Excessive Postoperative Nasal Bleeding Following Septoplasty Caused by a Branch of the Middle Meningeal Artery.

Septoplasty is a widely performed procedure globally to correct a deviated nasal septum and improve nasal breathing. Life-threatening nasal bleeding as a complication of septoplasty has been reported in a few cases in the literature. In cases of massive postoperative nasal bleeding, transarterial embolization using angiography was performed for the treatment. This article documents 1 case of excessive postoperative nasal bleeding following an uneventful septoplasty, which was successfully treated with embolization of the frontal branch of the middle meningeal artery. This case represents an extremely rare occurrence, and we present it in conjunction with a literature review.

A Sensing-Based Visualization Method for Representing Pressure Distribution in a Multi-Zone Building by Floor.

Airflow in a multi-zone building can be a major cause of pollutant transfer, excessive energy consumption, and occupants discomfort. The key to monitoring airflows and mitigating related problems is to obtain a comprehensive understanding of pressure relationships within the buildings. This study proposes a visualization method for representing pressure distribution within a multi-zone building by using a novel pressure-sensing system. The system consists of a Master device and a couple of Slave devices that are connected with each other by a wireless sensor network. A 4-story office building and a 49-story residential building were installed with the system to detect pressure variations. The spatial and numerical mapping relationships of each zone were further determined through grid-forming and coordinate-establishing processes for the building floor plan. Lastly, 2D and 3D visualized pressure mappings of each floor were generated, illustrating the pressure difference and spatial relationship between adjacent zones. It is expected that the pressure mappings derived from this study will allow building operators to intuitively perceive the pressure variations and the spatial layouts of the zones. These mappings also make it possible for operators to diagnose the differences in pressure conditions between adjacent zones and plan a control scheme for the HVAC system more efficiently.

Deep learning-based detection algorithm for brain metastases on black blood imaging.

Brain metastases (BM) are the most common intracranial tumors, and their prevalence is increasing. High-resolution black-blood (BB) imaging was used to complement the conventional contrast-enhanced 3D gradient-echo imaging to detect BM. In this study, we propose an efficient deep learning algorithm (DLA) for BM detection in BB imaging with contrast enhancement scans, and assess the efficacy of an automatic detection algorithm for BM. A total of 113 BM participants with 585 metastases were included in the training cohort for five-fold cross-validation. The You Only Look Once (YOLO) V2 network was trained with 3D BB sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) images to investigate the BM detection. For the observer performance, two board-certified radiologists and two second-year radiology residents detected the BM and recorded the reading time. For the training cohort, the overall performance of the five-fold cross-validation was 87.95%, 24.82%, 19.35%, 14.48, and 18.40 for sensitivity, precision, F1-Score, the false positive average for the BM dataset, and the false positive average for the normal individual dataset, respectively. For the comparison of reading time with and without DLA, the average reading time was reduced by 20.86% in the range of 15.22-25.77%. The proposed method has the potential to detect BM with a high sensitivity and has a limited number of false positives using BB imaging.

Diagnostic Performance of High-Resolution Vessel Wall Magnetic Resonance Imaging and Digital Subtraction Angiography in Intracranial Vertebral Artery Dissection.

PURPOSE: Intracranial vertebral artery dissection (VAD) is being increasingly recognized as a leading cause of Wallenberg syndrome and subarachnoid hemorrhage. Conventional angiography is considered the standard diagnostic modality, but the diagnosis of VAD remains challenging. This study aimed to compare the diagnostic performance of high-resolution vessel wall imaging (HR-VWI) with digital subtraction angiography (DSA) for intracranial VAD. MATERIALS AND METHODS: Twenty-four patients with 27 VADs, who underwent both HR-VWI and DSA within 2 weeks, were consecutively enrolled in the study from March 2016 to September 2020. HR-VWI and DSA were performed to diagnose VAD and to categorize its angiographic features as either definite dissection or suspicious dissection. Features of HR-VWI were used to evaluate direct arterial wall imaging. The reference standard was set from the clinicoradiologic diagnosis. Two independent raters evaluated the angiographic features, dissection signs, and interrater agreement. Each subject was also dichotomized into two groups (suspicious or definite VAD) in each modality, and diagnosis from HR-VWI and DSA was compared with the final diagnosis by consensus. RESULTS: HR-VWI had higher agreement (90.6% vs. 53.1%) with the final diagnosis and better interrater reliability (kappa value (κ) = 0.91; 95% confidence interval (CI) = 0.64-1.00) compared with DSA (κ = 0.58; 95% CI = 0.35-1.00). HR-VWI provided a more detailed identification of dissection signs (77.7% vs. 22.2%) and better reliability (κ = 0.88; 95% CI = 0.58-1.00 vs. κ = 0.75; 95% CI = 0.36-1.00), compared to DSA. HR-VWI was comparable to DSA for the depiction of angiographic features for VAD. CONCLUSIONS: HR-VWI may be useful to evaluate VAD, with better diagnostic confidence compared to DSA.

Effective End-to-End Deep Learning Process in Medical Imaging Using Independent Task Learning: Application for Diagnosis of Maxillary Sinusitis.

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.

The Clinical Significance of the Hyperintense Acute Reperfusion Marker Sign in Subacute Infarction Patients.

PURPOSE: The hyperintense acute reperfusion marker (HARM) is characterized by the delayed enhancement of the subarachnoid or subpial space observed on postcontrast fluid-attenuated inversion recovery (FLAIR) images, and is considered a cerebral reperfusion marker for various brain disorders, including infarction. In this study, we evaluated the cerebral distribution patterns of HARM for discriminating between an enhancing subacute infarction and an enhancing mass located in the cortex and subcortical white matter. MATERIALS AND METHODS: We analyzed consecutive patients who experienced a subacute ischemic stroke, were hospitalized, and underwent conventional brain magnetic resonance imaging including postcontrast FLAIR within 14 days from symptom onset, as well as those who had lesions corresponding to a clinical sign detected by diffusion-weighted imaging and postcontrast T1-weighted imaging between May 2019 and May 2021. A total of 199 patients were included in the study. Of them, 94 were finally included in the subacute infarction group. During the same period, 76 enhancing masses located in the cortex or subcortical white matter, which were subcategorized as metastasis, malignant glioma, and lymphoma, were analyzed. We analyzed the overall incidence of HARM in subacute ischemic stroke cases, and compared the enhancement patterns between cortical infarctions and cortical masses. RESULTS: Among 94 patients with subacute stroke, 78 patients (83%) presented HARM, and among 76 patients with subcortical masses, 48 patients (63%) presented peripheral rim enhancement. Of 170 subcortical enhancing lesions, 88 (51.8%) showed HARM, and 78 (88.6%) were determined to be subacute infarction. Among 94 patients with subacute stroke, 48 patients (51%) had diffusion restrictions, and HARM was found in 39 patients (81.2%). Of the 46 patients (49%) without diffusion restriction, 39 patients (84.8%) showed HARM. CONCLUSIONS: The presence of HARM was significantly associated with subacute infarctions. For the masses, a peripheral rim enhancement pattern was observed around the mass rather than the cerebral sulci on postcontrast FLAIR.

Novel Approaches to Detection of Cerebral Microbleeds: Single Deep Learning Model to Achieve a Balanced Performance.

PURPOSE: Cerebral microbleeds (CMBs) are considered essential indicators for the diagnosis of cerebrovascular disease and cognitive disorders. Traditionally, CMBs are manually interpreted based on criteria including the shape, diameter, and signal characteristics after an MR examination, such as susceptibility-weighted imaging or gradient echo imaging (GRE). In this paper, an efficient method for CMB detection in GRE scans is presented. MATERIALS AND METHODS: The proposed framework consists of the following phases: (1) pre-processing (skull extraction), (2) the first training with the ground truth labeled using CMB, (3) the second training with the ground truth labeled with CMB mimicking the same subjects, and (4) post-processing (cerebrospinal fluid (CSF) filtering). The proposed technique was validated on a dataset of 1133 CBMs that consisted of 5284 images for training and 1737 images for testing. We applied a two-stage approach using a region-based CNN method based on You Only Look Once (YOLO) to investigate a novel CMB detection technique. RESULTS: The sensitivity, precision, F1-score and false positive per person (FPavg) were evaluated as 80.96, 60.98, 69.57 and 6.57, 59.69, 62.70, 61.16 and 4.5, 66.90, 79.75, 72.76 and 2.15 for YOLO with a single label, YOLO with double labels, and YOLO + CSF filtering, respectively, and YOLO + CSF filtering showed the highest precision performance, F1-score and lowest FPavg. CONCLUSIONS: Using proposed framework, we developed an optimized CMB learning model with low false positives and a balanced performance in clinical practice.

Development and evaluation of a T1 standard brain template for Alzheimer disease.

BACKGROUND: Patients with Alzheimer disease (AD) and mild cognitive impairment (MCI) have high variability in brain tissue loss, making it difficult to use a disease-specific standard brain template. The objective of this study was to develop an AD-specific three-dimensional (3D) T1 brain tissue template and to evaluate the characteristics of the populations used to form the template. METHODS: We obtained 3D T1-weighted images from 294 individuals, including 101 AD, 96 amnestic MCI, and 97 cognitively normal (CN) elderly individuals, and segmented them into different brain tissues to generate AD-specific brain tissue templates. Demographic data and clinical outcome scores were compared between the three groups. Voxel-based analyses and regions-of-interest-based analyses were performed to compare gray matter volume (GMV) and white matter volume (WMV) between the three participant groups and to evaluate the relationship of GMV and WMV loss with age, years of education, and Mini-Mental State Examination (MMSE) scores. RESULTS: We created high-resolution AD-specific tissue probability maps (TPMs). In the AD and MCI groups, losses of both GMV and WMV were found with respect to the CN group in the hippocampus (F >44.60, P<0.001). GMV was lower with increasing age in all individuals in the left (r=-0.621, P<0.001) and right (r=-0.632, P<0.001) hippocampi. In the left hippocampus, GMV was positively correlated with years of education in the CN groups (r=0.345, P<0.001) but not in the MCI (r=0.223, P=0.0293) or AD (r=-0.021, P=0.835) groups. WMV of the corpus callosum was not significantly correlated with years of education in any of the three subject groups (r=0.035 and P=0.549 for left, r=0.013 and P=0.821 for right). In all individuals, GMV of the hippocampus was significantly correlated with MMSE scores (left, r=0.710 and P<0.001; right, r=0.680 and P<0.001), while WMV of the corpus callosum showed a weak correlation (left, r=0.142 and P=0.015; right, r=0.123 and P=0.035). CONCLUSIONS: A 3D, T1 brain tissue template was created using imaging data from CN, MCI, and AD participants considering the participants' age, sex, and years of education. Our disease-specific template can help evaluate brains to promote early diagnosis of MCI individuals and aid treatment of MCI and AD individuals.

Added Value of Chemical Exchange-Dependent Saturation Transfer MRI for the Diagnosis of Dementia.

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 (MTRasym) 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 MTRasym 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 MTRasym 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.

Multiple myeloma with intractable lumbar pain and diagnostic challenge with MRI: A case report.

We present a 63-year-old male patient with intractable bone pain and rapidly progressive osteoporosis, who was diagnosed with multiple myeloma (MM) by CT despite normal magnetic resonance imaging (MRI) findings. The gold standard diagnostic modality for MM is MRI as it can be used to sensitively evaluate bone marrow, however, the current case highlights that MRI is not always accurate in evaluating MM. CT in combination with MRI could be used for secondary osteoporosis with intractable bone pain in order to determine the diagnosis, treatment, and prognosis.

Fulminant Course of Acute Necrotizing Encephalopathy Followed by Serial MRI: A Case Report.

Acute necrotizing encephalopathy (ANE) is a rare but distinctive type of influenza-associated encephalopathy characterized by symmetric multiple lesions with an invariable thalamic involvement. Although the exact pathogenesis of ANE remains unclear, the most prevalent hypothesis is the "cytokine storm," which results in blood-brain-barrier breakdown. We present the case of a 10-year-old boy with fulminant ANE confirmed with serial MRI studies, including diffusion-weighted imaging and susceptibility-weighted imaging. A comparison of these serial images demonstrated detailed and longitudinal changes in MRI findings during the clinical course corresponding to pathophysiological changes. Our case clarifies the pathogenesis of ANE brain lesions using serial imaging studies and suggests that early immunomodulatory therapy reduces brain damage.

Geometric Classification of Paraclinoid Aneurysms for Microcatheter Superselection in Coil Embolization.

AIM: To suggest a geometric classification of paraclinoid aneurysms for microcatheter superselection. MATERIAL AND METHODS: Clinical data from 76 patients (80 paraclinoid aneurysms) who underwent endovascular treatments were retrospectively reviewed. Paraclinoid aneurysms were classified according to the six directions where the aneurysm neck lies and simplified into three groups as follows: superior, medial, and lateral groups. The medial group was further divided into proximal, mid, and distal subgroups according to the location of the aneurysm neck on lateral angiography. Furthermore, we assessed the superselection success rate with the first-selected pre-shaped microcatheter per group. RESULTS: According to the aneurysm direction, the medial group showed relatively lower superselection success rates (66.1%) than the superior (81.8%) and lateral groups (85.7%). The S-shaped microcatheter was the most frequently used in the superior (69.2%) and lateral groups (62.5%). Acute-angled J- and C-shaped microcatheters (88.5%) were preferred for proximal aneurysms; and obtuse-angled 45°- and 90°-angled microcatheters (75%), for distal aneurysms. The mid-portion group showed the lowest success rate (45.8%) and more difficulties in pre-shaped microcatheter superselection. CONCLUSION: Medially directed mid-portion aneurysms were difficult to access using pre-shaped microcatheters; thus, tailored steam-shaping techniques may be considered. Superiorly and laterally directed aneurysms could be accessed using pre-S-shaped microcatheters. Acute-angled microcatheters may be considered for proximal aneurysms; and obtuse-angled microcatheters, for distal aneurysms.

Atherosclerotic plaque locations may be related to different ischemic lesion patterns.

BACKGROUND: Atherosclerosis of the internal carotid artery (ICA) is an important cause of ischemic stroke. Artery-to-artery embolism is the major stroke mechanism in patients with atherosclerotic carotid disease. This study hypothesized that the atherosclerotic ICA geometry and plaque location would be associated with lesion pattern in patients with acute ischemic stroke. METHODS: Ischemic stroke patients with symptomatic proximal ICA disease (> 50% diameter stenosis) were enrolled. The carotid plaque location was divided into high-apical and low-body types. The geometric parameters of the ICA (angles between arteries) were measured, and ischemic lesion patterns were classified according to the number, location, and size of the lesions. Factors associated with plaque location and lesion pattern, dichotomized by size, were investigated. RESULTS: Of the 93 acute ischemic stroke patients enrolled, 31 had high-apical and 62 had low-body plaques. Hyperlipidemia was more prevalent and the common carotid artery (CCA)-ICA angle was wider (167.7 ± 10.4° vs 162.3 ± 9.8°, p = 0.019) in patients with low-body than high-apical plaques. Low-body plaques were more frequently associated with small scattered or cortical lesions (54.8% vs. 32.3%, p = 0.040), whereas high-apical plaques were more frequently associated with large lesions having additional lesions (38.7% vs. 11.3%, p = 0.002). The presence of low-body plaques (odds ratio: 3.106, 95% confidence interval: 1.105-8.728, p = 0.032) was independently associated with the small lesion-only pattern. CONCLUSIONS: Low-body plaques are more frequently associated with small scattered lesions, whereas high-apical plaques are more frequently associated with large lesions having additional lesions. A wide CCA-ICA angle is associated with low-body plaque of the carotid artery.

Diagnostic Performance of a Combination of Shear Wave Elastography and B-Mode Ultrasonography in Differentiating Benign From Malignant Thyroid Nodules.

OBJECTIVES: This study was conducted to compare clinicopathologic and radiologic factors between benign and malignant thyroid nodules and to evaluate the diagnostic performance of shear wave elastography (SWE) combined with B-mode ultrasonography (US) in differentiating malignant from benign thyroid nodules. METHODS: This retrospective study included 92 consecutive patients with 95 thyroid nodules examined on B-mode US and SWE before US-guided fine-needle aspiration biopsy or surgical excision. B-mode US findings (composition, echogenicity, margin, shape, and calcification) and SWE elasticity parameters (maximum [Emax], mean, minimum, and nodule-to-normal parenchymal ratio of elasticity) were reviewed and compared between benign and malignant thyroid nodules. The diagnostic performance of B-mode US and SWE for predicting malignant thyroid nodules was analyzed. The optimal cutoff values of elasticity parameters for identifying malignancy were determined. Diagnostic performance was compared between B-mode US only, SWE only, and the combination of B-mode US with SWE. RESULTS: On multivariate logistic regression analysis, age (odds ratio [OR], 0.90; P=0.028), a taller-than-wide shape (OR, 11.3; P=0.040), the presence of calcifications (OR, 15.0; P=0.021), and Emax (OR, 1.22; P=0.021) were independent predictors of malignancy in thyroid nodules. The combined use of B-mode US findings and SWE yielded improvements in sensitivity, the positive predictive value, the negative predictive value, and accuracy compared with the use of B-mode US findings only, but with no statistical significance. CONCLUSION: When SWE was combined with B-mode US, the diagnostic performance was better than when only B-mode US was used, although the difference was not statistically significant.

Incidental Microaneurysms During Microvascular Surgery: Incidence, Treatment, and Significance.

BACKGROUND: Although new imaging tools have been developed for the detection of smaller aneurysms, angiographically negative microaneurysms are still encountered during cerebral microsurgery. Currently, only limited information regarding incidence and efficacy of treatment of these microaneurysms is available. METHODS: We investigated the incidence and treatment of incidental microaneurysms (IMAs) in the last 5 years. IMAs are unidentifiable and invisible on preoperative angiography, but are detected during microvascular surgery. The inclusion criteria were aneurysm cases treated with microsurgery via transsylvian approaches, and those undergoing preoperative digital subtraction angiography. RESULTS: This study enrolled 484 surgical cases (248 cases of subarachnoid hemorrhage and 236 cases of unruptured aneurysms) in 460 patients, and 33 tiny aneurysms were found in 31 operative cases (6.4% incidence per operation). The most typical type was located on another branching site of the middle cerebral artery found during neck clipping of the middle cerebral artery bifurcation aneurysm. A patient with multiple aneurysms presented a statistically significant risk (375/78 vs. 15/16; P < 0.001) of IMA identification. IMAs were treated by clipping and wrapping in 18 and 15 cases, respectively, without complications. CONCLUSIONS: This study revealed a 6.4% incidence of IMAs; however, this could be underestimated because of the limited range of inspection. Early detection of an IMA through careful inspection during microvascular surgery could be beneficial, especially in patients with multiple aneurysms.

Clinicoradiological Features of Recurrent Meningioma With High Grade Transformation.

BACKGROUND/AIM: A minority of grade I meningiomas (MG1s) recur after surgical resection and their progression is associated with high grade transformation (HGT). This study aimed to characterize the clinicoradiological features of recurrent MGs (RMG) with HGT. PATIENTS AND METHODS: We identified 17 patients diagnosed with MG1 who then underwent surgery for RMG. Patients were categorized into HGT group vs. non-HGT (nHGT) group based on RMG histological grade and clinicoradiological features were comparatively analyzed. RESULTS: HGT was observed in 41.4% of RMGs. Original tumor size was larger in the HGT group and recurrence time interval was shorter. Following recurrence, 57.1% in the HGT group experienced further disease progression, compared to 22.2% in the nHGT group. CONCLUSION: A considerable HGT rate in RMGs developed after MG1 was observed. Although HGT was not distinguished from nHGT by radiological features, HGT in RMG was associated with larger initial tumor size and shorter recurrence time interval.

Improvement diagnostic accuracy of sinusitis recognition in paranasal sinus X-ray using multiple deep learning models.

BACKGROUND: Sinus X-ray imaging is still used in the initial evaluation of paranasal sinusitis, which is diagnosed by the opacification or air/fluid level in the sinuses and best seen in the Waters' view of the paranasal sinus (PNS). The objective of this study was to investigate the feasibility of recognizing the maxillary sinusitis features using PNS X-ray images, as well as to propose the most effective method of determining a reasonable consensus using multiple deep learning models. METHODS: A total of 4,860 patients, which included 2,430 normal and maxillary sinusitis subjects each, underwent Waters' view PNS X-ray scan. The datasets were randomly split into training (70%), validation (15%), and test (15%) subsets. We implemented a majority decision algorithm to determine a reasonable consensus using three multiple convolutional neural network (CNN) models: VGG-16, VGG-19, and ResNet-101. The performance of sinusitis detection was evaluated with quantitative accuracy (ACC) and activation maps. RESULTS: We compared the results of our approaches with ACC and activation maps. ACC [and area under the curve (AUC)] of the internal test dataset was evaluated as 87.4% (0.891), 90.8% (0.891), 93.7% (0.937), and 94.1% (0.948) for VGG-16, VGG-19, ResNet-101, and the majority decision, respectively. ACC (and AUC) of the external test dataset was evaluated as 87.58% (0.877), 87.58% (0.877), 92.12% (0.929), and 94.12% (0.942) for VGG-16, VGG-19, ResNet-101, and the majority decision, respectively. Majority decision algorithms can detect missing and correct lesions using a compensation function of the majority decision. CONCLUSIONS: The majority decision algorithm showed high accuracy and significantly more accurate lesion detection compared with those of individual CNN models. The proposed deep learning method with PNS X-ray images can be used as an adjunct to classify maxillary sinusitis.