Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: Chemical exchange-dependent saturation transfer (CEST) MRI is sensitive for detecting solid-like proteins and may detect changes in the levels of mobile proteins and peptides in tissues. The objective of this study was to evaluate the characteristics of chemical exchange proton pools using the CEST MRI technique in patients with dementia. Materials and Methods: Our institutional review board approved this cross-sectional prospective study and informed consent was obtained from all participants. This study included 41 subjects (19 with dementia and 22 without dementia). Complete CEST data of the brain were obtained using a three-dimensional gradient and spin-echo sequence to map CEST indices, such as amide, amine, hydroxyl, and magnetization transfer ratio asymmetry (MTR asym) values, using six-pool Lorentzian fitting. Statistical analyses of CEST indices were performed to evaluate group comparisons, their correlations with gray matter volume (GMV) and Mini-Mental State Examination (MMSE) scores, and receiver operating characteristic (ROC) curves. Results: Amine signals (0.029 for non-dementia, 0.046 for dementia, p = 0.011 at hippocampus) and MTR asym values at 3 ppm (0.748 for non-dementia, 1.138 for dementia, p = 0.022 at hippocampus), and 3.5 ppm (0.463 for non-dementia, 0.875 for dementia, p = 0.029 at hippocampus) were significantly higher in the dementia group than in the non-dementia group. Most CEST indices were not significantly correlated with GMV; however, except amide, most indices were significantly correlated with the MMSE scores. The classification power of most CEST indices was lower than that of GMV but adding one of the CEST indices in GMV improved the classification between the subject groups. The largest improvement was seen in the MTR asym values at 2 ppm in the anterior cingulate (area under the ROC curve = 0.981), with a sensitivity of 100 and a specificity of 90.91. Conclusion CEST MRI potentially allows noninvasive image alterations in the Alzheimer’s disease brain without injecting isotopes for monitoring different disease states and may provide a new imaging biomarker in the future.

Purpose: This study aimed to propose an effective end-to-end process in medical imaging using an independent task learning (ITL) algorithm and to evaluate its performance in maxillary sinusitis applications. Materials and Methods: For the internal dataset, 2122 Waters’ view X-ray images, which included 1376 normal and 746 sinusitis images, were divided into training (n=1824) and test (n=298) datasets. For external validation, 700 images, including 379 normal and 321 sinusitis images, from three different institutions were evaluated. To develop the automatic diagnosis system algorithm, four processing steps were performed: 1) preprocessing for ITL, 2) facial patch detection, 3) maxillary sinusitis detection, and 4) a localization report with the sinusitis detector. Results: The accuracy of facial patch detection, which was the first step in the end-to-end algorithm, was 100%, 100%, 99.5%, and 97.5% for the internal set and external validation sets #1, #2, and #3, respectively. The accuracy and area under the receiver operating characteristic curve (AUC) of maxillary sinusitis detection were 88.93% (0.89), 91.67% (0.90), 90.45% (0.86), and 85.13% (0.85) for the internal set and external validation sets #1, #2, and #3, respectively. The accuracy and AUC of the fully automatic sinusitis diagnosis system, including site localization, were 79.87% (0.80), 84.67% (0.82), 83.92% (0.82), and 73.85% (0.74) for the internal set and external validation sets #1, #2, and #3, respectively. Conclusion ITL application for maxillary sinusitis showed reasonable performance in internal and external validation tests, compared with applications used in previous studies.

Objective: Chemical exchange-dependent saturation transfer (CEST) MRI is sensitive for detecting solid-like proteins and may detect changes in the levels of mobile proteins and peptides in tissues. The objective of this study was to evaluate the characteristics of chemical exchange proton pools using the CEST MRI technique in patients with dementia. Materials and Methods: Our institutional review board approved this cross-sectional prospective study and informed consent was obtained from all participants. This study included 41 subjects (19 with dementia and 22 without dementia). Complete CEST data of the brain were obtained using a three-dimensional gradient and spin-echo sequence to map CEST indices, such as amide, amine, hydroxyl, and magnetization transfer ratio asymmetry (MTR asym) values, using six-pool Lorentzian fitting. Statistical analyses of CEST indices were performed to evaluate group comparisons, their correlations with gray matter volume (GMV) and Mini-Mental State Examination (MMSE) scores, and receiver operating characteristic (ROC) curves. Results: Amine signals (0.029 for non-dementia, 0.046 for dementia, p = 0.011 at hippocampus) and MTR asym values at 3 ppm (0.748 for non-dementia, 1.138 for dementia, p = 0.022 at hippocampus), and 3.5 ppm (0.463 for non-dementia, 0.875 for dementia, p = 0.029 at hippocampus) were significantly higher in the dementia group than in the non-dementia group. Most CEST indices were not significantly correlated with GMV; however, except amide, most indices were significantly correlated with the MMSE scores. The classification power of most CEST indices was lower than that of GMV but adding one of the CEST indices in GMV improved the classification between the subject groups. The largest improvement was seen in the MTR asym values at 2 ppm in the anterior cingulate (area under the ROC curve = 0.981), with a sensitivity of 100 and a specificity of 90.91. Conclusion CEST MRI potentially allows noninvasive image alterations in the Alzheimer’s disease brain without injecting isotopes for monitoring different disease states and may provide a new imaging biomarker in the future.

PURPOSE: The purpose of this study was to investigate if double inversion recovery (DIR) imaging can have a role in the evaluation of brain ischemia, compared with diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) imaging. MATERIALS AND METHODS: Sixty-seven patients within 48 hours of onset, underwent MRI scans with FLAIR, DWI with b-value of 0 (B0) and 1000 s/mm², and DIR sequences. Patients were categorized into four groups: within three hours, three to six hours, six to 24 hours, and 24 to 48 hours after onset. Lesion-to-normal ratio (LNR) value was calculated and compared among all sequences within each group, by the Friedman test and conducted among all groups, for each sequence by the Kruskal-Wallis test. In qualitative assessment, signal intensity changes of DIR, B0, and FLAIR based on similarity with DWI and image quality of each sequence, were graded on a 3-point scale, respectively. Scores for detectability of lesions were compared by the McNemar's test. RESULTS: LNR values from DWI were higher than DIR, but not statistically significant in all groups (P > 0.05). LNR values of DIR were significantly higher than FLAIR within 24 hours of onset (P < 0.05). LNR values were significantly different between, before, and after six hours onset time for DIR (P = 0.016), B0 (P = 0.008), and FLAIR (P = 0.018) but not for DWI (P = 0.051). Qualitative analysis demonstrated that detectability of DIR was higher, compared to that of FLAIR within 4.5 hours and six hours of onset (P < 0.05). Also, the DWI quality score was lower than that of DIR, particularly relative to infratentorial lesions. CONCLUSION: DIR provides higher detectability of hyperacute brain ischemia than B0 and FLAIR, and does not suffer from susceptibility artifact, unlike DWI. So, DIR can be used to replace evaluation of the FLAIR-DWI mismatch.
Artifacts ; Brain Infarction ; Brain Ischemia ; Diffusion Magnetic Resonance Imaging ; Humans ; Magnetic Resonance Imaging ; Stroke

PURPOSE: The Alberta Stroke Program Early CT Score (ASPECTS) was devised to quantify the extent of early ischemic changes in the middle cerebral artery territory on brain CT. We performed a systematic review and meta-analysis of studies that presented clinical outcomes and baseline ASPECTS in ischemic stroke patients managed with endovascular methods to validate the use of ASPECTS for risk prognostication. MATERIALS AND METHODS: We searched the MEDLINE, EMBASE, and Cochran databases for observational or interventional studies that reported clinical outcomes and baseline ASPECTS in ischemic stroke patients treated with endovascular methods. Data were pooled to perform a meta-analysis for comparisons of clinical outcomes between high and low ASPECTS patients. RESULTS: A meta-analysis of 13 studies (six observational and seven interventional) revealed favorable outcomes (mRS sore 0-2 at 90 days) for high baseline ASPECTS (odds ratio=2.22; 95% CI: 1.74-2.86). CONCLUSION: High ASPECTS is a predictor of favorable outcome after endovascular therapy for ischemic stroke.
Alberta* ; Brain ; Humans ; Middle Cerebral Artery ; Stroke* ; Thrombectomy

Mammary-type myofibroblastoma (MFB) is a rare, benign spindle cell neoplasm occurring along the milkline, with extension from the mid-axilla to the medial groin. It is histologically and immunohistochemically identical to MFB of the breast and is part of a spectrum of lesions that includes spindle cell lipoma and cellular angiofibroma. Recently, we experienced two cases of mammary-type MFB involving male patients aged 30 and 58 years, respectively. The tumors were located in the right scrotal sac and in the right axilla. Wide excisions were performed. Microscopically, the masses were composed of haphazardly arranged, variably sized fascicles of bland spindle cells and were admixed with mature fat tissue. The spindle cells in both cases showed immunopositivity for desmin and CD34 and negativity for smooth muscle actin. Loss of retinoblastoma (RB)/13q14 loci is a characteristic genetic alteration of mammary-type MFB, and we identified loss of RB protein expression by immunohistochemical staining. We emphasize the importance of awareness of this rare neoplasm when a spindle cell neoplasm is accompanied by desmin immunopositivity. The second patient was alive without recurrence for 20 months, and the first patient had not been followed.
Actins ; Angiofibroma ; Axilla ; Breast ; Desmin ; Groin ; Humans ; Lipoma ; Male ; Muscle, Smooth ; Neoplasms, Muscle Tissue* ; Recurrence ; Retinoblastoma ; Retinoblastoma Protein