Published

Abstract
Objective: This study developed a diagnostic tool combining machine learning (ML) segmentation and radiomic texture analysis (RTA) for bone density screening using chest low-dose computed tomography (LDCT).
Methods: A total of 197 patients who underwent LDCT followed by dual-energy X-ray absorptiometry were analyzed. First, an autosegmentation model was trained using LDCT to delineate the thoracic vertebral body (VB). Second, a two-level classifier was developed using radiomic features extracted from VBs for the hierarchical pairwise classification of each patient’s bone status. All the patients were initially classified as either normal or abnormal, and all patients with abnormal bone density were then subdivided into an osteopenia group and an osteoporosis group. The performance of the classifier was evaluated through fivefold cross-validation.
Results: The model for automated VB segmentation achieved a Sorenson-Dice coefficient of 0.87 ± 0.01. Furthermore, the area under the receiver operating characteristic curve scores for the two-level classifier were 0.96 ± 0.01 for detecting abnormal bone density (accuracy = 0.91 ± 0.02; sensitivity = 0.93 ± 0.03; specificity = 0.89 ± 0.03) and 0.98 ± 0.01 for distinguishing osteoporosis (accuracy = 0.94 ± 0.02; sensitivity = 0.95 ± 0.03; specificity = 0.93 ± 0.03). The testing prediction accuracy levels for the first- and second-level classifiers were 0.92 ± 0.04 and 0.94 ± 0.05, respectively. The overall testing prediction accuracy of our method was 0.90 ± 0.05.
Conclusion: The combination of ML segmentation and RTA for automated bone density prediction based on LDCT scans is a feasible approach that could be valuable for osteoporosis screening during lung cancer screening.
Key points: • This study developed an automatic diagnostic tool combining machine learning-based segmentation and radiomic texture analysis for bone density screening using chest low-dose computed tomography. • The developed method enables opportunistic screening without quantitative computed tomography or a dedicated phantom. • The developed method could be integrated into the current clinical workflow and used as an adjunct for opportunistic screening or for patients who are ineligible for screening with dual-energy X-ray absorptiometry.
Keywords: Bone density; Machine learning; Osteoporosis; Radiomics.

Abstract
Background: Diffusion tensor imaging (DTI) biomarkers can be used to quantify microstructural changes in the cerebral white matter (WM) following injury.
Objectives: This prospective single-center study aimed to evaluate whether atlas-based DTI-derived metrics obtained within 1 week after stroke can predict the motor outcome at 3 months.
Methods: Forty patients with small acute stroke (2-7 days after onset) involving the corticospinal tract were included. Each patient underwent magnetic resonance imaging (MRI) within 1 week and at 3 months after stroke, and the changes based on DTI-derived metrics were compared by performing WM tract atlas-based quantitative analysis.
Results: A total of 40 patients were included, with median age 63.5 years and a majority of males (72.5%). Patients were classified into good-prognosis group (mRS 0-2, n = 27) and poor-prognosis group (mRS 3-5, n = 13) by outcome. The median (25th-75th percentile) of MD (0.7 (0.6-0.7) vs. 0.7 (0.7-0.8); p = 0.049) and AD (0.6 (0.5, 0.7) vs. 0.7 (0.6, 0.8); p = 0.023) ratios within 1 week were significantly lower in the poor-prognosis group compared to the good-prognosis group. The ROC curve of the combined DTI-derived metrics model showed comparable Youden index (65.5% vs. 58.4%-65.4%) and higher specificity (96.3% vs. 69.2%-88.5%) compared to clinical indexes. The area under the ROC curve of the combined DTI-derived metrics model is comparable to those of the clinical indexes (all p > 0.1) and higher than those of the individual DTI-derived metrics parameters.
Conclusions: Atlas-based DTI-derived metrics at acute stage provide objective information for prognosis prediction of patients with ischemic or lacunar stroke.
Keywords: Corticospinal tracts; diffusion tensor imaging; ischemic stroke; motor function; prognosis.

Abstract
Concussion, also known as mild traumatic brain injury (mTBI), commonly causes transient neurocognitive symptoms, but in some cases, it causes cognitive impairment, including working memory (WM) deficit, which can be long-lasting and impede a patient’s return to work. The predictors of long-term cognitive outcomes following mTBI remain unclear, because abnormality is often absent in structural imaging findings. Previous studies have demonstrated that WM functional activity estimated from functional magnetic resonance imaging (fMRI) has a high sensitivity to postconcussion WM deficits and may be used to not only evaluate but guide treatment strategies, especially targeting brain areas involved in postconcussion cognitive decline. The purpose of the study was to determine whether machine learning-based models using fMRI biomarkers and demographic or neuropsychological measures at the baseline could effectively predict the 1-year cognitive outcomes of concussion. We conducted a prospective, observational study of patients with mTBI who were compared with demographically matched healthy controls enrolled between September 2015 and August 2020. Baseline assessments were collected within the first week of injury, and follow-ups were conducted at 6 weeks, 3 months, 6 months, and 1 year. Potential demographic, neuropsychological, and fMRI features were selected according to their significance of correlation with the estimated changes in WM ability. The support vector machine classifier was trained using these potential features and estimated changes in WM between the predefined time periods. Patients demonstrated significant cognitive recovery at the third month, followed by worsened performance after 6 months, which persisted until 1 year after a concussion. Approximately half of the patients experienced prolonged cognitive impairment at the 1-year follow up. Satisfactory predictions were achieved for patients whose WM function did not recover at 3 months (accuracy = 87.5%), 6 months (accuracy = 83.3%), and 1 year (accuracy = 83.3%) and performed worse at the 1-year follow-up compared to the baseline assessment (accuracy = 83.3%). This study demonstrated the feasibility of personalized prediction for long-term postconcussive WM outcomes based on baseline fMRI and demographic features, opening a new avenue for early rehabilitation intervention in selected individuals with possible poor long-term cognitive outcomes.
Keywords: concussion; long-term cognitive outcome; mild traumatic brain injury; personalized prediction; support vector machine classifier; working memory.

Abstract
Considering the potential chondrotoxic effects of lidocaine, this retrospective study aimed to examine whether ultrasound-guided hydrodilatation without concurrent lidocaine infusion can still provide comparable treatment benefits for patients with adhesive capsulitis (AC). Outpatient data from 104 eligible AC patients who received ultrasound-guided hydrodilatation between May 2016 and April 2021 were reviewed. A total of 59 patients received hydrodilatation with diluted corticosteroid only, while 45 patients received treatment with mixed, diluted corticosteroid and 1% lidocaine. The overall treatment outcome was documented as the percentage of clinical improvement, ranging from 0% to 100% compared to baseline, and it was ranked into poor, moderate and good treatment outcomes. The results show no significant group-wise difference in demographics, overall treatment outcome, and number of hydrodilatations, while most patients showed moderate and good treatment outcomes. Patients with lidocaine infusion did not show greater treatment benefit. Our results suggest that ultrasound-guided hydrodilatation without concurrent lidocaine infusion can still deliver good treatment benefits for AC patients, and the findings are supportive of a modified approach toward careful intra-articular local anesthetic use during management of AC in the primary care setting.
Keywords: adhesive capsulitis; chondrotoxicity; intra-articular lidocaine; ultrasound-guided hydrodilatation.

Abstract
The functional connectivity of the default-mode network (DMN) monitored by functional magnetic resonance imaging (fMRI) in Alzheimer’s disease (AD) patients has been found weaker than that in healthy participants. Since breathing and heart beating can cause fluctuations in the fMRI signal, these physiological activities may affect the fMRI data differently between AD patients and healthy participants. We collected resting-state fMRI data from AD patients and age-matched healthy participants. With concurrent cardiac and respiratory recordings, we estimated both physiological responses phase-locked and non-phase-locked to heart beating and breathing. We found that the cardiac and respiratory physiological responses in AD patients were 3.00 ± 0.51 s and 3.96 ± 0.52 s later (both p < 0.0001) than those in healthy participants, respectively. After correcting the physiological noise in the resting-state fMRI data by population-specific physiological response functions, the DMN estimated by seed-correlation was more localized to the seed region. The DMN difference between AD patients and healthy controls became insignificant after suppressing physiological noise. Our results indicate the importance of controlling physiological noise in the resting-state fMRI analysis to obtain clinically related characterizations in AD. Keywords: Respiratory response function; cardiac response function; classification; fMRI; network; physiological noise; resting-state.

Abstract
Objectives: To compare diffusion tensor (DT)-derived indices from the thalamic nuclei and cerebrospinal fluid (CSF) hydrodynamic parameters for the prediction of gait responsiveness to the CSF tap test in early iNPH patients.
Methods: In this study, 22 patients with iNPH and 16 normal controls were enrolled with the approval of an institutional review board. DT imaging and phase-contrast magnetic resonance imaging were performed in patients and controls to determine DT-related indices of the sensorimotor-related thalamic nuclei and CSF hydrodynamics. Gait performance was assessed in patients using gait scale before and after the tap test. The Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis were applied to compare group differences between patients and controls and assess the predictive performance of gait responsiveness to the tap test in the patients.
Results: Fractional anisotropy (FA) and axial diffusivity showed significant increases in the ventrolateral (VL) and ventroposterolateral (VPL) nuclei of the iNPH group compared with those of the control group (p < 0.05). The predictions of gait responsiveness of ventral thalamic FA alone (area under the ROC curve [AUC] < 0.8) significantly outperformed those of CSF hydrodynamics alone (AUC < 0.6). The AUC curve was elevated to 0.812 when the CSF peak systolic velocity and FA value were combined for the VPL nucleus, yielding the highest sensitivity (0.769) and specificity (0.778) to predict gait responses. Conclusions: Combined measurements of sensorimotor-related thalamic FA and CSF hydrodynamics can provide potential biomarkers for gait response to the CSF tap test in patients with iNPH.
Key points: • Ventrolateral and ventroposterolateral thalamic FA may predict gait responsiveness to tap test. • Thalamic neuroplasticity can be assessed through DTI in idiopathic normal-pressure hydrocephalus. • Changes in the CST associated with gait control could trigger thalamic neuroplasticity. • Activities of sensorimotor-related circuits could alter in patients with gait disturbance. • Management of patients with iNPH could be more appropriate.
Keywords: Diffusion tensor imaging; Gait; Hydrocephalus, normal pressure; Neuronal plasticity; Thalamus.

Abstract
We designed and synthesized novel theranostic nanoparticles that showed the considerable potential for clinical use in targeted therapy, and non-invasive real-time monitoring of tumors by MRI. Our nanoparticles were ultra-small with superparamagnetic iron oxide cores, conjugated to erlotinib (FeDC-E NPs). Such smart targeted nanoparticles have the preference to release the drug intracellularly rather than into the bloodstream, and specifically recognize and kill cancer cells that overexpress EGFR while being non-toxic to EGFR-negative cells. MRI, transmission electron microscopy and Prussian blue staining results indicated that cellular uptake and intracellular accumulation of FeDC-E NPs in the EGFR overexpressing cells was significantly higher than those of the non-erlotinib-conjugated nanoparticles. FeDC-E NPs inhibited the EGFR-ERK-NF-κB signaling pathways, and subsequently suppressed the migration and invasion capabilities of the highly invasive and migrative CL1-5-F4 cancer cells. In vivo tumor xenograft experiments using BALB/c nude mice showed that FeDC-E NPs could effectively inhibit the growth of tumors. T2-weighted MRI images of the mice showed significant decrease in the normalized signal within the tumor post-treatment with FeDC-E NPs compared to the non-targeted control iron oxide nanoparticles. This is the first study to use erlotinib as a small-molecule targeting agent for nanoparticles.

Abstract
OBJECTIVE. The purpose of this article is to use a mechanism-based approach to review the neuroimaging findings of abusive head trauma to infants. Advanced neuroimaging provides insights into not only the underlying mechanisms of craniocerebral injuries but also the long-term prognosis of brain injury for children on whom these injuries have been inflicted.
CONCLUSION. Knowledge of the traumatic mechanisms, the key neuroimaging findings, and the implications of functional imaging findings should help radiologists characterize the underlying causes of the injuries inflicted, thereby facilitating effective treatment.

Abstract
The effects and possible underlying mechanism of curcumin combined with radiation in human hepatocellular carcinoma (HCC) cells in vitro were evaluated. The effects of curcumin, radiation, and combination of both on cell viability, apoptosis, NF-κB activation, and expressions of NF-κB downstream effector proteins were investigated with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), NF-κB reporter gene, mitochondrial membrane potential (MMP), electrophoretic mobility shift (EMSA), and Western blot assays in Huh7-NF-κB-luc2, Hep3B, and HepG2 cells. Effect of I kappa B alpha mutant (IκBαM) vector, a specific inhibitor of NF-κB activation, on radiation-induced loss of MMP was also evaluated. Results show that curcumin not only significantly enhances radiation-induced cytotoxicity and depletion of MMP but inhibits radiation-induced NF-κB activity and expressions of NF-κB downstream proteins in HCC cells. IκBαM vector also shows similar effects. In conclusion, we suggest that curcumin augments anticancer effects of radiation via the suppression of NF-κB activation.

Abstract
Recent advances in the treatment of cerebral gliomas have increased the demands on noninvasive neuroimaging for the diagnosis, therapeutic planning, tumor monitoring, and patient outcome prediction. In the meantime, improved magnetic resonance (MR) imaging techniques have shown much potentials in evaluating the key pathological features of the gliomas, including cellularity, invasiveness, mitotic activity, angiogenesis, and necrosis, hence, further shedding light on glioma grading before treatment. In this paper, an update of advanced MR imaging techniques is reviewed, and their potential roles as biomarkers of tumor grading are discussed.

Abstract
Background and purpose: Brain enhancement on contrast-enhanced T1-weighted imaging (CET1-WI) after ischemic stroke is generally accepted as an indicator of the blood-brain barrier disruption. However, this phenomenon usually starts to become visible at the subacute phase. The purpose of this study was to evaluate the time-course profiles of K(trans), cerebral blood volume (vp), and CET1-WI with early detection of blood-brain barrier changes on K(trans) maps and their role for prediction of subsequent hemorrhagic transformation in acute middle cerebral arterial infarct.
Methods: Twenty-six patients with acute middle cerebral arterial stroke and early spontaneous reperfusion, whose MR images were obtained at predetermined stroke stages, were included. T2*-based MR perfusion-weighted images were acquired using the first-pass pharmacokinetic model to derive K(trans) and vp. Parenchymal enhancement observed on maps of K(trans), vp, and CET1-WI at each stage was compared. Association among these measurements and hemorrhagic transformation was analyzed.
Results: K(trans) map showed significantly higher parenchymal enhancement in ischemic parenchyma as compared with that of vp map and CET1-WI at early stroke stages (P<0.05). The increased K(trans) at acute stage was not associated with parenchymal enhancement in CET1-WI at the same stage. Parenchymal enhancement in CET1-WI started to occur at the late subacute stage and tended to be luxury reperfusion-dependent. Patients with hemorrhagic transformation showed higher mean K(trans) values as compared with patients without hemorrhagic transformation (P=0.02). Conclusions: Postischemic brain enhancement on routine CET1-WI seems to be closely related to the luxury reperfusion at the late subacute stage and is not dependent on microvascular permeability changes at the acute stage.
Keywords: Ktrans; blood–brain barrier; parenchymal enhancement.

Abstract
Objectives: To investigate the ability of susceptibility-weighted imaging (SWI) to predict stroke evolution in comparison with perfusion-weighted imaging (PWI).
Methods: In a retrospective analysis of 15 patients with non-lacunar ischaemic stroke studied no later than 24 h after symptom onset, we used the Alberta Stroke Program Early CT Score (ASPECTS) to compare lesions on initial diffusion-weighted images (DWI), SWI, PWI and follow-up studies obtained at least 5 days after symptom onset. The National Institutes of Health Stroke Scale scores at entry and stroke risk factors were documented. The clinical-DWI, SWI-DWI and PWI-DWI mismatches were calculated.
Results: SWI-DWI and mean transit time (MTT)-DWI mismatches were significantly associated with higher incidence of infarct growth (P = 0.007 and 0.028) and had similar ability to predict stroke evolution (P = 1.0). ASPECTS values on initial DWI, SWI and PWI were significantly correlated with those on follow-up studies (P ≤ 0.026) but not associated with infarct growth. The SWI ASPECTS values were best correlated with MTT ones (ρ = 0.8, P < 0.001). Conclusions: SWI is an alternative to PWI to assess penumbra and predict stroke evolution. Further prospective studies are needed to evaluate the role of SWI in guiding thrombolytic therapy. Key Points • SWI can provide perfusion information comparable to MTT • SWI-DWI mismatch can indicate ischaemic penumbra • SWI-DWI mismatch can be a predictor for stroke evolution.

Abstract
Susceptibility-weighted imaging (SWI) is commonly used to diagnose cerebral hemorrhage, calcification, and other T2* lesions. Its role in the detection of cerebral thromboemboli has been suggested for emboli of the anterior division of the middle cerebral artery (MCA). The purpose of our study was to determine SWI’s accuracy and sensitivity in detection of all sites of cerebral thromboemboli, not just MCA emboli. Two neuroradiologists retrospectively reviewed consecutive MRI brain examinations with SWI for cerebral thromboemboli in 100 patients with clinical suspicion for stroke determined by the NIH Stroke Scale (NIHSS) score. FLAIR, MRA, CT, and catheter angiography were reviewed for thromboemboli in the same patients. Thromboembolic sites included: the internal carotid artery (ICA) terminus, anterior MCA, posterior MCA, any other cerebral artery, or if not present. The exclusion criteria included: no magnetic resonance angiogram (MRA) or catheter angiogram for comparison, lack of restricted diffusion, lacunar infarcts, and the presence of massive hemorrhage. The accuracy, sensitivity, and specificity of each imaging modality were determined. Twenty-four patients were excluded based on the aforementioned criteria. Cerebral thromboemboli were identified in 35 of the remaining 76 patients. Of the 35 patients with thromboemboli, 30 were identified on SWI. FLAIR detected 22/35 emboli, MRA 30/33, CT 18/35, and catheter angiography 12/12. The accuracies for SWI, FLAIR, and CT were 97%, 84%, and 74%, respectively. The sensitivities for SWI, FLAIR, and CT were 85%, 61%, and 52%, respectively. The specificities for SWI, FLAIR, and CT were 100%, 98%, and 93%, respectively. There is an adjunctive role of SWI to identify cerebral thromboemboli in patients with acute infarction. SWI is superior to FLAIR and CT, and complementary to MRA and catheter angiography in emboli detection. This study supports SWI detection of MCA emboli, but also emphasizes its utility in emboli detection of other arteries based on a high accuracy and sensitivity.

Abstract
We describe findings suggestive of brain death on susceptibility-weighted imaging. We retrospectively reviewed brain magnetic resonance (MR) images of 15 patients who had cardiac arrest and found four cases with evidence of brain death. We then reviewed susceptibility-weighted imaging (SWI) findings on these cases. SWI images in the four cases with brain death showed deoxygenated blood in intracranial arteries. This preliminary result suggests that SWI may be used to diagnose brain death.

Abstract
Magnetic resonance susceptibility-weighted imaging (SWI), a novel 3D gradient echo MRI sequence exploiting phase and magnitude data for post-processing, is able to detect blood, iron, calcification and deoxygenated hemoglobin content for brain. SWI has been widely used to evaluate cerebral vascular disorders, trauma, multiple sclerosis, and tumors. We have also used SWI to evaluate acute stroke patients to identify thrombosis and possible penumbra. The acquisition was too long for examining acute stroke patients due to motion from agitation and mental changes. We have altered the parameters of phase resolution, voxel size, matrix size and partial Fourier to shorten the acquisition time to improve the diagnostic quality of SWI for acute stroke patients. The result was to reduce the acquisition time from 3:46 min to 2:14 min thereby providing a helpful tool in screening stroke patients.

Abstract
We aimed to demonstrate the complications of carotid-cavernous fistula (CCF) and their correlation with venous hypertension. From August 2000 to April 2008 we performed more than 2400 catheter angiographic procedures. Among those, six unusual cases presented acute complications of CCF. The presented complications of CCF from our cases showed a possible correlation with venous hypertension. With the experiences from our cases, venous hypertension may complicate CCF with a poor prognosis. The condition should be carefully evaluated and if present prompt treatment is necessary.

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