Comparison of SS-EPI DWI and one-minute TGSE-BLADE DWI for diagnosis of acute infarction

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Total 104 patients with a past history of stroke or symptoms suspicious for acute infarction or who had undergone surgery for brain tumor within two days were prospectively enrolled. Ten lesions in 9 patients were diagnosed as acute or subacute infarction and were detectable only in TGSE-BLADE DWI but not in SS-EPI DWI. Scores for geometric distortion, susceptibility artifacts, overall image quality, lesion conspicuity and diagnostic confidence were lower for SS-EPI DWI than TGSE-BLADE DWI ( p ≤.001). Distortion was significantly worse in SS-EPI DWI than TGSE-BLADE DWI ( p <.001). SNR of centrum semiovale was significantly higher in SS-EPI DWI than TGSE-BLADE DWI ( p <0.001). One-minute TGSE-BLADE DWI showed better image quality than SS-EPI DWI in terms of distortion and artifacts, and higher diagnostic performance for acute infarctions. Health sciences/Anatomy/Nervous system Health sciences/Diseases/Neurological disorders/Cerebrovascular disorders Health sciences/Diseases/Neurological disorders/Stroke Diffusion-weighted imaging Single-shot echo-planar imaging TGSE-BLADE acute cerebral infarction stroke Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Diffusion-weighted magnetic resonance imaging (DWI) is the most important MR sequence for diagnosing acute stroke 1 , 2 . Single-shot echo-planar imaging (SS-EPI) is the most widely used DWI technique; however, EPI-based DWI techniques are prone to susceptibility artifacts where the magnetic field is inhomogeneous, such as near air–bone interfaces 3 . In contrast, two-dimensional (2D) turbo gradient- and spin-echo diffusion-weighted imaging with non-Cartesian BLADE trajectory (TGSE-BLADE DWI) is insensitive to B 0 -related artifacts, and thus has reduced geometric distortion and susceptibility artifacts 4 . Although several studies have reported the clinical usefulness of TGSE-BLADE DWI for cholesteatomas, orbital tumors, cerebellopontine angle tumors, sinonasal lesions, and aneurysm clips 5 – 10 , none has evaluated its use for acute stroke. TGSE-BLADE DWI features a multi-blade k-space filling strategy that has a shorter acquisition time compared to PROPELLER DWI, which is based on a turbo spin-echo sequence with non-Cartesian BLADE trajectory 11 – 13 . However, the acquisition time for TGSE-BLADE DWI has been reported to be as long as 4–5 minutes 4 – 10 , which has prevented its clinical application. To overcome this shortcoming, we used a slice acceleration technique termed simultaneous multi-slice (SMS) imaging in TGSE-BLADE DWI. SMS has been incorporated into both TSE and EPI sequences, and applied to most anatomical regions 14 – 17 . As SMS offers a substantial acceleration in data acquisition according to the number of slices excited simultaneously, it has emerged as a significant imaging technique 18 . In contrast to in-plane parallel imaging, SMS incurs only a minimal intrinsic signal-to-noise ratio penalty, allowing for full acceleration while maintaining a fixed echo time 19 . In addition, some SMS implementations have the potential to decrease radiofrequency (RF) power deposition 19 . MRI is a crucial diagnostic tool for cerebral infarction that enables early detection and prompt formulation and initiation of treatment, which are correlated with enhanced patient prognosis 20 , 21 . Therefore, reduction of scan time is clinically important for increasing the efficacy of patient care. We achieved a reduction in TGSE-BLADE DWI acquisition time to 1 minute by employing SMS. The aim of this study was to compare distortion, artifacts, and image quality between SS-EPI DWI and TGSE-BLADE DWI with SMS (1-min TGSE-BLADE DWI); and to evaluate the diagnostic performance of 1-min TGSE-BLADE DWI for acute or subacute infarction. Materials and Methods Participants This prospective study was performed in accordance with the Declaration of Helsinki and was approved by Kyoto University Graduate School and Faculty of Medicine, Ethics Committee. Written informed consent was obtained from all participants. We prospectively enrolled 104 patients with a past history of stroke or symptoms suspicious for acute infarction, or who underwent surgery for a brain tumor within two days, and who underwent SS-EPI DWI, TGSE-BLADE DWI, and T2-weighted imaging (T2WI) between November 2021 and March 2022. The exclusion criteria were as follows: (a) insufficient image quality due to motion artifacts; and (b) unavailability of any of SS-EPI DWI, TGSE-BLADE DWI, or T2WI. Image acquisition MRI was performed using a 3T scanner (MAGNETOM Prisma or MAGNETOM Skyra; Siemens Healthineers, Erlangen, Germany) with a 64-channel head/neck coil or a 32-channel head coil. T2WI of the brain was acquired in addition to the two DWI sequences (SS-EPI DWI and TGSE-BLADE DWI). SS-EPI DWI is a commercially available product that is used routinely in our institute. TGSE-BLADE DWI is a prototype sequence covering the whole brain, and a scan time of 59 s was achieved with a total acceleration factor of 4 (2 × in-plane acceleration and 2 × slice acceleration). The pulse sequence parameters are shown in Table 1 . Table 1 Acquisition protocols Parameter SS-EPI DWI TGSE-BLADE DWI T2WI b value (s/mm 2 ) 0, 1000 0, 1000 NA TR (ms) 3900 3300, 3200* 3540 TE (ms) 63, 71* 46, 62* 79 FA (degrees) NA 120 120 FOV (mm) 220 × 220 220 × 220 220 × 220 Matrix 160 × 160 160 × 160 448 × 448 Slice thickness (mm) 5 5 5 Number of slices 22 22 22 Voxel size (mm 3 ) 1.4 × 1.4 × 5.0 1.4 × 1.4 × 5.0 0.5 × 0.5 × 5.0 Bandwidth (Hz/pixel) 1202 520 189 NEX 2 1 1 Parallel imaging (Phase Encoding × Slice Encoding) GRAPPA 3 × 1 GRAPPA 2 × Slice acceleration 2 GRAPPA 3 × 1 Turbo factor NA 13 11 EPI factor 128 3 NA Acquisition time (s) 52 59 51 * Parameters are for MAGNETOM Skyra. Image analysis (a) Lesion assessment Three board-certified neuroradiologists (A.S., S.Ok., and S.Ot. with 16, 16, and 13 years of experience in neuroradiology, respectively) evaluated patients’ images for acute or subacute infarctions, defined as lesions with high signal intensities on b1000 images and without high values on ADC map. High signal intensities on b1000 images were diagnosed as infarction or artifact based on temporal changes and the findings of other MR sequences; e.g., fluid attenuated inversion recovery (FLAIR). In patients who underwent surgery, restricted diffusion due to postoperative changes on images acquired immediately after surgery was diagnosed as acute cerebral infarction or contusion. Any disagreements among the three neuroradiologists were resolved by consensus. (b) Image quality Geometric distortion, susceptibility artifacts, and overall image quality were assessed qualitatively in the b1000 images of all patients using a 4-point Likert scale 7 . In patients who had high signal intensities on b1000 images, lesion conspicuity and diagnostic confidence were qualitatively evaluated in b1000 images using a 4-point Likert scale 7 . In the case of multiple lesions, a comprehensive assessment was performed. The image assessment criteria are listed in Supplementary Table 1. Image quality was evaluated by the same three neuroradiologists who performed lesion assessment. Each reader was blinded to the type of DWI sequence. The majority opinion of the raters was designated as the final score. If the three opinions differed, a resolution was obtained by consensus. (c) Quantitative analysis Distortion was examined quantitatively by measuring the displacement between T2WI and each DWI sequence in three parts of the brain: frontal lobe near frontal sinus, temporal tip, and pons 9 . Regions-of-interest (ROIs) were placed on high-signal-intensity lesions, centrum semiovale (CSO), and the pons in the b1000 images of each DWI sequence. If multiple lesions were present, the ROI was placed in the slice that contained the greatest area of the largest lesion. In all patients, signal-to-noise ratio (SNR) was calculated as SNR = SI cso or pons / SD cso or pons 22 . SI cso or pons and SD cso or pons are the mean and standard deviation of signal intensities of CSO or pons. Contrast-to-noise ratio (CNR) was calculated as CNR = (SI lesion – SI cso ) / SD cso in patients with acute or subacute infarction 22 . SI lesion , SI cso , and SI pons are the mean signal intensities of lesions of acute or subacute infarction, CSO, and pons, respectively; and SD cso is the standard deviation of CSO. The same ROIs were then placed in the ADC maps of each DWI sequence. ROI area was 60–99 mm 2 in CSO and pons, and 4–69 mm 2 in lesions. Evaluation of distortion and ROI measurements was performed by a board-certified radiologist (S.Ok.) using ImageJ software version 1.53e ( https://imagej.nih.gov/ij/ ) and was approved by another board-certified radiologist (Y.F. with 25 years of experience in neuroradiology). SNR maps SNR maps were created using SS-EPI DWI and TGSE-BLADE DWI acquired in one healthy volunteer. Each DWI sequence was scanned 10 times, and an SNR map of each DWI was created as the mean map divided by the SD map, using Image Calculator in SPM12 ( https://www.fil.ion.ucl.ac.uk/spm/software/ ). Statistical analysis Interrater reliability for the image quality scores measured independently by the three radiologists was evaluated using Fleiss’ kappa statistics using RStudio Software version 2022.12.0 (RStudio PBC, Boston, USA) 23 . The calculated κ statistic was interpreted as follows: 0.20 or less, slight agreement; 0.21–0.40, fair agreement; 0.41–0.60, moderate agreement; 0.61–0.80, substantial agreement; and 0.81–1.00, almost perfect agreement. Lengths of displacement and image quality scores were compared between the two DWI sequences using Wilcoxon signed-rank test because the data distribution was not normal. SNR, CNR, and ADC values were compared between the two DWI sequences using paired t-tests because the data distribution was normal. p values less than 0.05 were considered statistically significant. The correlation coefficient was calculated to evaluate correlations of ADC values from the two DWI sequences, and Bland–Altman analysis was also performed. Statistical analyses were performed using MedCalc version 20 (MedCalc Software, Ostend, Belgium). Results Participants No participant was excluded from the study. In total, 104 patients were included (mean age, 67.1 ± 16.7; age range, 23–93 years; 64 males, 40 females) (Supplementary Fig. 1). Of 82 patients with a past history of stroke or symptoms suspicious for acute infarction, 37 had high signal intensities indicative of acute or subacute cerebral infarction. Forty-one patients had no high signal intensities on b1000 images, and 4 patients had a high signal intensity on b1000 images that also showed high signal on ADC maps. Twenty-two patients underwent surgery within two days and had high signal intensity lesions indicative of postoperative contusion or acute infarction on b1000 images. Table 2 lists the demographic data of all participants. Table 2 Patient demographics Characteristic Patients with a past history of stroke or symptoms suspicious for acute infarction Patients who underwent surgery for a brain tumor within two days (n=22) Patients without acute or subacute infarction (n=45) Patients with acute or subacute infarction (n=37) Sex (male:female) 27:18 25:12 12:10 Mean age ± SD (years) 68.0 ± 14.9 74.5 ± 11.3 53.0 ± 19.0 Neurological indication for MRI examination Old cerebral infarction (n=31) Subacute infarction without high signal intensity on b1000 images (n=6) Transient ischemic attack (n=2) Carotid artery stenosis (n=2) Amaurosis fugax (n=1) Old cerebral hemorrhage (n=1) Middle cerebral artery stenosis (n=1) Retinal artery occlusion (n=1) Acute or subacute infarction Day 1–5 (n=6) Day 6–10 (n=14) Day 11 (n=11) Onset date unknown (n=5) Subarachnoid hemorrhage, post aneurysm coiling (n=1) Postoperative day 1 of brain tumor Glioma (n=14) Brain metastasis (n=4) Meningioma (n=2) Acoustic schwannoma (n=1) Tuberculoma (n=1) Lesion assessment Ten lesions in 9 patients were diagnosed as acute/subacute infarction or postoperative contusion and were detectable on TGSE-BLADE DWI but not on SS-EPI DWI. Six of the 10 acute or subacute infarct lesions were in the cerebellar hemisphere, located near the cerebellar tentorium, frontal cortex, parietal cortex, putamen, and globus pallidus (Fig. 1 ). Four of the 10 acute infarct lesions or postoperative contusions were observed in patients immediately after surgery, and were difficult to find on SS-EPI DWI because of susceptibility artifacts due to air or hemorrhage (Fig. 2 ). No lesion was detectable on SS-EPI DWI but not on TGSE-BLADE DWI. Lesions visualized only on TGSE-BLADE DWI were verified by pixel-to-pixel comparison in FLAIR images obtained at the same time or in FLAIR images obtained at follow-up MRI. Image quality The kappa values of inter-rater agreement for the image quality scores of geometric distortion, susceptibility artifacts, overall image quality, lesion conspicuity, and diagnostic confidence were 0.67, 0.63, 0.69, 0.49, and 0.54, respectively, showing fair agreement or moderate agreement. Table 3 lists the image quality scores for each DWI sequence. Scores for geometric distortion, susceptibility artifacts, and overall image quality were lower in SS-EPI DWI than TGSE-BLADE DWI (all p < .001). Scores for lesion conspicuity and diagnostic confidence were lower in SS-EPI DWI than TGSE-BLADE DWI in patients with acute infarction and in patients immediately after surgery ( p ≤ .001 and p < .001, respectively). Table 3 Results of image quality for SS-EPI DWI and TGSE-BLADE DWI The scores of geometric distortion, susceptibility artifacts and overall image quality (n = 104) SS-EPI DWI 1-min TGSE-BLADE DWI p value Geometric distortion 3.0 (3.0–3.0) 4.0 (4.0–4.0) < .001 Susceptibility artifacts 3.0 (3.0–3.0) 4.0 (4.0–4.0) < .001 Overall image quality 3.0 (3.0–3.0) 4.0 (4.0–4.0) < .001 The scores of lesion conspicuity and diagnostic confidence in patients with acute or subacute infarctions (n = 37) SS-EPI DWI 1-min TGSE-BLADE DWI p value Lesion conspicuity 4.0 (3.1-4.0) 4.0 (4.0–4.0) .001 Diagnostic confidence 4.0 (3.0–4.0) 4.0 (4.0–4.0) < .001 The scores of lesion conspicuity and diagnostic confidence in patients who have undergone surgery for a brain tumor within a few days (n = 22) SS-EPI DWI 1-min TGSE-BLADE DWI p value Lesion conspicuity 3.0 (3.0–3.0) 4.0 (4.0–4.0) < .001 Diagnostic confidence 3.0 (3.0–3.0) 4.0 (4.0–4.0) < .001 Note – Data are presented as the median (interquartile range). Quantitative analysis Example images and the measured distortion values are shown in Fig. 3 . Distortion values were significantly higher in SS-EPI DWI than TGSE-BLADE DWI in frontal lobe, temporal tip, and pons ( p < .001). Mean SNR in CSO was significantly higher in SS-EPI DWI (26.3 ± 7.0) than TGSE-BLADE DWI (22.0 ± 5.5) ( p < .001), but showed no significant difference in pons (SS-EPI DWI, 9.7 ± 3.0; TGSE-BLADE DWI, 9.5 ± 1.8) ( p = .40). Mean SNR values were higher at the periphery and lower at the center of the brain in the SNR maps for both DWI sequences due to the characteristics of the 32-channel phased array coil (Fig. 4 ). Mean SNR in CSO was higher in SS-EPI DWI than TGSE-BLADE DWI; however, SNR in temporal lobe was higher in TGSE-BLADE DWI, probably because this sequence is less prone to susceptibility artifacts. Mean CNR was significantly higher in SS-EPI DWI (20.5 ± 12.1) than TGSE-BLADE DWI (15.5 ± 11.1) ( p < 0.001). Mean ADC values for each DWI are shown in Table 4 . There was no significant difference in ADC values in CSO or pons. In lesions, mean ADC values were significantly lower in SS-EPI DWI than TGSE-BLADE DWI ( p = .004). There was a linear correlation between SS-EPI DWI and TGSE-BLADE DWI for ADC values in lesions (r = 0.80) (Supplementary Fig. 2a). Bland–Altman analysis of the ADC measurements of SS-EPI DWI and TGSE-BLADE DWI revealed that most data were distributed between ± 1.96 SD (Supplementary Fig. 2b). Table 4 ADC values in centrum semiovale, pons, and lesions for SS-EPI DWI and TGSE-BLADE DWI SS-EPI DWI TGSE-BLADE DWI p value CSO 769.6 ± 81.8 764.8 ± 67.8 .37 Pons 761.2 ± 53.2 769.0 ± 98.1 .42 Lesions 592.9 ± 146.2 627.2 ± 124.2 .004 Note – Data are presented as the mean ± SD (mm 2 /s). CSO, centrum semiovale. Discussion The major findings of the present study are that some acute infarctions were detectable only by TGSE-BLADE DWI whereas no lesions were detectable only by SS-EPI DWI, and that scores for geometric distortion, susceptibility artifacts, overall image quality, lesion conspicuity, and diagnostic confidence were higher for TGSE-BLADE DWI. Taken together, these imaging image characteristics indicate the potential utility of TGSE-BLADE DWI with SMS for diagnosis of acute infarction. In previous studies with TGSE-BLADE DWI, scan time was consistently 4 to 5 minutes 4 – 9 . The present study reports the first attempt to significantly reduce acquisition time to approximately 1 minute. The ability to scan images within this shortened timeframe, coupled with enhanced diagnostic capabilities for acute cerebral infarction compared to SS-EPI DWI, renders it highly valuable for routine clinical application. Lesions that could not be identified after surgery as acute infarction on SS-EPI DWI were located near the cerebellar tentorium, cortex, hemorrhage, or pneumocephalus. A previous study has reported sensitivity of 81.1% and a false-negative rate of 5.6% for detecting infratentorial infarctions using 5 mm SS-EPI DWI, and lesions in false-negative cases were small 24 . Another study noted that most patients with false-negative lesions had infratentorial infarction or transient ischemic attack 25 . To mitigate false negatives, several reports have suggested that incorporating coronal sections or thin slice DWI can enhance diagnostic capabilities with SS-EPI DWI 26 , 27 . However, it might be possible to diagnose acute cerebral infarctions prone to false negatives using TGSE-BLADE DWI alone, and achieve diagnostic accuracy similar to that of additional imaging (such as coronal sections or thin slices) without acquiring additional scans. Median scores for geometric distortion and susceptibility artifacts were 3.0 for SS-EPI DWI and 4.0 for TGSE-BLADE DWI. Distortion was also quantitatively less near the air-bone interfaces (e.g., frontal lobe, temporal tip, and pons) in TGSE-BLADE-DWI with SMS. These findings align with those of a prior study that used TGSE-BLADE DWI without acceleration technique 9 . Their scores for lesion conspicuity and diagnostic confidence in patients with acute or subacute infarction were lower in SS-EPI DWI than TGSE-BLADE DWI; however, median score was 4.0 for each sequence. In contrast, median score in post-surgery patients was 3.0 for SS-EPI DWI and 4.0 for TGSE-BLADE DWI. We consider that there is greater susceptibility postoperatively to artifacts due to air or hemorrhage, in which case TGSE-BLADE DWI is more beneficial. SNR values were lower for TGSE-BLADE DWI than SS-EPI DWI in CSO. In SNR maps for temporal lobe, however, values were higher for TGSE-BLADE DWI than for SS-EPI DWI. TGSE-BLADE DWI showed less SNR degradation in areas prone to distortion, such as near air–bone interfaces, whereas SS-EPI DWI demonstrated superior SNR in other regions, primarily because only half of the signals are used in this sequence due to the non-CPMG (Carr-Purcell-Meiboom-Gill) problem. Another reason for the lower SNR values is that positioning the gradient echo with T2* decay effects at the center of k-space diminishes the image quality of TGSE-BLADE DWI 5 . Despite these disadvantages of 1-min TGSE-BLADE DWI, its ability to detect lesions located near susceptibility artifacts is a strong advantage. There was no significant difference between the sequences in terms of ADC values in CSO or pons. In lesions, however, ADC values were significantly higher for TGSE-BLADE DWI than SS-EPI DWI, consistent with the findings of a previous study 6 . This discrepancy might have been due to the substantial differences in SNR and T1 values between normal tissue and lesions 28 , but the cause remains unclear because no study has investigated cerebral infarction using TGSE-BLADE DWI. Furthermore, these differences might also have contributed to the lower CNR observed in TGSE-BLADE DWI. Whereas there was a strong correlation in ADC values for lesions between SS-EPI DWI and TGSE-BLADE DWI. Therefore, we consider that there should be few issues in clinical diagnosis. There are several limitations in this study. Firstly, the sample size was small. A larger sample size might facilitate a more comprehensive investigation of lesions that could not be visualized by SS-EPI DWI. However, we prospectively enrolled over 100 patients, and believe that the number of cases was sufficient to demonstrate the utility of TGSE-BLADE DWI. Second, subacute infarct was diagnosed most commonly, and there were relatively few hyperacute infarcts. Due to the prospective nature of the study in which two types of DWI were acquired, it was challenging to perform these imaging examinations in patients with hyperacute stroke who require urgent treatment decisions. A previous study reported that some lesions were not depicted on SS-EPI DWI in the hyperacute stage 29 , indicating the need for further investigation in the future. Third, SMS imaging was not applied for SS-EPI DWI because we compared TGSE-BLADE DWI with SS-EPI DWI acquired with the protocol used at our institution. Although it is feasible to implement SMS for SS-EPI DWI, there is limited advantage because the shorter TR used has the effect of reducing SNR. Finally, in making the score judgments, the neuroradiologists noted that it was easy to distinguish the SS-EPI DWI and TGSE-BLADE DWI sequences based on the presence or absence of signal pile-up and geometric distortion. Conclusion Compared with SS-EPI DWI, one-minute TGSE-BLADE DWI has better image quality in terms of distortion and artifacts, higher diagnostic performance for identifying acute infarctions, and its acquisition time is similar to that of SS-EPI DWI. One-minute TGSE-BLADE DWI is therefore clinically acceptable and shows promise as a diagnostic tool for identifying acute infarctions in acute stroke patients and postoperative patients. Declarations Author contributions Y.U., K.Z. and Y.A. conceived and designed the analysis. M.T., N.S., S.Ik and S.I. collected the data. T.M. and Y.A. contributed data or analysis tools. A.S. , S.Ot, S.Ok. and S.N. performed the analysis. S.Ok . and Y.F. wrote the main manuscript text. All authors reviewed the manuscript. Data availability statement The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Software and versions used in the study: ImageJ software version 1.53e (https://imagej.nih.gov/ij/), SPM12 (https://www.fil.ion.ucl.ac.uk/spm/software/), RStudio Software version 2022.12.0 (RStudio PBC, Boston, USA), and Medcalc version 20 (MedCalc Software). Funding This work was supported by JSPS KAKENHI Grant Numbers JP22K07746, JP24K18796, ISHIZUE 2023 of Kyoto University, and The Kyoto University Foundation. Competing interests N/A except Yuta Urushibata and Kun Zhou. Yuta Urushibata is an employee of Siemens Healthcare K. K., Japan. Kun Zhou is an employee of Siemens Shenzhen Magnetic Resonance Ltd., China Additional information Correspondence and requests for materials should be addressed to Y.F. References Drake-Pérez, M., Boto, J., Fitsiori, A., Lovblad, K. & Vargas, M. I. Clinical applications of diffusion weighted imaging in neuroradiology. Insights Imaging 9 , 535-547, doi:10.1007/s13244-018-0624-3 (2018). Nagaraja, N. 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J Med Imaging Radiat Oncol 60 , 616-623, doi:10.1111/1754-9485.12490 (2016). Sorimachi, T., Ito, Y., Morita, K. & Fujii, Y. Thin-section diffusion-weighted imaging of the infratentorium in patients with acute cerebral ischemia without apparent lesion on conventional diffusion-weighted imaging. Neurol Med Chir (Tokyo) 48 , 108-113, doi:10.2176/nmc.48.108 (2008). Baggett, M., Helmy, D., Chang, J., Bobinski, M. & Assadsangabi, R. Added value in stroke imaging: accuracy and utility of additional coronal diffusion-weighted imaging. Clin Radiol 76 , 785.e781-785.e787, doi:10.1016/j.crad.2021.07.006 (2021). Nakamura, H. et al. Effect of thin-section diffusion-weighted MR imaging on stroke diagnosis. AJNR Am J Neuroradiol 26 , 560-565 (2005). Mazaheri, Y. et al. Diffusion-weighted MRI of the prostate at 3.0 T: comparison of endorectal coil (ERC) MRI and phased-array coil (PAC) MRI-The impact of SNR on ADC measurement. Eur J Radiol 82 , e515-520, doi:10.1016/j.ejrad.2013.04.041 (2013). Oppenheim, C. et al. False-negative diffusion-weighted MR findings in acute ischemic stroke. AJNR Am J Neuroradiol 21 , 1434-1440 (2000). Additional Declarations Competing interest reported. Yuta Urushibata is an employee of Siemens Healthcare K. K., Japan. Kun Zhou is an employee of Siemens Shenzhen Magnetic Resonance Ltd., China. The other authors have no competing interests. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Published Journal Publication published 22 Feb, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 09 Oct, 2024 Reviews received at journal 06 Oct, 2024 Reviewers agreed at journal 22 Sep, 2024 Reviews received at journal 06 Aug, 2024 Reviewers agreed at journal 20 Jul, 2024 Reviewers invited by journal 18 May, 2024 Editor assigned by journal 14 May, 2024 Editor invited by journal 06 May, 2024 Submission checks completed at journal 06 May, 2024 First submitted to journal 02 May, 2024 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board 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-4361252","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":300849477,"identity":"4d12636e-289e-4835-864c-0129e02c8924","order_by":0,"name":"Sachi Okuchi","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Sachi","middleName":"","lastName":"Okuchi","suffix":""},{"id":300849478,"identity":"9b26ce87-20b4-4400-9702-a8f253bb89c3","order_by":1,"name":"Yasutaka Fushimi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIie3RsUoDMRjA8a8EMn1665VTzkdICVw3i2+S4+CmDjeVgw4eCDcFbm3BhxCEzgeFuKT6AB0cXN066mBiKa2YKx0F89+Sy48kFwCf7y9GWiDAAAMEaobi8FvrJlRsSV/uCD2JmJj+TdwxhXxTFIsLrnXyVkCeNvFdSxCuY+itnNsYkkQztsZkJYd8BuN0XlNhSDao4Fk4yatMCFryYixCmT4oHH4gELNcs86DWcKbPWFml9tjhEWWsDNpyXhHlp2kr+jkm4RaTcylcj6vc9G7Z0+DuuMu54o8bvBzPQpktoiKMrtsyLKF93IaB6H7j10dzto3vam2BzbvE2qXgLj6QQBG+2EgncTn8/n+XV+dwlTGOeV99wAAAABJRU5ErkJggg==","orcid":"","institution":"Kyoto University","correspondingAuthor":true,"prefix":"","firstName":"Yasutaka","middleName":"","lastName":"Fushimi","suffix":""},{"id":300849479,"identity":"4fb8ef6d-6546-4498-ae65-31a2b163b5e4","order_by":2,"name":"Akihiko Sakata","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Akihiko","middleName":"","lastName":"Sakata","suffix":""},{"id":300849480,"identity":"3620ea7f-dfb5-4136-ba1a-2ba7c70b7c49","order_by":3,"name":"Sayo Otani","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Sayo","middleName":"","lastName":"Otani","suffix":""},{"id":300849481,"identity":"f5391dd5-c76d-4941-acfd-9e6d22d42f80","order_by":4,"name":"Satoshi Nakajima","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Satoshi","middleName":"","lastName":"Nakajima","suffix":""},{"id":300849482,"identity":"b5cca3f8-25bf-4e89-8978-4b79505f9b74","order_by":5,"name":"Takakuni Maki","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Takakuni","middleName":"","lastName":"Maki","suffix":""},{"id":300849483,"identity":"3ce49546-5421-4cbc-b3db-be0e5b4afac4","order_by":6,"name":"Masahiro Tanji","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Masahiro","middleName":"","lastName":"Tanji","suffix":""},{"id":300849484,"identity":"fd3346e4-925b-4b69-a0ce-c54a92092530","order_by":7,"name":"Noritaka Sano","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Noritaka","middleName":"","lastName":"Sano","suffix":""},{"id":300849485,"identity":"48ea0c9e-187e-405c-8bd4-0a54a654d47f","order_by":8,"name":"Satoshi Ikeda","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Satoshi","middleName":"","lastName":"Ikeda","suffix":""},{"id":300849486,"identity":"70db4c5e-7c28-4a3e-9445-dea181bb9f8b","order_by":9,"name":"Shuichi Ito","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Shuichi","middleName":"","lastName":"Ito","suffix":""},{"id":300849487,"identity":"f6bfe609-b176-48ae-a842-c278c943c9bc","order_by":10,"name":"Yuta Urushibata","email":"","orcid":"","institution":"Siemens Healthineers (Japan)","correspondingAuthor":false,"prefix":"","firstName":"Yuta","middleName":"","lastName":"Urushibata","suffix":""},{"id":300849488,"identity":"3dfc4814-6963-45b8-90a4-c52d1ea742f4","order_by":11,"name":"Kun Zhou","email":"","orcid":"","institution":"Siemens Shenzhen Magnetic Resonance Ltd","correspondingAuthor":false,"prefix":"","firstName":"Kun","middleName":"","lastName":"Zhou","suffix":""},{"id":300849490,"identity":"52a8dc6f-41ab-4de3-8773-8bca3895b36f","order_by":12,"name":"Yoshiki Arakawa","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Yoshiki","middleName":"","lastName":"Arakawa","suffix":""},{"id":300849492,"identity":"840a2c74-3cba-4ccb-9bd5-f29ae67b0973","order_by":13,"name":"Yuji Nakamoto","email":"","orcid":"","institution":"Kyoto University","correspondingAuthor":false,"prefix":"","firstName":"Yuji","middleName":"","lastName":"Nakamoto","suffix":""}],"badges":[],"createdAt":"2024-05-02 23:55:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4361252/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4361252/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-90413-5","type":"published","date":"2025-02-22T15:57:13+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":56479174,"identity":"d4df11d4-7fdf-4889-97ba-3977e1ff0c55","added_by":"auto","created_at":"2024-05-14 17:59:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":127912,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative images in patients with acute or subacute infarction. The white arrows indicate infarctions in the cerebellar hemisphere near the cerebellar tentorium (a, b), left frontal cortex (c, d), right parietal lobe (e, f), left putamen (g, h), right globus pallidus (i, j), and right frontal cortex (k, l). SS-EPI DWI (a, c, e, g, i and k); TGSE-BLADE DWI (b, d, f, h, j and l). The lesions are detectable only on TGSE-BLADE DWI but are unclear on SS-EPI DWI due to proximity to cortex, cerebellar tentorium, or hemosiderin deposition in the basal ganglia.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4361252/v1/7b7e667d67c140c6e9bb0898.jpg"},{"id":56479173,"identity":"788e9a1e-6f10-4bd8-80ac-c638095723b6","added_by":"auto","created_at":"2024-05-14 17:59:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":87603,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative images obtained in patients who underwent surgery for brain tumor show postoperative changes related to acute cerebral infarction or postoperative contusion on postoperative day 1. It is difficult to determine whether the postoperative changes are due to acute cerebral infarction or to postoperative contusion (white arrows) and susceptibility artifact (arrowheads) in SS-EPI DWI (a, c, e, and g). Postoperative changes are clearly differentiated as acute cerebral infarction or postoperative contusion on TGSE-BLADE DWI (b, d, f, and h).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4361252/v1/252cd1f94c273b4ac168d954.jpg"},{"id":56479175,"identity":"b879558a-d65b-4846-ae9b-bbb0bddf6a79","added_by":"auto","created_at":"2024-05-14 17:59:05","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73941,"visible":true,"origin":"","legend":"\u003cp\u003eA 74-year-old male with acute infarctions in right basal ganglia and corona radiata. Values of distortion seen on SS-EPI DWI (a, c) and TGSE-BLADE DWI (b, d) are shown in boxplots (e–g) for the regions of frontal lobe near frontal sinus (e), temporal tip (f), and pons (g). In all three regions, distortion was less pronounced in TGSE-BLADE DWI than SS-EPI DWI.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4361252/v1/4ec54fabc3599bc987d1c0b9.jpg"},{"id":56479176,"identity":"6672c07b-6aac-4fe0-bb86-bf166e363864","added_by":"auto","created_at":"2024-05-14 17:59:05","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":133750,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative b1000 images (a, b) and SNR maps (c, d) of SS-EPI DWI (a, c) and TGSE-BLADE DWI (b, d) are shown in a healthy volunteer.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4361252/v1/15e0e540f39b59ee73900897.jpg"},{"id":77052517,"identity":"55f3d09c-02e6-4197-b74d-5806aef115b3","added_by":"auto","created_at":"2025-02-24 16:13:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1176406,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4361252/v1/8fd50286-d78c-4044-a94e-06ea17ebb004.pdf"},{"id":56479177,"identity":"5249e3b5-591d-437c-8f34-4ea405fc0ac2","added_by":"auto","created_at":"2024-05-14 17:59:05","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":602022,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-4361252/v1/f751aeaab2016102b84d6e4a.docx"}],"financialInterests":"Competing interest reported. Yuta Urushibata is an employee of Siemens Healthcare K. K., Japan.\nKun Zhou is an employee of Siemens Shenzhen Magnetic Resonance Ltd., China.\nThe other authors have no competing interests.","formattedTitle":"Comparison of SS-EPI DWI and one-minute TGSE-BLADE DWI for diagnosis of acute infarction","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiffusion-weighted magnetic resonance imaging (DWI) is the most important MR sequence for diagnosing acute stroke\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Single-shot echo-planar imaging (SS-EPI) is the most widely used DWI technique; however, EPI-based DWI techniques are prone to susceptibility artifacts where the magnetic field is inhomogeneous, such as near air\u0026ndash;bone interfaces\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In contrast, two-dimensional (2D) turbo gradient- and spin-echo diffusion-weighted imaging with non-Cartesian BLADE trajectory (TGSE-BLADE DWI) is insensitive to B\u003csub\u003e0\u003c/sub\u003e-related artifacts, and thus has reduced geometric distortion and susceptibility artifacts\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Although several studies have reported the clinical usefulness of TGSE-BLADE DWI for cholesteatomas, orbital tumors, cerebellopontine angle tumors, sinonasal lesions, and aneurysm clips\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, none has evaluated its use for acute stroke. TGSE-BLADE DWI features a multi-blade k-space filling strategy that has a shorter acquisition time compared to PROPELLER DWI, which is based on a turbo spin-echo sequence with non-Cartesian BLADE trajectory\u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, the acquisition time for TGSE-BLADE DWI has been reported to be as long as 4\u0026ndash;5 minutes\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, which has prevented its clinical application.\u003c/p\u003e \u003cp\u003eTo overcome this shortcoming, we used a slice acceleration technique termed simultaneous multi-slice (SMS) imaging in TGSE-BLADE DWI. SMS has been incorporated into both TSE and EPI sequences, and applied to most anatomical regions\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. As SMS offers a substantial acceleration in data acquisition according to the number of slices excited simultaneously, it has emerged as a significant imaging technique\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In contrast to in-plane parallel imaging, SMS incurs only a minimal intrinsic signal-to-noise ratio penalty, allowing for full acceleration while maintaining a fixed echo time\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In addition, some SMS implementations have the potential to decrease radiofrequency (RF) power deposition\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMRI is a crucial diagnostic tool for cerebral infarction that enables early detection and prompt formulation and initiation of treatment, which are correlated with enhanced patient prognosis\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Therefore, reduction of scan time is clinically important for increasing the efficacy of patient care. We achieved a reduction in TGSE-BLADE DWI acquisition time to 1 minute by employing SMS. The aim of this study was to compare distortion, artifacts, and image quality between SS-EPI DWI and TGSE-BLADE DWI with SMS (1-min TGSE-BLADE DWI); and to evaluate the diagnostic performance of 1-min TGSE-BLADE DWI for acute or subacute infarction.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cp\u003eThis prospective study was performed in accordance with the Declaration of Helsinki and was approved by Kyoto University Graduate School and Faculty of Medicine, Ethics Committee. Written informed consent was obtained from all participants.\u003c/p\u003e\n \u003cp\u003eWe prospectively enrolled 104 patients with a past history of stroke or symptoms suspicious for acute infarction, or who underwent surgery for a brain tumor within two days, and who underwent SS-EPI DWI, TGSE-BLADE DWI, and T2-weighted imaging (T2WI) between November 2021 and March 2022. The exclusion criteria were as follows: (a) insufficient image quality due to motion artifacts; and (b) unavailability of any of SS-EPI DWI, TGSE-BLADE DWI, or T2WI.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eImage acquisition\u003c/h2\u003e\n \u003cp\u003eMRI was performed using a 3T scanner (MAGNETOM Prisma or MAGNETOM Skyra; Siemens Healthineers, Erlangen, Germany) with a 64-channel head/neck coil or a 32-channel head coil. T2WI of the brain was acquired in addition to the two DWI sequences (SS-EPI DWI and TGSE-BLADE DWI). SS-EPI DWI is a commercially available product that is used routinely in our institute. TGSE-BLADE DWI is a prototype sequence covering the whole brain, and a scan time of 59 s was achieved with a total acceleration factor of 4 (2 \u0026times; in-plane acceleration and 2 \u0026times; slice acceleration). The pulse sequence parameters are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAcquisition protocols\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSS-EPI DWI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTGSE-BLADE DWI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eT2WI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eb value (s/mm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0, 1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0, 1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTR (ms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3300, 3200*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3540\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTE (ms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63, 71*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46, 62*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFA (degrees)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFOV (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e220 \u0026times; 220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e220 \u0026times; 220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e220 \u0026times; 220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMatrix\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160 \u0026times; 160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e160 \u0026times; 160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e448 \u0026times; 448\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSlice thickness (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of slices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVoxel size (mm\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4 \u0026times; 1.4 \u0026times; 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4 \u0026times; 1.4 \u0026times; 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5 \u0026times; 0.5 \u0026times; 5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBandwidth (Hz/pixel)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNEX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParallel imaging\u003c/p\u003e\n \u003cp\u003e(Phase Encoding \u0026times; Slice Encoding)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGRAPPA\u003c/p\u003e\n \u003cp\u003e3 \u0026times; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGRAPPA 2 \u0026times;\u003c/p\u003e\n \u003cp\u003eSlice acceleration 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGRAPPA\u003c/p\u003e\n \u003cp\u003e3 \u0026times; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTurbo factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEPI factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAcquisition time (s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e* Parameters are for MAGNETOM Skyra.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eImage analysis\u003c/h2\u003e\u003cspan\u003e\n \u003cp\u003e(a) Lesion assessment\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThree board-certified neuroradiologists (A.S., S.Ok., and S.Ot. with 16, 16, and 13 years of experience in neuroradiology, respectively) evaluated patients\u0026rsquo; images for acute or subacute infarctions, defined as lesions with high signal intensities on b1000 images and without high values on ADC map. High signal intensities on b1000 images were diagnosed as infarction or artifact based on temporal changes and the findings of other MR sequences; e.g., fluid attenuated inversion recovery (FLAIR). In patients who underwent surgery, restricted diffusion due to postoperative changes on images acquired immediately after surgery was diagnosed as acute cerebral infarction or contusion. Any disagreements among the three neuroradiologists were resolved by consensus.\u003c/p\u003e\n \u003cp\u003e(b) Image quality\u003c/p\u003e\n \u003cp\u003eGeometric distortion, susceptibility artifacts, and overall image quality were assessed qualitatively in the b1000 images of all patients using a 4-point Likert scale\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In patients who had high signal intensities on b1000 images, lesion conspicuity and diagnostic confidence were qualitatively evaluated in b1000 images using a 4-point Likert scale\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In the case of multiple lesions, a comprehensive assessment was performed. The image assessment criteria are listed in Supplementary Table\u0026nbsp;1. Image quality was evaluated by the same three neuroradiologists who performed lesion assessment. Each reader was blinded to the type of DWI sequence. The majority opinion of the raters was designated as the final score. If the three opinions differed, a resolution was obtained by consensus.\u003c/p\u003e\n \u003cp\u003e(c) Quantitative analysis\u003c/p\u003e\n \u003cp\u003eDistortion was examined quantitatively by measuring the displacement between T2WI and each DWI sequence in three parts of the brain: frontal lobe near frontal sinus, temporal tip, and pons\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eRegions-of-interest (ROIs) were placed on high-signal-intensity lesions, centrum semiovale (CSO), and the pons in the b1000 images of each DWI sequence. If multiple lesions were present, the ROI was placed in the slice that contained the greatest area of the largest lesion. In all patients, signal-to-noise ratio (SNR) was calculated as SNR\u0026thinsp;=\u0026thinsp;SI\u003csub\u003ecso or pons\u003c/sub\u003e / SD\u003csub\u003ecso or pons\u003c/sub\u003e\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. SI\u003csub\u003ecso or pons\u003c/sub\u003e and SD\u003csub\u003ecso or pons\u003c/sub\u003e are the mean and standard deviation of signal intensities of CSO or pons. Contrast-to-noise ratio (CNR) was calculated as CNR = (SI\u003csub\u003elesion\u003c/sub\u003e \u0026ndash; SI\u003csub\u003ecso\u003c/sub\u003e) / SD\u003csub\u003ecso\u003c/sub\u003e in patients with acute or subacute infarction\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. SI\u003csub\u003elesion\u003c/sub\u003e, SI\u003csub\u003ecso\u003c/sub\u003e, and SI\u003csub\u003epons\u003c/sub\u003e are the mean signal intensities of lesions of acute or subacute infarction, CSO, and pons, respectively; and SD\u003csub\u003ecso\u003c/sub\u003e is the standard deviation of CSO. The same ROIs were then placed in the ADC maps of each DWI sequence. ROI area was 60\u0026ndash;99 mm\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e in CSO and pons, and 4\u0026ndash;69 mm\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e in lesions. Evaluation of distortion and ROI measurements was performed by a board-certified radiologist (S.Ok.) using ImageJ software version 1.53e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.nih.gov/ij/\u003c/span\u003e\u003c/span\u003e) and was approved by another board-certified radiologist (Y.F. with 25 years of experience in neuroradiology).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eSNR maps\u003c/h2\u003e\n \u003cp\u003eSNR maps were created using SS-EPI DWI and TGSE-BLADE DWI acquired in one healthy volunteer. Each DWI sequence was scanned 10 times, and an SNR map of each DWI was created as the mean map divided by the SD map, using Image Calculator in SPM12 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fil.ion.ucl.ac.uk/spm/software/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eInterrater reliability for the image quality scores measured independently by the three radiologists was evaluated using Fleiss\u0026rsquo; kappa statistics using RStudio Software version 2022.12.0 (RStudio PBC, Boston, USA)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The calculated \u0026kappa; statistic was interpreted as follows: 0.20 or less, slight agreement; 0.21\u0026ndash;0.40, fair agreement; 0.41\u0026ndash;0.60, moderate agreement; 0.61\u0026ndash;0.80, substantial agreement; and 0.81\u0026ndash;1.00, almost perfect agreement.\u003c/p\u003e\n \u003cp\u003eLengths of displacement and image quality scores were compared between the two DWI sequences using Wilcoxon signed-rank test because the data distribution was not normal. SNR, CNR, and ADC values were compared between the two DWI sequences using paired t-tests because the data distribution was normal. \u003cem\u003ep\u003c/em\u003e values less than 0.05 were considered statistically significant. The correlation coefficient was calculated to evaluate correlations of ADC values from the two DWI sequences, and Bland\u0026ndash;Altman analysis was also performed. Statistical analyses were performed using MedCalc version 20 (MedCalc Software, Ostend, Belgium).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cp\u003eNo participant was excluded from the study. In total, 104 patients were included (mean age, 67.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.7; age range, 23\u0026ndash;93 years; 64 males, 40 females) (Supplementary Fig. 1). Of 82 patients with a past history of stroke or symptoms suspicious for acute infarction, 37 had high signal intensities indicative of acute or subacute cerebral infarction. Forty-one patients had no high signal intensities on b1000 images, and 4 patients had a high signal intensity on b1000 images that also showed high signal on ADC maps. Twenty-two patients underwent surgery within two days and had high signal intensity lesions indicative of postoperative contusion or acute infarction on b1000 images. Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e lists the demographic data of all participants.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003ePatient demographics\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"644\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.304347826086957%\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.93788819875776%\" colspan=\"2\"\u003e\n \u003cp\u003ePatients with a past history of stroke or symptoms suspicious for acute infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.757763975155278%\" rowspan=\"2\"\u003e\n \u003cp\u003ePatients who underwent surgery for a brain tumor within two days (n=22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"60.880829015544045%\"\u003e\n \u003cp\u003ePatients without acute or subacute infarction (n=45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.119170984455955%\"\u003e\n \u003cp\u003ePatients with acute or subacute infarction (n=37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.304347826086957%\"\u003e\n \u003cp\u003eSex (male:female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.49068322981366%\"\u003e\n \u003cp\u003e27:18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.4472049689441%\"\u003e\n \u003cp\u003e25:12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.757763975155278%\"\u003e\n \u003cp\u003e12:10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.304347826086957%\"\u003e\n \u003cp\u003eMean age \u0026plusmn; SD (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.49068322981366%\"\u003e\n \u003cp\u003e68.0 \u0026plusmn; 14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.4472049689441%\"\u003e\n \u003cp\u003e74.5 \u0026plusmn; 11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.757763975155278%\"\u003e\n \u003cp\u003e53.0 \u0026plusmn; 19.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.304347826086957%\"\u003e\n \u003cp\u003eNeurological indication for MRI examination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.49068322981366%\"\u003e\n \u003cp\u003eOld cerebral infarction (n=31)\u003cbr\u003e\u0026nbsp;Subacute infarction without high signal intensity on b1000 images (n=6)\u003cbr\u003e\u0026nbsp;Transient ischemic attack (n=2)\u003cbr\u003e\u0026nbsp;Carotid artery stenosis (n=2)\u003cbr\u003e\u0026nbsp;Amaurosis fugax (n=1)\u003cbr\u003e\u0026nbsp;Old cerebral hemorrhage (n=1)\u003cbr\u003e\u0026nbsp;Middle cerebral artery stenosis (n=1)\u003cbr\u003e\u0026nbsp;Retinal artery occlusion (n=1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.4472049689441%\"\u003e\n \u003cp\u003eAcute or subacute infarction\u003cbr\u003e\u0026nbsp;Day 1\u0026ndash;5 (n=6)\u003cbr\u003e\u0026nbsp;Day 6\u0026ndash;10 (n=14)\u003cbr\u003e\u0026nbsp;Day 11 (n=11)\u003c/p\u003e\n \u003cp\u003eOnset date unknown (n=5)\u003cbr\u003e\u0026nbsp;Subarachnoid hemorrhage, post aneurysm coiling (n=1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.757763975155278%\"\u003e\n \u003cp\u003ePostoperative day 1 of brain tumor\u003cbr\u003e\u0026nbsp; Glioma (n=14)\u003cbr\u003e\u0026nbsp; Brain metastasis (n=4)\u003cbr\u003e\u0026nbsp; Meningioma (n=2)\u003cbr\u003e\u0026nbsp; Acoustic schwannoma (n=1)\u003cbr\u003e\u0026nbsp; Tuberculoma (n=1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eLesion assessment\u003c/h2\u003e\n \u003cp\u003eTen lesions in 9 patients were diagnosed as acute/subacute infarction or postoperative contusion and were detectable on TGSE-BLADE DWI but not on SS-EPI DWI. Six of the 10 acute or subacute infarct lesions were in the cerebellar hemisphere, located near the cerebellar tentorium, frontal cortex, parietal cortex, putamen, and globus pallidus (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Four of the 10 acute infarct lesions or postoperative contusions were observed in patients immediately after surgery, and were difficult to find on SS-EPI DWI because of susceptibility artifacts due to air or hemorrhage (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). No lesion was detectable on SS-EPI DWI but not on TGSE-BLADE DWI. Lesions visualized only on TGSE-BLADE DWI were verified by pixel-to-pixel comparison in FLAIR images obtained at the same time or in FLAIR images obtained at follow-up MRI.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eImage quality\u003c/h2\u003e\n \u003cp\u003eThe kappa values of inter-rater agreement for the image quality scores of geometric distortion, susceptibility artifacts, overall image quality, lesion conspicuity, and diagnostic confidence were 0.67, 0.63, 0.69, 0.49, and 0.54, respectively, showing fair agreement or moderate agreement.\u003c/p\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e lists the image quality scores for each DWI sequence. Scores for geometric distortion, susceptibility artifacts, and overall image quality were lower in SS-EPI DWI than TGSE-BLADE DWI (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Scores for lesion conspicuity and diagnostic confidence were lower in SS-EPI DWI than TGSE-BLADE DWI in patients with acute infarction and in patients immediately after surgery (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;.001 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, respectively).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eResults of image quality for SS-EPI DWI and TGSE-BLADE DWI\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eThe scores of geometric distortion, susceptibility artifacts and overall image quality (n\u0026thinsp;=\u0026thinsp;104)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EPI DWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-min TGSE-BLADE DWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGeometric distortion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0 (3.0\u0026ndash;3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (4.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSusceptibility artifacts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0 (3.0\u0026ndash;3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (4.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverall image quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0 (3.0\u0026ndash;3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (4.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eThe scores of lesion conspicuity and diagnostic confidence in patients with acute or subacute infarctions (n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EPI DWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-min TGSE-BLADE DWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLesion conspicuity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (3.1-4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (4.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiagnostic confidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (3.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (4.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eThe scores of lesion conspicuity and diagnostic confidence in patients who have undergone surgery for a brain tumor within a few days (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSS-EPI DWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-min TGSE-BLADE DWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLesion conspicuity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0 (3.0\u0026ndash;3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (4.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiagnostic confidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0 (3.0\u0026ndash;3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 (4.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eNote \u0026ndash; Data are presented as the median (interquartile range).\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eQuantitative analysis\u003c/h2\u003e\n \u003cp\u003eExample images and the measured distortion values are shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Distortion values were significantly higher in SS-EPI DWI than TGSE-BLADE DWI in frontal lobe, temporal tip, and pons (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\n \u003cp\u003eMean SNR in CSO was significantly higher in SS-EPI DWI (26.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0) than TGSE-BLADE DWI (22.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), but showed no significant difference in pons (SS-EPI DWI, 9.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0; TGSE-BLADE DWI, 9.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.40). Mean SNR values were higher at the periphery and lower at the center of the brain in the SNR maps for both DWI sequences due to the characteristics of the 32-channel phased array coil (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Mean SNR in CSO was higher in SS-EPI DWI than TGSE-BLADE DWI; however, SNR in temporal lobe was higher in TGSE-BLADE DWI, probably because this sequence is less prone to susceptibility artifacts. Mean CNR was significantly higher in SS-EPI DWI (20.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1) than TGSE-BLADE DWI (15.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003cp\u003eMean ADC values for each DWI are shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. There was no significant difference in ADC values in CSO or pons. In lesions, mean ADC values were significantly lower in SS-EPI DWI than TGSE-BLADE DWI (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.004). There was a linear correlation between SS-EPI DWI and TGSE-BLADE DWI for ADC values in lesions (r\u0026thinsp;=\u0026thinsp;0.80) (Supplementary Fig. 2a). Bland\u0026ndash;Altman analysis of the ADC measurements of SS-EPI DWI and TGSE-BLADE DWI revealed that most data were distributed between \u0026plusmn;\u0026thinsp;1.96 SD (Supplementary Fig. 2b).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eADC values in centrum semiovale, pons, and lesions for SS-EPI DWI and TGSE-BLADE DWI\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSS-EPI DWI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTGSE-BLADE DWI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCSO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e769.6\u0026thinsp;\u0026plusmn;\u0026thinsp;81.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e764.8\u0026thinsp;\u0026plusmn;\u0026thinsp;67.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePons\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e761.2\u0026thinsp;\u0026plusmn;\u0026thinsp;53.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e769.0\u0026thinsp;\u0026plusmn;\u0026thinsp;98.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLesions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e592.9\u0026thinsp;\u0026plusmn;\u0026thinsp;146.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e627.2\u0026thinsp;\u0026plusmn;\u0026thinsp;124.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eNote \u0026ndash; Data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (mm\u003csup\u003e2\u003c/sup\u003e/s). CSO, centrum semiovale.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe major findings of the present study are that some acute infarctions were detectable only by TGSE-BLADE DWI whereas no lesions were detectable only by SS-EPI DWI, and that scores for geometric distortion, susceptibility artifacts, overall image quality, lesion conspicuity, and diagnostic confidence were higher for TGSE-BLADE DWI. Taken together, these imaging image characteristics indicate the potential utility of TGSE-BLADE DWI with SMS for diagnosis of acute infarction. In previous studies with TGSE-BLADE DWI, scan time was consistently 4 to 5 minutes\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. The present study reports the first attempt to significantly reduce acquisition time to approximately 1 minute. The ability to scan images within this shortened timeframe, coupled with enhanced diagnostic capabilities for acute cerebral infarction compared to SS-EPI DWI, renders it highly valuable for routine clinical application.\u003c/p\u003e \u003cp\u003eLesions that could not be identified after surgery as acute infarction on SS-EPI DWI were located near the cerebellar tentorium, cortex, hemorrhage, or pneumocephalus. A previous study has reported sensitivity of 81.1% and a false-negative rate of 5.6% for detecting infratentorial infarctions using 5 mm SS-EPI DWI, and lesions in false-negative cases were small\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Another study noted that most patients with false-negative lesions had infratentorial infarction or transient ischemic attack\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. To mitigate false negatives, several reports have suggested that incorporating coronal sections or thin slice DWI can enhance diagnostic capabilities with SS-EPI DWI\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. However, it might be possible to diagnose acute cerebral infarctions prone to false negatives using TGSE-BLADE DWI alone, and achieve diagnostic accuracy similar to that of additional imaging (such as coronal sections or thin slices) without acquiring additional scans.\u003c/p\u003e \u003cp\u003eMedian scores for geometric distortion and susceptibility artifacts were 3.0 for SS-EPI DWI and 4.0 for TGSE-BLADE DWI. Distortion was also quantitatively less near the air-bone interfaces (e.g., frontal lobe, temporal tip, and pons) in TGSE-BLADE-DWI with SMS. These findings align with those of a prior study that used TGSE-BLADE DWI without acceleration technique\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Their scores for lesion conspicuity and diagnostic confidence in patients with acute or subacute infarction were lower in SS-EPI DWI than TGSE-BLADE DWI; however, median score was 4.0 for each sequence. In contrast, median score in post-surgery patients was 3.0 for SS-EPI DWI and 4.0 for TGSE-BLADE DWI. We consider that there is greater susceptibility postoperatively to artifacts due to air or hemorrhage, in which case TGSE-BLADE DWI is more beneficial.\u003c/p\u003e \u003cp\u003eSNR values were lower for TGSE-BLADE DWI than SS-EPI DWI in CSO. In SNR maps for temporal lobe, however, values were higher for TGSE-BLADE DWI than for SS-EPI DWI. TGSE-BLADE DWI showed less SNR degradation in areas prone to distortion, such as near air\u0026ndash;bone interfaces, whereas SS-EPI DWI demonstrated superior SNR in other regions, primarily because only half of the signals are used in this sequence due to the non-CPMG (Carr-Purcell-Meiboom-Gill) problem. Another reason for the lower SNR values is that positioning the gradient echo with T2* decay effects at the center of k-space diminishes the image quality of TGSE-BLADE DWI\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Despite these disadvantages of 1-min TGSE-BLADE DWI, its ability to detect lesions located near susceptibility artifacts is a strong advantage.\u003c/p\u003e \u003cp\u003eThere was no significant difference between the sequences in terms of ADC values in CSO or pons. In lesions, however, ADC values were significantly higher for TGSE-BLADE DWI than SS-EPI DWI, consistent with the findings of a previous study\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This discrepancy might have been due to the substantial differences in SNR and T1 values between normal tissue and lesions \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, but the cause remains unclear because no study has investigated cerebral infarction using TGSE-BLADE DWI. Furthermore, these differences might also have contributed to the lower CNR observed in TGSE-BLADE DWI. Whereas there was a strong correlation in ADC values for lesions between SS-EPI DWI and TGSE-BLADE DWI. Therefore, we consider that there should be few issues in clinical diagnosis.\u003c/p\u003e \u003cp\u003eThere are several limitations in this study. Firstly, the sample size was small. A larger sample size might facilitate a more comprehensive investigation of lesions that could not be visualized by SS-EPI DWI. However, we prospectively enrolled over 100 patients, and believe that the number of cases was sufficient to demonstrate the utility of TGSE-BLADE DWI. Second, subacute infarct was diagnosed most commonly, and there were relatively few hyperacute infarcts. Due to the prospective nature of the study in which two types of DWI were acquired, it was challenging to perform these imaging examinations in patients with hyperacute stroke who require urgent treatment decisions. A previous study reported that some lesions were not depicted on SS-EPI DWI in the hyperacute stage\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, indicating the need for further investigation in the future. Third, SMS imaging was not applied for SS-EPI DWI because we compared TGSE-BLADE DWI with SS-EPI DWI acquired with the protocol used at our institution. Although it is feasible to implement SMS for SS-EPI DWI, there is limited advantage because the shorter TR used has the effect of reducing SNR. Finally, in making the score judgments, the neuroradiologists noted that it was easy to distinguish the SS-EPI DWI and TGSE-BLADE DWI sequences based on the presence or absence of signal pile-up and geometric distortion.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCompared with SS-EPI DWI, one-minute TGSE-BLADE DWI has better image quality in terms of distortion and artifacts, higher diagnostic performance for identifying acute infarctions, and its acquisition time is similar to that of SS-EPI DWI. One-minute TGSE-BLADE DWI is therefore clinically acceptable and shows promise as a diagnostic tool for identifying acute infarctions in acute stroke patients and postoperative patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.U., K.Z. and Y.A. conceived and designed the analysis. M.T., N.S., S.Ik and S.I. collected the data. T.M. and Y.A. contributed data or analysis tools. A.S. , S.Ot, S.Ok. and S.N. performed the analysis. S.Ok . and Y.F. wrote the main manuscript text. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Software and versions used in the study: ImageJ software version 1.53e (https://imagej.nih.gov/ij/), SPM12 (https://www.fil.ion.ucl.ac.uk/spm/software/), RStudio Software version 2022.12.0 (RStudio PBC, Boston, USA), and Medcalc version 20 (MedCalc Software).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by JSPS KAKENHI Grant Numbers JP22K07746, JP24K18796, ISHIZUE 2023 of Kyoto University, and The Kyoto University Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN/A except Yuta Urushibata and Kun Zhou.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYuta Urushibata is an employee of Siemens Healthcare K. K., Japan.\u003c/p\u003e\n\u003cp\u003eKun Zhou is an employee of Siemens Shenzhen Magnetic Resonance Ltd., China\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests for materials should be addressed to Y.F.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDrake-P\u0026eacute;rez, M., Boto, J., Fitsiori, A., Lovblad, K. \u0026amp; Vargas, M. I. Clinical applications of diffusion weighted imaging in neuroradiology. \u003cem\u003eInsights Imaging\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 535-547, doi:10.1007/s13244-018-0624-3 (2018).\u003c/li\u003e\n\u003cli\u003eNagaraja, N. 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Total 104 patients with a past history of stroke or symptoms suspicious for acute infarction or who had undergone surgery for brain tumor within two days were prospectively enrolled. Ten lesions in 9 patients were diagnosed as acute or subacute infarction and were detectable only in TGSE-BLADE DWI but not in SS-EPI DWI. Scores for geometric distortion, susceptibility artifacts, overall image quality, lesion conspicuity and diagnostic confidence were lower for SS-EPI DWI than TGSE-BLADE DWI (\u003cem\u003ep\u003c/em\u003e≤.001). Distortion was significantly worse in SS-EPI DWI than TGSE-BLADE DWI (\u003cem\u003ep\u003c/em\u003e\u0026lt;.001). SNR of centrum semiovale was significantly higher in SS-EPI DWI than TGSE-BLADE DWI (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). One-minute TGSE-BLADE DWI showed better image quality than SS-EPI DWI in terms of distortion and artifacts, and higher diagnostic performance for acute infarctions.\u003c/p\u003e","manuscriptTitle":"Comparison of SS-EPI DWI and one-minute TGSE-BLADE DWI for diagnosis of acute infarction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-14 17:59:00","doi":"10.21203/rs.3.rs-4361252/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-09T18:36:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-06T12:00:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330019927229301507201111552492975734972","date":"2024-09-22T21:32:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-06T14:34:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"266065455960292253805494294722700740438","date":"2024-07-20T06:07:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-18T04:12:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-14T08:56:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-07T03:50:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-07T03:45:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-02T23:54:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e98d36b6-789b-4dda-b314-c9b89f0d7a65","owner":[],"postedDate":"May 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":31744250,"name":"Health sciences/Anatomy/Nervous system"},{"id":31744251,"name":"Health sciences/Diseases/Neurological disorders/Cerebrovascular disorders"},{"id":31744252,"name":"Health sciences/Diseases/Neurological disorders/Stroke"}],"tags":[],"updatedAt":"2025-02-24T16:00:10+00:00","versionOfRecord":{"articleIdentity":"rs-4361252","link":"https://doi.org/10.1038/s41598-025-90413-5","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-02-22 15:57:13","publishedOnDateReadable":"February 22nd, 2025"},"versionCreatedAt":"2024-05-14 17:59:00","video":"","vorDoi":"10.1038/s41598-025-90413-5","vorDoiUrl":"https://doi.org/10.1038/s41598-025-90413-5","workflowStages":[]},"version":"v1","identity":"rs-4361252","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4361252","identity":"rs-4361252","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}