandible, and the scanning interval was between C2 and T1. The DTI scan was at the axial position before the sagittal and coronal planes constructed. Two radiologists (6 and 5.5 years of experience in spine MRI) supervised the imaging. The imaging parameters were: b value, 0 and 800 s/mm\u003csup\u003e2\u003c/sup\u003e; directions, 32; TR/TE, 4500/67 ms; orientation, axial; slice thickness/gap, 2/1 mm; FOV, 224\u0026times;224 mm\u003csup\u003e2\u003c/sup\u003e; actual voxel size, 2.5\u0026times;2.9\u0026times;2 mm\u003csup\u003e3\u003c/sup\u003e; total slices, 30; and scan time, 9 min 49 s. Axial T2-weighted anatomical images were also obtained using the T2 turbo-spin-echo (TSE) sequence: variable flip angle radiofrequency excitations; TR/TE, 2500/110 ms; FOV, 155\u0026times;155 mm; and section thickness/ga,p 15/1.2 mm. A typical case was shown in Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-B.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eImage processing and analysis\u003c/h2\u003e \u003cp\u003eThe DTI images were transferred to the EWS4.1 workstation and measured by two radiologists (6 and 5.5 years of experience in spine MRI) independently using the Philips post-processing software (Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). To determine the level of entrance to the intervertebral foramen, an anatomic fusion of DTI and T2WI-weighted images was performed for the intersection of the attachment of the medial edge of the affected superior pedicle to the inferior pedicle and the nerve root (Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). The ROI was set on the B0 images.\u003c/p\u003e \u003cp\u003eThe FA and ADC values were measured as follows: B=800 image high signal area, fusing 3D-FFE image to assist localization and sketched four ROIs at the level of entrance to the intervertebral foramen. Four delineation methods were used: 1) free-hand method (Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA): manually tracing the ROI along the nerve root contour to avoid cerebrospinal fluid interference; 2) maximum roundness (Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB): the round ROI was drawn as large as possible, tangential to the edge of the nerve root, covering the maximum nerve root area and not exceeding the edge; 3) quadrilateral method (Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC): the longest axis of the nerve root section area is first drawn, followed by the vertical axis, and then the endpoints of the two axes are connected clockwise to form a quadrilateral; and 4) the multi-point averaging method (Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD): the above two axes above divide the nerve roots into four quadrants, the largest circle is drawn in each quadrant, the average value of the four circles is taken as the measured value of DTI. The corresponding cervical 4-8 nerve root reconstructions were generated. Six weeks later, the two radiologists repeated the measurements. The size of the free-hand method ROIs was 34.7\u0026plusmn;12.48 mm\u003csup\u003e2\u003c/sup\u003e, maximum roundness was 34.2\u0026plusmn;11.25mm\u003csup\u003e2\u003c/sup\u003e, quadrilateral method was 33.9\u0026plusmn;10.8 mm\u003csup\u003e2\u003c/sup\u003e, and the multi-point averaging method was 33.6\u0026plusmn;13.4 mm\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll analyses were performed using SPSS 25.0 (IBM, Armonk, NY, USA). The continuous data were presented as means \u0026plusmn; standard deviations (SD). The categorical data were presented as n (%). For the repeated measurements between the two radiologists, the comparisons were made using the paired t-test. For the overall differences among the four methods, one-way repeated measurement ANOVA was used, with the LSD. post hoc test. To investigate the consistency between the two measurements and the reproducibility between the two radiologists, the intra-class correlation coefficient (ICC) was used. The model of ICC was set as two-way random, which considers both rater and participant error. The ICC type was set as an absolute agreement. The R software (version 3.5.2) and \u0026lsquo;BlandAltmanLeh\u0026rsquo; package were used to obtain the Bland-Altman plots. A P-value \u0026lt;0.05 was considered statistically significant (two-tailed).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics of the patients\u003c/h2\u003e \u003cp\u003e56 patients were enrolled, and after screening, 42 patients were finally included. The exclusion reasons were: 6 patients, because the nerve root volume was too small, so the DTI image was not clear enough to accurately delineate the nerve root boundary; 5 patients, DTI and the T2 images showed poor fusion image quality; 3 patients,the scanning time was too long to tolerate, so the scanning was stopped, resulting in partial image loss. Their baseline characteristics were shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Their age was 51.8\u0026plusmn;6.1 years (range: 37 to 65), and the sex ratio was 1:0.83 (male/female=23/19). The distribution of compressed nerve roots was five C4, eight C5, 16 C6, 11 C7, and two C8.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics of the patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean \u0026plusmn; SD / n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.8\u0026plusmn;6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (54.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (45.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompressed nerve root\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (38.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (26.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eSD: standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eFA and ADC measurement results\u003c/h2\u003e \u003cp\u003eTable \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the results of all FA and ADC measurements. As indicated, no significant difference was found among the four methods in FA or ADC, irrespective of radiologists. (all P\u0026gt;0.05). Similar results were observed between the first and second measurements (all P\u0026gt;0.05), but some significant differences were observed for radiologist 2 for the four-small rounds method (P=0.033).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFA and ADC results of the two technicians and two time points\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eFA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eADC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eICC*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eICC*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiologist 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree hand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u0026plusmn;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.904 (0.829 to 0.947)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.54\u0026plusmn;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.54\u0026plusmn;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.934 (0.880 to 0.964)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe single largest round\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.975 (0.955 to 0.987)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.56\u0026plusmn;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.56\u0026plusmn;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.984 (0.971 to 0.991)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle rectangle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.21\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.892 (0.807 to 0.940)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.56\u0026plusmn;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.57\u0026plusmn;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.920 (0.856 to 0.956)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFour-small rounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.793 (0.648 to 0.883)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.55\u0026plusmn;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.56\u0026plusmn;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.796 (0.652 to 0.885)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiologist 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree hand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.905 (0.829 to 0.948)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.54\u0026plusmn;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.55\u0026plusmn;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.937 (0.886 to 0.966)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe single largest round\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.916 (0.849 to 0.954)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.56\u0026plusmn;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.56\u0026plusmn;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.960 (0.927 to 0.978)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle rectangle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.21\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.671 (0.466 to 0.808)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.57\u0026plusmn;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.55\u0026plusmn;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.866 (0.764 to 0.926)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFour-small rounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.21\u0026plusmn;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u0026plusmn;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.779 (0.624 to 0.875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.56\u0026plusmn;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.53\u0026plusmn;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.755 (0.580 to 0.862)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eFA: fractional anisotropy; ADC: apparent diffusion coefficient; ICC: intra-class correlation coefficient. *ICC analysis for both FA and ADC of different measurements were all significant (P\u0026lt;0.001).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWithin each radiologist, the ICC was used to investigate the consistency of the repeated measurements. As indicated in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, all results were positively significant (all P\u0026lt;0.001), indicating high consistency. The free-hand and single largest circle were the two methods with the highest ICC (all ICC \u0026gt;0.90).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFA and ADC measurement consistency between two radiologists\u003c/h2\u003e \u003cp\u003eThe ICC between the two radiologists was used to investigate the reproducibility of the measurements between investigators. As indicated in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, all results were significant (all P\u0026lt;0.001), but the ICC for the free-hand and the single largest round methods were higher than for the two other methods (all ICC \u0026gt;0.90). The Bland-Altman plots in Figures \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e also indicated similar results to the numeric statistics. The free-hand method had differences gathered around zero (mean of -0.010\u0026plusmn;0.105 to 0.001\u0026plusmn;0.016), fewer outliers (n=1-4), and well-distributed plots. The same was observed for the single largest round method (mean of -0.001\u0026plusmn;0.012 to -0.000\u0026plusmn;0.064; 2-3 outliers), compared with the other two methods.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eICC results between radiologists 1 and 2\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eADC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiologists 1 and 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasurement 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree hand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.889 (0.804 to 0.939)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.918 (0.853 to 0.955)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe single largest round\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.914 (0.846 to 0.953)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.973 (0.950 to 0.985)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle rectangle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.839 (0.720 to 0.910)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.817 (0.686 to 0.897)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFour-small rounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.832 (0.709 to 0.906)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.872 (0.775 to 0.929)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasurement 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree hand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.858 (0.751 to 0.921)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.833 (0.711 to 0.907)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe single largest round\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.926 (0.866 to 0.959)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.904 (0.828 to 0.947)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle rectangle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.734 (0.559 to 0.847)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.684 (0.484 to 0.817)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFour-small rounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.642 (0.421 to 0.791)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.650 (0.432 to 0.796)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eFA: fractional anisotropy; ADC: apparent diffusion coefficient; ICC: intra-class correlation coefficient.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDTI is a promising technique for determining the responsible lesion of cervical radiculopathy [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], but the selection and delineation of the ROI influence the results [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Unlike normal nerve roots, diseased nerve roots are compressed in different directions, resulting in different degrees of edema inside the nerve root (nerve fibers), so the signals of the nerve root cross-section are heterogeneous. Different drawing methods cover different signal areas which may lead to different DTI values. Therefore, it is of clinical significance to discuss the ROI sketching method of diseased nerve roots.\u003c/p\u003e \u003cp\u003eThis study aimed to explore the impact of different ROI sketching methods on the repeatability and consistency of DTI measurement values in patients with cervical spondylotic radiculopathy. The results suggest that for the delineation of DTI ROI in patients with cervical spondylotic radiculopathy, the free-hand and single largest circle methods were the most consistent methods.\u003c/p\u003e \u003cp\u003eIn this study, we found that when measuring FA and ADC in patients with cervical spondylotic radiculopathy, intra- and interobserver variabilities were dependent upon the methods of ROI delineation. FA and ADC measurements obtained by the largest circle and the free-hand methods were more reproducible than those obtained from the rectangle or four small rounds measurements. Ma et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] found that the ROI size had a considerable influence on the ADC measurements of PDACs and suggested that the largest round ROI yielded the best intra- and interobserver reproducibility. At the same time, Jafari-Khouzani et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] believe that increasing the ROI size can reduce the variance of the FA and ADC values. This is consistent with our results. We think that a larger circle will yield high repeatability and consistency. Of course, the nerve root cross-section is mostly a circle. A round ROI covering the cross-sectional nerve area will include most of the pixels, leading to the highest homogeneity. Moreover, the maximum circular ROI is easier to operate in practice with less time and better controllability, which greatly reduces the measurement errors caused by the circle sketched beyond the actual boundary of the nerve root during the actual operation. Therefore, the ICCs are high. The ROIs area of the free-hand method is greater than the maximum roundness method, nevertheless, due to the time-consuming drawing process, the contour method requires the operator to continuously judge and identify the actual boundary of the nerve roots. Therefore, the result is greatly affected by the operator's subjective factors.\u003c/p\u003e \u003cp\u003eThe quadrilateral and four small circles ROI methods have high central variability and lower ICCs. It takes longer to include fewer pixels. Nogueira et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] report that small ROIs show high ADC reproducibility in the DTI diagnosis of breast lesions. Inoue et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] showed that the ROI shape has no marked influence on the ICC in endometrial carcinoma. These are contrary to our conclusions and may be due to the different nature of the subjects and lesions. Moreover, an important advantage of using the largest round ROIs is that its placement is much less time-consuming compared to having to delimit the whole slice. Lambregts et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and Ma et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] showed that the ROI has a considerable influence on tumor DTI values. Sun et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] showed that the ADC and FA values derived from outline ROIs are higher than those from round ROIs. Inconsistent with those previous studies, we found that there were no significant differences in the FA values and ADC values of the four methods, which may be related to the small sample size. Moreover, FA and ADC values may be correlated with age, sex, and BMI. The cross-sectional areas of the nerve roots included in the four methods were similar, that is, the number of axons did not differ significantly, so there was no significant difference in the measured values. The obtained FA measurements of four ROIs are lower than those reported in the previous literature [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which may be because included patients had more severe root compression than the reported patients. In this present study, the mean FA values in entrapped nerve roots were lower than they were in intact nerve roots, indicating that diffusion in the tissue had become more isotropic because of edema, in which fluid is trapped in the tissue, creating an isotropic environment and a reduction in FA.\u003c/p\u003e \u003cp\u003eOf course, there are limitations in this study. First, in order to obtain the typical diseased nerve root, we adopted very strict case inclusion criteria, leading to small sample size. Second, due to the limited sample size, we did not group the patients according to sex, age, body mass index, and other factors, and did not study the possible influence of different factors on the results. Therefore, in future studies, we will combine multiple centers to screen and include typical cases, and assess the influence of relevent factors on the results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, the results suggest that for the delineation of DTI ROI in patients with cervical spondylotic radiculopathy, the free-hand and single largest circle methods were the most consistent methods. The results provide a reliable and objective basis for the use of DTI in the diagnosis and treatment of cervical spondylotic radiculopathy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eROI: region of interest\u003c/p\u003e\n\u003cp\u003eCSR: cervical spondylotic radiculopathy\u003c/p\u003e\n\u003cp\u003eICC: intra-class correlation coefficient\u003c/p\u003e\n\u003cp\u003eFA: fractional anisotropy\u003c/p\u003e\n\u003cp\u003eADC: apparent diffusion coefficient\u003c/p\u003e\n\u003cp\u003eCT: computed tomography\u003c/p\u003e\n\u003cp\u003eMRI: magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eDTI: Diffusion tensor imaging\u003c/p\u003e\n\u003cp\u003eDWI: diffusion-weighted imaging\u003c/p\u003e\n\u003cp\u003eSD: standard deviations\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of Zhujiang Hospital of South Medical University (Guangzhou, China), approval number 2019-20. The need for individual consent was waived by the committee because of the retrospective nature of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China [grant number 31701048]; and Science and Technology project of Shao Guan, China [grant number 200807124532992].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePHW contributed to acquisition of data, interpretation of data, and drafted the manuscript; CYH contributed to acquisition and analysis of data; BCS contributed to design, and critically revised the manuscript; AMJ contributed to conception, design, interpretation of data, and critically revised the manuscript; All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChildress MA, Becker BA. 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Eur Radiol. 2011;21:2567-74.\u003c/li\u003e\n\u003cli\u003eMa X, Han X, Jiang W, Wang J, Zhang Z, Li G, et al. A Follow-up Study of Postoperative DCM Patients Using Diffusion MRI with DTI and NODDI. Spine (Phila Pa 1976). 2018;43:E898-e904.\u003c/li\u003e\n\u003cli\u003eNogueira L, Brand\u0026atilde;o S, Matos E, Nunes RG, Ferreira HA, Loureiro J, et al. Region of interest demarcation for quantification of the apparent diffusion coefficient in breast lesions and its interobserver variability. Diagn Interv Radiol. 2015;21:123-7.\u003c/li\u003e\n\u003cli\u003eHan X, Suo S, Sun Y, Zu J, Qu J, Zhou Y, et al. Apparent diffusion coefficient measurement in glioma: Influence of region-of-interest determination methods on apparent diffusion coefficient values, interobserver variability, time efficiency, and diagnostic ability. J Magn Reson Imaging. 2017;45:722-30.\u003c/li\u003e\n\u003cli\u003eLiang KN, Feng PY, Feng XR, Cheng H. Diffusion Tensor Imaging and Fiber Tractography Reveal Significant Microstructural Changes of Cervical Nerve Roots in Patients with Cervical Spondylotic Radiculopathy. World Neurosurg. 2019;126:e57-e64.\u003c/li\u003e\n\u003cli\u003eMa C, Guo X, Liu L, Zhan Q, Li J, Zhu C, et al. Effect of region of interest size on ADC measurements in pancreatic adenocarcinoma. Cancer Imaging. 2017;17:13.\u003c/li\u003e\n\u003cli\u003eJafari-Khouzani K, Paynabar K, Hajighasemi F, Rosen B. Effect of Region of Interest Size on the Repeatability of Quantitative Brain Imaging Biomarkers. IEEE Trans Biomed Eng. 2019;66:864-72.\u003c/li\u003e\n\u003cli\u003eInoue C, Fujii S, Kaneda S, Fukunaga T, Kaminou T, Kigawa J, et al. Apparent diffusion coefficient (ADC) measurement in endometrial carcinoma: effect of region of interest methods on ADC values. J Magn Reson Imaging. 2014;40:157-61.\u003c/li\u003e\n\u003cli\u003eInoue C, Fujii S, Kaneda S, Fukunaga T, Kaminou T, Kigawa J, et al. Correlation of apparent diffusion coefficient value with prognostic parameters of endometrioid carcinoma. J Magn Reson Imaging. 2015;41:213-9.\u003c/li\u003e\n\u003cli\u003eSun Y, Xiao Q, Hu F, Fu C, Jia H, Yan X, et al. Diffusion kurtosis imaging in the characterisation of rectal cancer: utilizing the most repeatable region-of-interest strategy for diffusion parameters on a 3T scanner. Eur Radiol. 2018;28:5211-20.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"diffusion tensor imaging, cervical radiculopathy, imaging parameters","lastPublishedDoi":"10.21203/rs.3.rs-1023507/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1023507/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDiffusion tensor imaging is a promising technique for determining the responsible lesion of cervical radiculopathy, but the selection and delineation of the region of interest (ROI) affects the results. To explore the impact of different ROI sketching methods on the repeatability and consistency of DTI measurement values in patients with cervical spondylotic radiculopathy (CSR).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis was a retrospective study that included CSR patients who underwent DTI imaging. The images were analyzed independently by two radiologists. Four delineation methods were used: free-hand method, maximum roundness, quadrilateral method, and multi-point averaging method. They re-examined the images 6 weeks later. To investigate the consistency between the two measurements and the reproducibility between two radiologists, the intra-class correlation coefficient (ICC) was used.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 42 CSR patients were enrolled in this study. The distribution of compressed nerve roots was five C4, eight C5, sixteen C6, eleven C7, and two C8. No difference was found among the four methods in fractional anisotropy (FA) or apparent diffusion coefficient (ADC), irrespective of radiologists. (all P\u0026gt;0.05). Similar results were observed between the first and second measurements (all P\u0026gt;0.05), but some significant differences were observed for radiologist 2 for the four-small rounds method (P=0.033). Between the two measurements and the two radiologists, the free-hand and single largest circle methods were the two methods with the highest ICC (all ICC \u0026gt;0.90).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eFor the delineation of DTI ROI in patients with CSR, the free-hand and single largest circle methods were the most consistent methods.\u003c/p\u003e","manuscriptTitle":"Comparison of Region-of-Interest Delineation Methods for Diffusion Tensor Imaging in Patients with Cervical Spondylotic Radiculopathy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-11-02 18:18:29","doi":"10.21203/rs.3.rs-1023507/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-02-09T04:57:46+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-01-21T12:09:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"a57893ff-8686-4a76-8d04-bb682e15218b","date":"2022-01-10T14:05:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-12-24T14:24:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4873bf6c-8b1e-47fc-8b33-14c5e81701ba","date":"2021-12-20T14:44:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1a520d04-a3a4-42ef-b917-d5a13780c726","date":"2021-11-27T23:10:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-11-20T02:20:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-11-04T10:17:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-11-01T05:28:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-11-01T05:15:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Musculoskeletal Disorders","date":"2021-10-27T10:09:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d80fa13c-0c50-49de-9c2b-222cd9ee1394","owner":[],"postedDate":"November 2nd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":8263908,"name":"Orthopedics"}],"tags":[],"updatedAt":"2022-07-06T10:29:13+00:00","versionOfRecord":[],"versionCreatedAt":"2021-11-02 18:18:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1023507","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1023507","identity":"rs-1023507","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}