Multiscale brain age prediction reveals region-specific accelerated brain aging in Parkinson's disease.

Brain biological age, which measures the aging process in the brain using neuroimaging data, has been used to assess advanced brain aging in neurodegenerative diseases, including Parkinson disease (PD). However, assuming that whole brain degeneration is uniform may not be sufficient for assessing the complex neurodegenerative processes in PD. In this study we constructed a multiscale brain age prediction models based on structural MRI of 1240 healthy participants. To assess the brain aging patterns using the brain age prediction model, 93 PD patients and 91 healthy controls matching for sex and age were included. We found increased global and regional brain age in PD patients. The advanced aging regions were predominantly noted in the frontal and temporal cortices, limbic system, basal ganglia, thalamus, and cerebellum. Furthermore, region-level rather than global brain age in PD patients was associated with disease severity. Our multiscale brain age prediction model could aid in the development of objective image-based biomarkers to detect advanced brain aging in neurodegenerative diseases.

Human transcriptome array analysis and diffusion tensor imaging in attention-deficit/hyperactivity disorder.

The mRNA markers identified using microarray assay and diffusion tensor magnetic resonance imaging (DTI) were applied to elucidate the pathophysiology of attention-deficit hyperactivity disorder (ADHD). First, we obtained total RNA from leukocytes from three children with ADHD and three healthy controls for analysis with microarray assays. Subsequently, we applied real-time quantitative polymerase chain reaction (qRT‒PCR) assays to validate the differential expression of 7 genes (COX7B, CYCS, TFAM, UTP14A, ZNF280C, IFT57 and NDUFB5) between 130 ADHD patients and 70 controls, and we built an ADHD prediction model based on the ΔCt values of aforementioned seven genes (AUROC = 0.98). Finally, in a validation group (28 patients with ADHD and 27 healthy controls), mRNA expression of the above seven genes also significantly differentiated ADHD patients from controls (AUROC value = 0.91). The DTI analysis showed increased fractional anisotropy (FA) of the forceps minor, superior corona radiata, posterior corona radiata and anterior corona radiata in ADHD patients. Moreover, the FA of the right superior corona radiata tract was positively correlated with ΔCt levels of the COX7B gene and the IFT57 gene. The results shed a new light on a genetic profile of ADHD that may help in deciphering the white matter microstructural features in disease pathogenesis.

Comparison of contraction-type and noncontraction-type lymphatic vessels in lymphaticovenous anastomosis for cancer-related unilateral lower limb lymphedema: a retrospective cohort propensity-score-matched outcome analysis.

BACKGROUND: Contraction-type lymphatic vessels (LV) are considered suboptimal for lymphaticovenous anastomosis (LVA). However, despite these pathological changes, their functionality and link to outcomes have not been fully elucidated. The aim of this study was to determine the impact on outcomes when contraction-type LVs were used for LVA compared to the noncontraction-type (normal + ectatic) counterpart for treating lower limb lymphedema. STUDY DESIGN: Eighty-three patients with gynecologic cancer-related unilateral lower-limb lymphedema who underwent LVA as their primary treatment were enrolled in this study. The study group included 20 patients who used only contraction-type LVs. An additional 63 patients (control group) received noncontraction-type LVs only. Patients with a history of LVA, liposuction, or excisional therapy were excluded. Patient characteristics, intraoperative findings, functional parameters, and pre-LVA and post-LVA volume changes were recorded and matched using propensity scores. The primary endpoint was the volume change at 6/12 months after LVA. RESULTS: After matching, 20 patients were included in each group. All parameters were matched, except that the study group still had a significantly inferior indocyanine green (ICG)-positive ratio, lymph flow-positive ratio, and washout-positive ratios ( P <0.001, P =0.003, and P <0.001, respectively) when compared to the control group after matching. However, at 1-year follow-up, the postoperative percentage volume reduction was comparable between the groups ( P= 0.619). CONCLUSION: The use of contraction-type LVs for LVA is encouraged when no other LVs are available.

Association of Autonomic Symptom Burden with Sudden Sensorineural Hearing Loss.

OBJECTIVE: To investigate the autonomic symptom burden in patients with sudden sensorineural hearing loss (SSNHL) and its association with the severity and prognosis. STUDY DESIGN: Observational prospective study. SETTING: Tertiary academic medical center. METHODS: Patients diagnosed with SSNHL at a single medical center completed the COMPASS 31 questionnaire, which assesses dysautonomia across 6 domains with 31 questions. A total COMPASS 31 score was calculated by summing the scores from each weighted domain. The treatment outcome was evaluated by the percentage of recovery, calculated as the hearing gain in pure tone average (PTA) after treatment divided by the pretreatment PTA difference between the 2 ears. We defined poor recovery as a percentage of recovery <80%. RESULTS: A total of 63 SSNHL patients were included. The mean COMPASS 31 score was 23.4 (SD 14). Patients with poor recovery had significantly higher COMPASS 31 scores than those with good recovery (mean 26.4 [SD 14.4] vs 16.9 [SD 10.4]; 95% confidence interval [CI] 2-17). There was a negative association between COMPASS 31 score and both hearing gain (r = -.323, 95% CI -0.082 to -0.529) and percentage of recovery (r = -.365, 95% CI -0.129 to -0.562). Multivariate analyses of independent factors indicate that patients with higher COMPASS 31 scores had a greater risk for poor recovery (OR 1.06 [95% CI 1.003-1.117]). CONCLUSION: This study highlights the association between autonomic symptom burden and poor hearing outcomes in SSNHL patients. The findings underscore the importance of evaluating autonomic function during the treatment of SSNHL.

Radiofrequency ablation for thyroid Bethesda III nodules: preliminary results.

Purpose: The purpose of this study was to evaluate the feasibility of radiofrequency ablation (RFA) for thyroid nodules with cytological atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS, Bethesda III). Materials and methods: A total of 28 adults presenting with 30 initial Bethesda III nodules underwent thyroid RFA at a single medical center. Thyroid nodules with Bethesda IV or V according to the second aspiration were excluded. All RFA procedures were performed using the free-hand, 'moving-shot' technique under local anesthesia. Clinical features and demographics, RFA details, nodule volume reduction rate (VRR), and complications were analyzed. Results: The mean age of patients was 47.6 years, 82.1% of whom were females. Mean nodule volumes at pre-RFA, and at 6 months and 12 months post-RFA were 7.92, 2.42, and 1.25 mL, respectively, with a VRR of 77.9% at 6 months, and 87.4% at 12 months. Post-RFA complications were noted in two patients, one with transient vocal cord palsy and another with isthmus minor rupture. Conclusion: RFA may be another safe alternative except for active surveillance or surgical excision for AUS/FLUS nodules with low-suspicion Thyroid Imaging Reporting and Data System features for patients who are unsuitable or strongly refuse surgery. Long-term results remain uncertain, thus further follow-up study is necessary.

Factors Influencing a Favorable Outcome for RFA of Huge Benign Thyroid Nodules: Preliminary Results and Short-Term Evaluation.

Objective: This study aimed to investigate potentially favorable factors influencing the therapeutic success of radiofrequency ablation (RFA) of huge benign thyroid nodules (BTNs) (volume >100 ml) and to evaluate the feasibility of RFA as an alternative treatment modality for patients unable or unwilling to undergo surgery. Methods: This retrospective study evaluated a total of 868 patients, of which 22 patients had huge BTNs who underwent ultrasound-guided moving shot RFA treatment between May 2017 and January 2022. The huge BTNs were categorized into two groups according to a post-RFA treatment volume reduction ratio (VRR) of >80% and <80% at 6 months. Factors influencing these huge BTNs were reviewed, analyzed, and correlated with treatment effectiveness between the two groups. Results: The factors influencing an effective VRR included huge BTNs located on the left side (OR 7.875, p = 0.03), predominant solid/spongiform nodules (OR 7.875, p = 0.03), and higher initial ablation rate (IAR) (p = 0.028). Multivariable logistic regression revealed predominant solid/spongiform nodule and the higher IAR were associated with the advanced VRR. Conclusion: RFA was effective at decreasing the volume of huge BTNs with an acceptable complication rate. The BTN characteristics correlated with a better VRR at the 6-month short-term follow-up were predominant solid/spongiform BTNs and those with the first time ablation treatment initial ablation rate. Nevertheless, regarding the higher regrowth rate of these groups of patients who may need to be treated more times, RFA can only be a feasible alternative treatment modality for patients unable or unwilling to undergo operation.

Radiofrequency ablation for thyroid Bethesda III nodules: preliminary results.

Purpose: The purpose of this study was to evaluate the feasibility of radiofrequency ablation (RFA) for thyroid nodules with cytological atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS, Bethesda III). Materials and methods: A total of 28 adults presenting with 30 initial Bethesda III nodules underwent thyroid RFA at a single medical center. Thyroid nodules with Bethesda IV or V according to the second aspiration were excluded. All RFA procedures were performed using the free-hand, 'moving-shot' technique under local anesthesia. Clinical features and demographics, RFA details, nodule volume reduction rate (VRR), and complications were analyzed. Results: The mean age of patients was 47.6 years, 82.1% of whom were females. Mean nodule volumes at pre-RFA, and at 6 months and 12 months post-RFA were 7.92, 2.42, and 1.25 mL, respectively, with a VRR of 77.9% at 6 months, and 87.4% at 12 months. Post-RFA complications were noted in two patients, one with transient vocal cord palsy and another with isthmus minor rupture. Conclusion: RFA may be another safe alternative except for active surveillance or surgical excision for AUS/FLUS nodules with low-suspicion Thyroid Imaging Reporting and Data System features for patients who are unsuitable or strongly refuse surgery. Long-term results remain uncertain, thus further follow-up study is necessary.

Electroencephalogram-Driven Machine-Learning Scenario for Assessing Impulse Control Disorder Comorbidity in Parkinson's Disease Using a Low-Cost, Custom LEGO-Like Headset.

Patients with Parkinson's disease (PD) may develop cognitive symptoms of impulse control disorders (ICDs) when chronically treated with dopamine agonist (DA) therapy for motor deficits. Motor and cognitive comorbidities critically increase the disability and mortality of the affected patients. This study proposes an electroencephalogram (EEG)-driven machine-learning scenario to automatically assess ICD comorbidity in PD. We employed a classic Go/NoGo task to appraise the capacity of cognitive and motoric inhibition with a low-cost, custom LEGO-like headset to record task-relevant EEG activity. Further, we optimized a support vector machine (SVM) and support vector regression (SVR) pipeline to learn discriminative EEG spectral signatures for the detection of ICD comorbidity and the estimation of ICD severity, respectively. With a dataset of 21 subjects with typical PD, 9 subjects with PD and ICD comorbidity (ICD), and 25 healthy controls (HC), the study results showed that the SVM pipeline differentiated subjects with ICD from subjects with PD with an accuracy of 66.3% and returned an around-chance accuracy of 53.3% for the classification of PD versus HC subjects without the comorbidity concern. Furthermore, the SVR pipeline yielded significantly higher severity scores for the ICD group than for the PD group and resembled the ICD vs. PD distinction according to the clinical questionnaire scores, which was barely replicated by random guessing. Without a commercial, high-precision EEG product, our demonstration may facilitate deploying a wearable computer-aided diagnosis system to assess the risk of DA-triggered cognitive comorbidity in patients with PD in their daily environment.

Modified gefitinib conjugated Fe3O4 NPs for improved delivery of chemo drugs following an image-guided mechanistic study of inner vs. outer tumor uptake for the treatment of non-small cell lung cancer.

Gefitinib (GEF) is an FDA-approved anti-cancer drug for the first-line treatment of patients with metastatic non-small cell lung cancer (NSCLC). However, the efficacy of anticancer drugs is limited due to their non-specificity, lower accumulation at target sites, and systemic toxicity. Herein, we successfully synthesized a modified GEF (mGEF) drug and conjugated to Iron oxide nanoparticles (Fe3O4 NPs) for the treatment of NSCLC via magnetic resonance (MR) image-guided drug delivery. A traditional EDC coupling pathway uses mGEF to directly conjugate to Fe3O4 NPs to overcom the drug leakage issues. As a result, we found in vitro drug delivery on mGEF- Fe3O4 NPs exhibits excellent anticancer effects towards the PC9 cells selectively, with an estimated IC 50 value of 2.0 µM. Additionally, in vivo MRI and PET results demonstrate that the NPs could accumulate in tumor-specific regions with localized cell growth inhibition. Results also revealed that outer tumor region exhibiting a stronger contrast than the tinner tumor region which may due necrosis in inner tumor region. In vivo biodistribution further confirms Fe3O4 NPs are more biocompatible and are excreated after the treatment. Overall, we believe that this current strategy of drug modification combined with chemical conjugation on magnetic NPs will lead to improved cancer chemotherapy as well as understanding the tumor microenvironments for better therapeutic outcomes.

Neuroplastic Changes Associated With Hybrid Exercise-Cognitive Training in Stroke Survivors With Mild Cognitive Decline: A Randomized Controlled Trial.

BACKGROUND: Exercise and cognitive training have been shown to induce neuroplastic changes and modulate cognitive function following stroke. However, it remains unclear whether hybridized exercise-cognitive training facilitates cortical activity and further influences cognitive function after stroke. OBJECTIVE: The study aimed to investigate the effects of 2 hybridized exercise-cognitive trainings on neuroplastic changes and behavioral outcomes in stroke survivors with mild cognitive decline. METHODS: This study was a single-blind randomized controlled trial. Stroke survivors were randomly assigned to 1 of 3 groups: (1) sequential exercise-cognitive training (SEQ), (2) dual-task exercise-cognitive training (DUAL), or (3) control group (CON). All groups underwent training 60 min per day, 3 days per week, for a total of 12 weeks. The primary outcome was the resting-state (RS) functional connectivity (FC) in functional magnetic resonance imaging. Secondary behavioral outcomes included cognitive and physical functions. RESULTS: After 12 weeks of training, patients in the SEQ group (n = 21) exhibited increased RS FC between the left occipital lobe and posterior cingulate gyrus with right parietal lobe, compared to the DUAL (n = 22) and CON (n = 20) groups. Additionally, patients in the DUAL group showed increased FC of the left temporal lobe. However, changes in behavioral outcome measures were non-significant among the 3 groups (all P's > .05). CONCLUSIONS: This study highlights the distinct neuroplastic mechanisms associated with 2 types of exercise-cognitive hybridized trainings. The pre-post functional magnetic resonance imaging measurements illustrated the time course of neural mechanisms for cognitive recovery in stroke survivors following different exercise-cognitive training approaches. Trial registration. NCT03230253.

Prediction of extranodal extension in head and neck squamous cell carcinoma by CT images using an evolutionary learning model.

BACKGROUND: Extranodal extension (ENE) in head and neck squamous cell carcinoma (HNSCC) correlates to poor prognoses and influences treatment strategies. Deep learning may yield promising performance of predicting ENE in HNSCC but lack of transparency and interpretability. This work proposes an evolutionary learning method, called EL-ENE, to establish a more interpretable ENE prediction model for aiding clinical diagnosis. METHODS: There were 364 HNSCC patients who underwent neck lymph node (LN) dissection with pre-operative contrast-enhanced computerized tomography images. All the 778 LNs were divided into training and test sets with the ratio 8:2. EL-ENE uses an inheritable bi-objective combinatorial genetic algorithm for optimal feature selection and parameter setting of support vector machine. The diagnostic performances of the ENE prediction model and radiologists were compared using independent test datasets. RESULTS: The EL-ENE model achieved the test accuracy of 80.00%, sensitivity of 81.13%, and specificity of 79.44% for ENE detection. The three radiologists achieved the mean diagnostic accuracy of 70.4%, sensitivity of 75.6%, and specificity of 67.9%. The features of gray-level texture and 3D morphology of LNs played essential roles in predicting ENE. CONCLUSIONS: The EL-ENE method provided an accurate, comprehensible, and robust model to predict ENE in HNSCC with interpretable radiomic features for expanding clinical knowledge. The proposed transparent prediction models are more trustworthy and may increase their acceptance in daily clinical practice.

Electroactive membrane fusion-liposome for increased electron transfer to enhance radiodynamic therapy.

Dynamic therapies have potential in cancer treatments but have limitations in efficiency and penetration depth. Here a membrane-integrated liposome (MIL) is created to coat titanium dioxide (TiO2) nanoparticles to enhance electron transfer and increase radical production under low-dose X-ray irradiation. The exoelectrogenic Shewanella oneidensis MR-1 microorganism presents an innate capability for extracellular electron transfer (EET). An EET-mimicking photocatalytic system is created by coating the TiO2 nanoparticles with the MIL, which significantly enhances superoxide anions generation under low-dose (1 Gy) X-ray activation. The c-type cytochromes-constructed electron channel in the membrane mimics electron transfer to surrounding oxygen. Moreover, the hole transport in the valence band is also observed for water oxidation to produce hydroxyl radicals. The TiO2@MIL system is demonstrated against orthotopic liver tumours in vivo.

Predicting new-onset post-stroke depression from real-world data using machine learning algorithm.

Introduction: Post-stroke depression (PSD) is a serious mental disorder after ischemic stroke. Early detection is important for clinical practice. This research aims to develop machine learning models to predict new-onset PSD using real-world data. Methods: We collected data for ischemic stroke patients from multiple medical institutions in Taiwan between 2001 and 2019. We developed models from 61,460 patients and used 15,366 independent patients to test the models' performance by evaluating their specificities and sensitivities. The predicted targets were whether PSD occurred at 30, 90, 180, and 365 days post-stroke. We ranked the important clinical features in these models. Results: In the study's database sample, 1.3% of patients were diagnosed with PSD. The average specificity and sensitivity of these four models were 0.83-0.91 and 0.30-0.48, respectively. Ten features were listed as important features related to PSD at different time points, namely old age, high height, low weight post-stroke, higher diastolic blood pressure after stroke, no pre-stroke hypertension but post-stroke hypertension (new-onset hypertension), post-stroke sleep-wake disorders, post-stroke anxiety disorders, post-stroke hemiplegia, and lower blood urea nitrogen during stroke. Discussion: Machine learning models can provide as potential predictive tools for PSD and important factors are identified to alert clinicians for early detection of depression in high-risk stroke patients.

Latanoprost-associated cystoid macular edema in a patient with phakic eyes.

Here, we report a case of bilateral cystoid macular edema (CME) in a woman with phakic eyes after 22 years of latanoprost use. Optical coherence tomography revealed multiple intraretinal cysts, and fluorescein angiography revealed characteristic petaloid dye leakage from the perifoveal capillaries. A cause-effect relationship was suspected when CME resolved after switching from latanoprost to dorzolamide, as confirmed by positive rechallenge and dechallenge tests. Since prostaglandin analog-induced CME has only been reported in patients with pseudophakic, aphakic, or phakic eyes with retinal conditions predisposing to macular edema, this seems to be the first reported case of latanoprost-induced CME in a patient with phakic eyes without retinal risk factors.

DGA3-Net: A parameter-efficient deep learning model for ASPECTS assessment for acute ischemic stroke using non-contrast computed tomography.

Detecting the early signs of stroke using non-contrast computerized tomography (NCCT) is essential for the diagnosis of acute ischemic stroke (AIS). However, the hypoattenuation in NCCT is difficult to precisely identify, and accurate assessments of the Alberta Stroke Program Early CT Score (ASPECTS) are usually time-consuming and require experienced neuroradiologists. To this end, this study proposes DGA3-Net, a convolutional neural network (CNN)-based model for ASPECTS assessment via detecting early ischemic changes in ASPECTS regions. DGA3-Net is based on a novel parameter-efficient dihedral group CNN encoder to exploit the rotation and reflection symmetry of convolution kernels. The bounding volume of each ASPECTS region is extracted from the encoded feature, and an attention-guided slice aggregation module is used to aggregate features from all slices. An asymmetry-aware classifier is then used to predict stroke presence via comparison between ASPECTS regions from the left and right hemispheres. Pre-treatment NCCTs of suspected AIS patients were collected retrospectively, which consists of a primary dataset (n = 170) and an external validation dataset (n = 90), with expert consensus ASPECTS readings as ground truth. DGA3-Net outperformed two expert neuroradiologists in regional stroke identification (F1 = 0.69) and ASPECTS evaluation (Cohen's weighted Kappa = 0.70). Our ablation study also validated the efficacy of the proposed model design. In addition, class-relevant areas highlighted by visualization techniques corresponded highly with various well-established qualitative imaging signs, further validating the learned representation. This study demonstrates the potential of deep learning techniques for timely and accurate AIS diagnosis from NCCT, which could substantially improve the quality of treatment for AIS patients.

Effectiveness of Center of Pressure Trajectory as Anticipatory Postural Adjustment Measurement in Parkinson's Disease With Freezing of Gait History.

BACKGROUND: Evidence showed that patients with Parkinson's disease (PD) who have a history of freezing of gait (FOG) have hypometric anticipatory postural adjustment (APA) during gait initiation (GI) compared to PD without FOG. OBJECTIVES: This study aimed to test the feasibility of center of pressure (COP) displacement during GI as the measure of APA in PD with and without a history of FOG. METHODS: Patients with PD underwent COP trajectory measurements, including duration, length, velocity, and acceleration in different phases of APA (APA1, APA2a, APA2, and LOC), as well as evaluation of New Freezing of Gait Questionnaire (NFOG-Q), Tinetti balance and gait score, and Postural Instability and Gait Difficulty (PIGD) score in the on and off medication states. RESULTS: The duration (seconds) of APA2a, APA2b, and LOC were highest while velocity in mediolateral direction (X) (m/s), including APA1, APA2a, APA2b, and LOC showed lowest in PD with FOG. Velocity in the mediolateral direction in different phases of APA increased in patients with FOG after dopaminergic therapy. APA2a (seconds) and APA2b (X) (m/s) were significantly associated with NFOG-Q part II, APA2b (X) (m/s) was significantly associated with NFOG-Q part III, and APA2a (seconds) was significantly associated with Tinetti balance and gait and PIGD score. CONCLUSIONS: PD with FOG history showed a favorable response of APAs to dopaminergic replacement. The APA parameters by COP trajectory, especially lateral COP shift toward the stance foot (APA2b (X) (m/s) and APA2a (seconds)) are surrogate markers to assess PD with FOG history.

2022 Taiwan clinical multicenter expert consensus and recommendations for thyroid radiofrequency ablation.

Radiofrequency ablation (RFA) is a minimally invasive management strategy that has been widely applied for benign and recurrent malignant thyroid lesions as an alternative to surgery in Taiwan. Members of academic societies for specialists in interventional radiology, endocrinology, and endocrine surgery collaborated to develop the first consensus regarding thyroid RFA in Taiwan. The modified Delphi method was used to reach a consensus. Based on a comprehensive review of recent and valuable literature and expert opinions, the recommendations included indications, pre-procedural evaluations, procedural techniques, post-procedural monitoring, efficacy, and safety, providing a comprehensive review of the application of RFA. The consensus effectively consolidates advice regarding thyroid RFA in clinical practice for local experts.

Localization Strategy Prior to Radiofrequency Ablation for Primary and Secondary Hyperparathyroidism.

OBJECTIVE: Preoperative localization in patients with primary or secondary hyperparathyroidism before radiofrequency ablation (RFA) is crucial. There is currently a lack of consensus regarding imaging protocol. Evaluating the diagnostic performance of ultrasound, four-dimensional computed tomography (4D-CT), and technetium 99m-sestamibi single-photon-emission-computed tomography/computed tomography (SPECT/CT) is necessary for RFA of hyperparathyroidism. METHODS: This retrospective study recruited patients with primary or secondary hyperparathyroidism who underwent ultrasound, 4D-CT, and SPECT/CT before RFA at a single institution. The sensitivity, accuracy, and receiver operating characteristic curve analysis were used to evaluate the diagnostic performance of the imaging modalities. RESULTS: A total of 33 patients underwent RFA for hyperparathyroidism (8 patients with primary hyperparathyroidism, 25 patients with secondary hyperparathyroidism). Ultrasound had the highest sensitivity (0.953) and accuracy (0.943), while 4D-CT had higher sensitivity and accuracy than SPECT/CT (sensitivity/accuracy, 4D-CT vs. SPECT/CT: 0.929/0.920 vs. 0.741/0.716). Combined ultrasound with 4D-CT and the three combined modalities achieved equivalent, and the highest, diagnostic performance (sensitivity 1.000, accuracy 0.989). The lesion length and volume were important predictors of the diagnostic performance of 4D-CT and SPECT/CT (area under curve of length in 4D-CT/volume in 4D-CT/length in SPECT/volume in SPECT: 0.895/0.834/0.767/0.761). CONCLUSION: Combined ultrasound with 4D-CT provides optimal preoperative localization prior to RFA in patients with primary or secondary hyperparathyroidism. The length and volume of parathyroid lesions are determinative of the diagnostic performance of 4D-CT and SPECT/CT.

Improving detection of impacted animal bones on lateral neck radiograph using a deep learning artificial intelligence algorithm.

OBJECTIVE: We aimed to develop a deep learning artificial intelligence (AI) algorithm to detect impacted animal bones on lateral neck radiographs and to assess its effectiveness for improving the interpretation of lateral neck radiographs. METHODS: Lateral neck radiographs were retrospectively collected for patients with animal bone impaction between January 2010 and March 2020. Radiographs were then separated into training, validation, and testing sets. A total of 1733 lateral neck radiographs were used to develop the deep learning algorithm. The testing set was assessed for the stand-alone deep learning AI algorithm and for human readers (radiologists, radiology residents, emergency physicians, ENT physicians) with and without the aid of the AI algorithm. Another radiograph cohort, collected from April 1, 2020, to June 30, 2020, was analyzed to simulate clinical application by comparing the deep learning AI algorithm with radiologists' reports. RESULTS: In the testing set, the sensitivity, specificity, and accuracy of the AI model were 96%, 90%, and 93% respectively. Among the human readers, all physicians of different subspecialties achieved a higher accuracy with AI-assisted reading than without. In the simulation set, among the 20 cases positive for animal bones, the AI model accurately identified 3 more cases than the radiologists' reports. CONCLUSION: Our deep learning AI model demonstrated a higher sensitivity for detection of animal bone impaction on lateral neck radiographs without an increased false positive rate. The application of this model in a clinical setting may effectively reduce time to diagnosis, accelerate workflow, and decrease the use of CT.

Clinical Utility of Plantar Pressure Measurements as Screening in Patients With Parkinson Disease With and Without Freezing of Gait History.

OBJECTIVE: To test the feasibility of objective assessments using the TekScan MatScan pressure mat plantar pressure measurement as a time-effective screening service for Parkinson disease (PD) with and without freezing of gait (FOG) history. DESIGN: Prospective cross-sectional study. SETTING: Largest medical center in southern Taiwan. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Plantar pressure measurements including average peak pressure (PP), contact area (CA), and pressure-time integral (PTI) in static and dynamic conditions as well as clinical scores during off-medication states. PARTICIPANTS: A total of 103 patients with PD and 22 age- and sex-matched volunteers without PD (N=125). RESULTS: Plantar pressure assessment including PP, CA, and PTI on the total foot areas between participants with PD and controls without PD in the static conditions are similar. Patients with PD presented higher PTI on total foot areas as well as hallux, midfoot area, and medial and lateral heels during dynamic conditions than controls without PD. The PP, CA, and PTI during the static condition and CA during the dynamic condition on the hallux showed statistical significance between PD with and without FOG history. Stepwise logistic regression after controlling with age and body mass index showed only PTI on hallux (static conditions) was significantly associated with the presence of FOG. The receiver operating characteristic curve analysis in diagnostic accuracy for FOG in PTI was statistically significant (P=.002; area under the curve, 0.71). CONCLUSIONS: FOG screening using the TekScan MatScan pressure mat plantar pressure measurement could serve as a time-effective screening service at the outpatient clinic. Based on our study, PTI may be valuable in auxiliary diagnosis.