Evaluating the Usability and Quality of a Clinical Mobile App for Assisting Physicians in Head Computed Tomography Scan Ordering: Mixed Methods Study.

BACKGROUND: Among the numerous factors contributing to health care providers' engagement with mobile apps, including user characteristics (eg, dexterity, anatomy, and attitude) and mobile features (eg, screen and button size), usability and quality of apps have been introduced as the most influential factors. OBJECTIVE: This study aims to investigate the usability and quality of the Head Computed Tomography Scan Appropriateness Criteria (HAC) mobile app for physicians' computed tomography scan ordering. METHODS: Our study design was primarily based on methodological triangulation by using mixed methods research involving quantitative and qualitative think-aloud usability testing, quantitative analysis of the Mobile Apps Rating Scale (MARS) for quality assessment, and debriefing across 3 phases. In total, 16 medical interns participated in quality assessment and testing usability characteristics, including efficiency, effectiveness, learnability, errors, and satisfaction with the HAC app. RESULTS: The efficiency and effectiveness of the HAC app were deemed satisfactory, with ratings of 97.8% and 96.9%, respectively. MARS assessment scale indicated the overall favorable quality score of the HAC app (82 out of 100). Scoring 4 MARS subscales, Information (73.37 out of 100) and Engagement (73.48 out of 100) had the lowest scores, while Aesthetics had the highest score (87.86 out of 100). Analysis of the items in each MARS subscale revealed that in the Engagement subscale, the lowest score of the HAC app was "customization" (63.6 out of 100). In the Functionality subscale, the HAC app's lowest value was "performance" (67.4 out of 100). Qualitative think-aloud usability testing of the HAC app found notable usability issues grouped into 8 main categories: lack of finger-friendly touch targets, poor search capabilities, input problems, inefficient data presentation and information control, unclear control and confirmation, lack of predictive capabilities, poor assistance and support, and unclear navigation logic. CONCLUSIONS: Evaluating the quality and usability of mobile apps using a mixed methods approach provides valuable information about their functionality and disadvantages. It is highly recommended to embrace a more holistic and mixed methods strategy when evaluating mobile apps, because results from a single method imperfectly reflect trustworthy and reliable information regarding the usability and quality of apps.

Computed Tomography Findings of Patients Presenting With Headache: 4-Year Retrospective Two-Center Study in Central and Western Regions of Ghana.

Objectives: The radiographic assessment of the head is a crucial part of headache care. A computed tomography (CT) scan enables a more detailed analysis of the condition and more focused care. This study examined head CT scans to determine what kinds of anomalies were present in patients with headaches as their primary complaint. Methods: We evaluated 4 years' worth of CT scan data from head exams conducted at two diagnostic facilities in Ghana's western and central regions. We examined data on 477 patients with a headache as their primary complaint between January 2017 and December 2020. We employed chi-square and Fisher's exact tests (where applicable) to compare head CT diagnoses between age groups, gender, headache subtypes, and brain lesion subgroups. Results: There were 53.5% (n = 255) females and 46.5% (n = 222) males in the study. The average age of patients was 38.67 ± 17.23 years, with an annual rate of abnormal CT diagnoses ranging from 35.9% in 2017 to 45.4% in 2022. Abnormal head CT diagnoses are strongly correlated with age groups and patient gender (p = 0.011 and p = 0.009, respectively). Of the 202 patients, 15.3% and 24.3% were classified as intracranial lesions and extracranial lesions, respectively. Maxillary sinusitis affected nearly 60% of the patients, while tumors and hemorrhages affected 25.2% and 11.9%, respectively. Conclusions: A CT scan of the head is essential to detect abnormalities in nearly 50% of patients suffering from various degrees of headache. Sinusitis, brain tumors, and hemorrhage were common lesions detected. It is crucial to create local standard operating procedures to promote better utilization of this type of imaging service, particularly among patients who have been diagnosed with headaches.

Nontraumatic Pediatric Head and Neck Emergencies: Resource for On-Call Radiologists.

The vast array of acute nontraumatic diseases encountered in the head and neck of pediatric patients can be intimidating for radiologists in training in a fast-paced emergency setting. Although there is some overlap of pediatric and adult diseases, congenital lesions and developmental variants are much more common in the pediatric population. Furthermore, the relative incidences of numerous infections and neoplasms differ between pediatric and adult populations. Young patients and/or those with developmental delays may have clinical histories that are difficult to elicit or nonspecific presentations, underscoring the importance of imaging in facilitating accurate and timely diagnoses. It is essential that radiologists caring for children be well versed in pediatric nontraumatic head and neck emergency imaging. The authors provide an on-call resource for radiology trainees, organized by anatomic location and highlighting key points, pearls, pitfalls, and mimics of many acute nontraumatic diseases in the pediatric head and neck. ©RSNA, 2024 Supplemental material is available for this article.

Observed-to-expected lung-area-to-head-circumference ratio on ultrasound examination vs total fetal lung volume on magnetic resonance imaging in prediction of survival in fetuses with left-sided diaphragmatic hernia.

OBJECTIVE: To assess and compare the value of antenatally determined observed-to-expected (O/E) lung-area-to-head-circumference ratio (LHR) on ultrasound examination vs O/E total fetal lung volume (TFLV) on magnetic resonance imaging (MRI) examination to predict postnatal survival of fetuses with isolated, expectantly managed left-sided congenital diaphragmatic hernia (CDH). METHODS: This was a multicenter retrospective study including all consecutive fetuses with isolated CDH that were managed expectantly in Mannheim, Germany, and in five other European centers, that underwent at least one ultrasound examination for measurement of O/E-LHR and one MRI scan for measurement of O/E-TFLV during pregnancy. All MRI data were centralized, and lung volumes were measured by two experienced operators blinded to the pre- and postnatal data. Multiple logistic regression analyses were performed to examine the effect on survival at hospital discharge of various perinatal variables, including the center of management. In left-sided CDH with intrathoracic herniation of the liver, receiver-operating-characteristics (ROC) curves were constructed separately for cases from Mannheim and the other five European centers and were used to compare O/E-TFLV and O/E-LHR in the prediction of postnatal survival. RESULTS: From Mannheim, 309 patients were included with a median gestational age (GA) at ultrasound examination of 29.6 (range, 19.7-39.1) weeks and median GA at MRI examination of 31.1 (range, 18.0-39.9) weeks. From the other five European centers, 116 patients were included with a median GA at ultrasound examination of 26.7 (range, 20.6-37.6) weeks and median GA at MRI examination of 27.7 (range, 21.3-37.9) weeks. Regression analysis demonstrated that the survival rates at discharge were lower in left-sided CDH (odds ratio (OR), 0.349 (95% CI, 0.133-0.918), P = 0.033) and those with intrathoracic liver (OR, 0.297 (95% CI, 0.141-0.628), P = 0.001), and higher with increasing O/E-TFLV (OR, 1.123 (95% CI, 1.079-1.170), P < 0.001), advanced GA at birth (OR, 1.294 (95% CI, 1.055-1.588), P = 0.013) and when birth occurred in Mannheim (OR, 7.560 (95% CI, 3.368-16.967), P < 0.001). Given the difference in survival rate between Mannheim and the five other European centers, ROC curve comparisons between the two imaging modalities were presented separately. For cases of left-sided CDH with intrathoracic herniation of the liver, pairwise comparison showed no significant difference between the area under the ROC curves for the prediction of postnatal survival between O/E-TFLV and O/E-LHR in Mannheim (mean difference = 0.025, P = 0.610, standard error = 0.050), whereas there was a significant difference in the other European centers studied (mean difference = 0.056, P = 0.033, standard error = 0.056). CONCLUSIONS: In fetuses with left-sided CDH and intrathoracic herniation of the liver, the predictive value for postnatal survival of O/E-TFLV on MRI examination and O/E-LHR on ultrasound examination was similar in one center (Mannheim), but O/E-TFLV had better predictive value compared to O/E-LHR in the five other European centers. Hence, in these five European centers, MRI should be included in the diagnostic process for left-sided CDH. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

[Ultrasonographic features of Castleman disease in the head and neck: a report of 7 cases].

PURPOSE: To summarize the ultrasonographic features of head and neck Castleman disease (CD), and to clarify its diagnostic key points. METHODS: Seven patients with head and neck CD confirmed by histopathology were collected from Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. The clinical features and ultrasound findings of the patients were evaluated. RESULTS: Of the 7 patients (1 male and 6 females), the mean age at diagnosis was 31.4 years (7-60 years). All the cases were hyaline vascular type. On ultrasound, 3 lesions (42.9%) were located in the parotid gland, 4 lesions(57.1%) in the neck. All the lesions presented as a solitary, well-defined and solid mass without calcification. The echogenicity was markedly hypoechoic in 1 case(14.3%) and hypoechoic in 6 cases (85.7%). Of the 7 CD cases, 4 cases (57.1%) were heterogeneous masses with linear echogenic septa. All lesions had mixed pattern in vascularity on color Doppler sonography. CONCLUSIONS: Most CDs in the head and neck represent as a markedly hypoechoic or hypoechoic lesion with mixed pattern in vascularity. The neoplasm may be characterized by the presence of linear echogenic septa within the mass.

Scatter estimation and correction using time-of-flight and deconvolution in x-ray medical imaging.

Objective.Time-of-flight (TOF) scatter rejection requires a total timing jitter, including the detector timing jitter and the x-ray source's pulses width, of 50 ps or less to mitigate most of the effects of scattered photons in radiography and CT imaging. However, since the total contribution of the source and detector to the timing jitter can be retrieved during an acquisition with nothing between the source and detector, it can be demonstrated that this contribution may be partially removed to improve the image quality.Approach.A scatter correction method using iterative deconvolution of the measured time point-spread function estimates the number of scattered photons detected in each pixel. To evaluate the quality of the estimation, GATE was used to simulate the radiography of a water cylinder with bone inserts, and a head and torso in a system with total timing jitters from 100 ps up to 500 ps full-width-at-half-maximum (FWHM).Main results.With a total timing jitter of 200 ps FWHM, 89% of the contrast degradation caused by scattered photons was recovered in a head and torso radiography, compared to 28% with a simple time threshold method. Corrected images using the estimation have a percent root-mean square error between 2% and 14% in both phantoms with timing jitters from 100 to 500 ps FWHM which is lower than the error achieved with scatter rejection alone at 100 ps FWHM.Significance.TOF x-ray imaging has the potential to mitigate the effects of the scattering contribution and offers an alternative to anti-scatter grids that avoids loss of primary photons. Compare to simple TOF scatter rejection using only a threshold, the deconvolution estimation approach has lower requirements on both the source and detector. These requirements are now within reach of state-of-the-art systems.

ACSwinNet: A Deep Learning-Based Rigid Registration Method for Head-Neck CT-CBCT Images in Image-Guided Radiotherapy.

Accurate and precise rigid registration between head-neck computed tomography (CT) and cone-beam computed tomography (CBCT) images is crucial for correcting setup errors in image-guided radiotherapy (IGRT) for head and neck tumors. However, conventional registration methods that treat the head and neck as a single entity may not achieve the necessary accuracy for the head region, which is particularly sensitive to radiation in radiotherapy. We propose ACSwinNet, a deep learning-based method for head-neck CT-CBCT rigid registration, which aims to enhance the registration precision in the head region. Our approach integrates an anatomical constraint encoder with anatomical segmentations of tissues and organs to enhance the accuracy of rigid registration in the head region. We also employ a Swin Transformer-based network for registration in cases with large initial misalignment and a perceptual similarity metric network to address intensity discrepancies and artifacts between the CT and CBCT images. We validate the proposed method using a head-neck CT-CBCT dataset acquired from clinical patients. Compared with the conventional rigid method, our method exhibits lower target registration error (TRE) for landmarks in the head region (reduced from 2.14 ± 0.45 mm to 1.82 ± 0.39 mm), higher dice similarity coefficient (DSC) (increased from 0.743 ± 0.051 to 0.755 ± 0.053), and higher structural similarity index (increased from 0.854 ± 0.044 to 0.870 ± 0.043). Our proposed method effectively addresses the challenge of low registration accuracy in the head region, which has been a limitation of conventional methods. This demonstrates significant potential in improving the accuracy of IGRT for head and neck tumors.

Dynamic contrast enhanced MRI of the head and neck region using a VIBE sequence with Cartesian undersampling and compressed sensing.

OBJECTIVES: Compressed sensing allows for image reconstruction from sparsely sampled k-space data, which is particularly useful in dynamic contrast enhanced MRI (DCE-MRI). The aim of the study was to assess the diagnostic value of a volume-interpolated 3D T1-weighted spoiled gradient-echo sequence with variable density Cartesian undersampling and compressed sensing (CS) for head and neck MRI. METHODS: Seventy-one patients with clinical indications for head and neck MRI were included in this study. DCE-MRI was performed at 3 Tesla magnet using CS-VIBE (variable density undersampling, temporal resolution 3.4 s, slice thickness 1 mm). Image quality was compared to standard Cartesian VIBE. Three experienced readers independently evaluated image quality and lesion conspicuity on a 5-point Likert scale and determined the DCE-derived time intensity curve (TIC) types. RESULTS: CS-VIBE demonstrated higher image quality scores compared to standard VIBE with respect to overall image quality (4.3 ± 0.6 vs. 4.2 ± 0.7, p = 0.682), vessel contour (4.6 ± 0.4 vs. 4.4 ± 0.6, p < 0.001), muscle contour (4.4 ± 0.5 vs. 4.5 ± 0.6, p = 0.302), lesion conspicuity (4.5 ± 0.7 vs. 4.3 ± 0.9, p = 0.024) and showed improved fat saturation (4.8 ± 0.3 vs. 3.8 ± 0.4, p < 0.001) and movement artifacts were significantly reduced (4.6 ± 0.6 vs. 3.7 ± 0.7, p < 0.001). Standard VIBE outperformed CS-VIBE in the delineation of pharyngeal mucosa (4.2 ± 0.5 vs. 4.6 ± 0.6, p < 0.001). Lesion size in cases where a focal lesion was identified was similar for all readers for CS-VIBE and standard VIBE (p = 0.101). TIC curve assessment showed good interobserver agreement (k=0.717). CONCLUSION: CS-VIBE with variable density Cartesian undersampling allows for DCE-MRI of the head and neck region with diagnostic, high image quality and high temporal resolution.

[Development of a Head Radiography Simulator System Using Pose Estimation Techniques].

PURPOSE: This study proposes a system that can simulate head radiography by combining a technique for estimating human posture from moving images (hereafter referred to as "pose estimation technique") and use of two cameras capable of acquiring RGB images to determine body position during positioning. METHODS: The angles of the median sagittal plane (MS), axial plane (AX), and orbitomeatal baseline (OM) were obtained using the pose estimation technique from frontal and lateral images captured after positioning. The resulting radiographs were displayed according to the results. RESULTS: The head tilt during positioning could be determined based on the coordinate data of feature points acquired using the pose estimation technique. In an imaging experiment using a simulated human patient, errors increased as head tilt increased; however, the mean error values in each axis were 0.9° for MS, 0.8° for AX, and 1.5°for OM, when the patient was correctly positioned. CONCLUSION: The pose estimation technique can assist in evaluating positioning accuracy in radiography and is expected to be used as a potential simulator system.

[Artifact Assessment in the Skull Base Region of Head CT Images with Various Tilt Angles Relative to the Orbitomeatal Line].

PURPOSE: The aim of this study was to evaluate artifacts in the skull base region of head computed tomography (CT) images with various tilt angles relative to the orbitomeatal line. METHODS: CT images of a head phantom acquired by helical and non-helical scanning with the tilt angles set from 0 to 20 degrees in 5-degree increments were evaluated in this study. Regions of interest (ROIs) were set at the cerebellum, temporal lobe, frontal lobe, and basal ganglia in the phantom images. Artifacts were evaluated by the coefficient of variation (CV) of the mean CT value between ROIs and the location parameter (ß) of the Gumbel method. RESULTS: The CV and ß values increased with increasing tilt angle for both helical and nonhelical images in the frontal lobes, but both decreased in the cerebellar region. In the temporal lobe and basal ganglia, there was no trend of change with tilt angle. CONCLUSION: Increasing the tilt angle relative to the OM line increased artifacts at the frontal lobes and decreased artifacts at the cerebellar region.

A nonparametric measure of contrast in x-ray images.

Objective.We propose a nonparametric figure of merit, the contrast equivalent distance CED, to measure contrast directly from clinical images.Approach.A relative brightness distanceδis calculated by making use of the order statistic of the pixel values. By multiplyingδwith the grey value rangeR, the mean brightness distance MBD is obtained. From the MBD, the CED and the distance-to-noise ratio DNR can be derived. The latter is the ratio of the MBD and a previously suggested nonparametric measureτfor the noise. Since the order statistic is independent of the spatial arrangement of the pixel values, the measures can be obtained directly from clinical images. We apply the new measures to mammography images of an anthropomorphic phantom and of a phantom with a step wedge as well as to CT images of a head phantom.Main results.For low-noise images of a step wedge, the MBD is equivalent to the conventional grey value distance. While this measure permits the evaluation of clinical images, it is sensitive to noise. Therefore, noise has to be quantified at the same time. When the ratioσ/τof the noise standard deviationσtoτis available, validity limits for the CED as a measure of contrast can be established. The new figures of merit can be calculated for entire images as well as on regions of interest (ROI) with an edge length not smaller than 32 px.Significance.The new figures of merit are suited to quantify the quality of clinical images without relying on the assumption of a linear, shift-invariant system. They can be used for any kind of greyscale image, provided the ratioσ/τcan be estimated. This will hopefully help to achieve the optimisation of image quality vs dose required by radioprotection laws.

Head of Zebu cattle (Bos Taurus indicus): sectional anatomy and 3D computed tomography.

The research was designed to use computed tomography (CT) with 3D-CT reconstruction imaging techniques and the various anatomical sections-plana transversalia, frontalis, and dorsalia-to describe the anatomical architecture of the Zebu cattle head. Our study used nine mature heads. The CT bone window created detailed images of cranial bones, mandibles, teeth, and hyoid bones. All of the head cavities were evaluated, including the cranial, orbital, oral, auricular, and nasal cavities with their paranasal and conchal sinuses. The septum nasi, attached to the vomer and maxillary bones, did not reach the nasal cavity floor caudally at the level of the second premolar teeth, resulting in a single median channel from the choanae to the nasopharynx. The positions, boundaries, and connections of the paranasal sinuses were clearly identified. There were four nasal conchal sinuses (that were named the dorsal, middle, ethmoidal, and ventral) and five paranasal sinuses that were described as the following: sinus frontalis, maxillaris, palatinorum, and lacrimalis, as defined in the different anatomical sections and computed tomographic images. The complicated sinus frontalis caused the pneumatization of all bones that surrounded the cranial cavity, with the exception of the ethmoidal and body of basisphenoid bones. The sinus maxillaris was connected to the sinus lacrimalis and palatinorum through the maxillolacrimal and palatomaxillary openings, and to the middle nasal meatus through the nasomaxillary opening. Our findings provide a detailed anatomical knowledge for disease diagnosis to internal medicine veterinarians and surgeons by offering a comprehensive atlas of the Zebu cattle anatomy.

Selective postmortem arterial angiography of head and neck using digital x-ray or computed tomography: A practical and rapid method to identify vascular injuries.

Identification of vascular injuries is crucial for complete postmortem evaluation and understanding of trauma deaths by the Medical Examiner. Some vascular injuries are difficult to evaluate due to challenging anatomic locations, especially in the head and neck. Documenting injuries of the facial and vertebral arteries is challenging and necessitates time-consuming dissections that can create artifacts and disfigurement. In busy medical examiner offices with a significant number of traumatic injuries, finding a creative solution to employ reliable postmortem angiography is desirable. At the Office of the Chief Medical Examiner for the State of Maryland (OCME), we created and effectively implemented a selective angiography procedure using traditional indwelling Foley catheters and water-soluble barium swallow contrast to evaluate arterial injuries using either digital radiography or computed tomography imaging modalities. This technique and imaging interpretation can be performed by a medical examiner or forensic pathology fellow after basic technical training and basic radiology training. This study outlines the technique, methods, and utilization of the procedure and describes the findings of six deaths due to vascular lesions from different injury mechanisms and disease processes and describes the ease of implementation on a broader scale in busy Medical Examiner's offices.

Development of clinical prediction model to guide the use of CT head scans for non-traumatic Thai patient with seizure: A cross-sectional study.

The aim of this study was to develop clinical predictor tools for guiding the use of computed tomography (CT) head scans in non-traumatic Thai patients presented with seizure. A prediction model using a retrospective cross-sectional design was conducted. We recruited adult patients (aged ≥ 18 years) who had been diagnosed with seizures by their physicians and had undergone CT head scans for further investigation. Positive CT head defined as the presence of any new lesion that related to the patient's presented seizure officially reported by radiologist. A total of 9 candidate predictors were preselected. The prediction model was developed using a full multivariable logistic regression with backward stepwise elimination. We evaluated the model's predictive performance in terms of its discriminative ability and calibration via AuROC and calibration plot. The application was then constructed based on final model. A total of 362 patients were included into the analysis which comprising of 71 patients with positive CT head findings and 291 patients with normal results. Six final predictors were identified including: Glasgow coma scale, the presence of focal neurological deficit, history of malignancy, history of CVA, Epilepsy, and the presence of alcohol withdrawal symptom. In terms of discriminative ability, the final model demonstrated excellent performance (AuROC of 0.82 (95% CI: 0.76-0.87)). The calibration plot illustrated a good agreement between observed and predicted risks. This prediction model offers a reliable tool for effectively reduce unnecessary use and instill confidence in supporting physicians in determining the need for CT head scans in non-traumatic patients with seizures.

Investigation of distributed learning for automated lesion detection in head MR images.

In this study, we investigated the application of distributed learning, including federated learning and cyclical weight transfer, in the development of computer-aided detection (CADe) software for (1) cerebral aneurysm detection in magnetic resonance (MR) angiography images and (2) brain metastasis detection in brain contrast-enhanced MR images. We used datasets collected from various institutions, scanner vendors, and magnetic field strengths for each target CADe software. We compared the performance of multiple strategies, including a centralized strategy, in which software development is conducted at a development institution after collecting de-identified data from multiple institutions. Our results showed that the performance of CADe software trained through distributed learning was equal to or better than that trained through the centralized strategy. However, the distributed learning strategies that achieved the highest performance depend on the target CADe software. Hence, distributed learning can become one of the strategies for CADe software development using data collected from multiple institutions.

Photon-Counting CT in the Head and Neck: Current Applications and Future Prospects.

Photon-counting detectors (PCDs) represent a major milestone in the evolution of CT imaging. CT scanners using PCD systems have already been shown to generate images with substantially greater spatial resolution, superior iodine contrast-to-noise ratio, and reduced artifact compared with conventional energy-integrating detector-based systems. These benefits can be achieved with considerably decreased radiation dose. Recent studies have focused on the advantages of PCD-CT scanners in numerous anatomic regions, particularly the coronary and cerebral vasculature, pulmonary structures, and musculoskeletal imaging. However, PCD-CT imaging is also anticipated to be a major advantage for head and neck imaging. In this paper, we review current clinical applications of PCD-CT in head and neck imaging, with a focus on the temporal bone, facial bones, and paranasal sinuses; minor arterial vasculature; and the spectral capabilities of PCD systems.

Validation and Evaluation of a Vendor-Provided Head Motion Correction Algorithm on the uMI Panorama PET/CT System.

Brain PET imaging often faces challenges from head motion (HM), which can introduce artifacts and reduce image resolution, crucial in clinical settings for accurate treatment planning, diagnosis, and monitoring. United Imaging Healthcare has developed NeuroFocus, an HM correction (HMC) algorithm for the uMI Panorama PET/CT system, using a data-driven, statistics-based approach. The HMC algorithm automatically detects HM using a centroid-of-distribution technique, requiring no parameter adjustments. This study aimed to validate NeuroFocus and assess the prevalence of HM in clinical short-duration 18F-FDG scans. Methods: The study involved 317 patients undergoing brain PET scans, divided into 2 groups: 15 for HMC validation and 302 for evaluation. Validation involved patients undergoing 2 consecutive 3-min single-bed-position brain 18F-FDG scans-one with instructions to remain still and another with instructions to move substantially. The evaluation examined 302 clinical single-bed-position brain scans for patients with various neurologic diagnoses. Motion was categorized as small or large on the basis of a 5% SUV change in the frontal lobe after HMC. Percentage differences in SUVmean were reported across 11 brain regions. Results: The validation group displayed a large negative difference (-10.1%), with variation of 5.2% between no-HM and HM scans. After HMC, this difference decreased dramatically (-0.8%), with less variation (3.2%), indicating effective HMC application. In the evaluation group, 38 of 302 patients experienced large HM, showing a 10.9% ± 8.9% SUV increase after HMC, whereas most exhibited minimal uptake changes (0.1% ± 1.3%). The HMC algorithm not only enhanced the image resolution and contrast but also aided in disease identification and reduced the need for repeat scans, potentially optimizing clinical workflows. Conclusion: The study confirmed the effectiveness of NeuroFocus in managing HM in short clinical 18F-FDG studies on the uMI Panorama PET/CT system. It found that approximately 12% of scans required HMC, establishing HMC as a reliable tool for clinical brain 18F-FDG studies.

Assessing the effectiveness of artificial intelligence (AI) in prioritising CT head interpretation: study protocol for a stepped-wedge cluster randomised trial (ACCEPT-AI).

INTRODUCTION: Diagnostic imaging is vital in emergency departments (EDs). Accessibility and reporting impacts ED workflow and patient care. With radiology workforce shortages, reporting capacity is limited, leading to image interpretation delays. Turnaround times for image reporting are an ED bottleneck. Artificial intelligence (AI) algorithms can improve productivity, efficiency and accuracy in diagnostic radiology, contingent on their clinical efficacy. This includes positively impacting patient care and improving clinical workflow. The ACCEPT-AI study will evaluate Qure.ai's qER software in identifying and prioritising patients with critical findings from AI analysis of non-contrast head CT (NCCT) scans. METHODS AND ANALYSIS: This is a multicentre trial, spanning four diverse sites, over 13 months. It will include all individuals above the age of 18 years who present to the ED, referred for an NCCT. The project will be divided into three consecutive phases (pre-implementation, implementation and post-implementation of the qER solution) in a stepped-wedge design to control for adoption bias and adjust for time-based changes in the background patient characteristics. Pre-implementation involves baseline data for standard care to support the primary and secondary outcomes. The implementation phase includes staff training and qER solution threshold adjustments in detecting target abnormalities adjusted, if necessary. The post-implementation phase will introduce a notification (prioritised flag) in the radiology information system. The radiologist can choose to agree with the qER findings or ignore it according to their clinical judgement before writing and signing off the report. Non-qER processed scans will be handled as per standard care. ETHICS AND DISSEMINATION: The study will be conducted in accordance with the principles of Good Clinical Practice. The protocol was approved by the Research Ethics Committee of East Midlands (Leicester Central), in May 2023 (REC (Research Ethics Committee) 23/EM/0108). Results will be published in peer-reviewed journals and disseminated in scientific findings (ClinicalTrials.gov: NCT06027411) TRIAL REGISTRATION NUMBER: NCT06027411.

Orthognathic surgery improves compromised natural head position and pharyngeal airway in patients with Skeletal Class II or III malocclusion.

BACKGROUND: Natural head position (NHP), pharyngeal airway and maxillofacial growth pattern are correlated. The author's previous studies proved that following surgical correction of Skeletal Class II malocclusion, the over-extended NHP returned upright, and the pharyngeal airway space (PAS) dimension expanded. OBJECTIVE: The present study compares the post-operative change in NHP and PAS after orthognathic surgery in Skeletal Class II and III malocclusion patients. METHODS: Patients receiving orthognathic procedures to correct Skeletal Class II or III malocclusions were reviewed in this retrospective study. Pre-operative and 6-week post-operative cone-beam computed tomography datasets were collected. Variables representing the craniofacial pattern, the NHP and the PAS were measured three-dimensionally. Post-operative variables were compared with their pre-operative counterparts using either repeat-measure 2-way analysis of variance or Wilcoxon matched-pairs signed rank test. RESULTS: Thirty cases of Skeletal Class II malocclusion and 13 cases of Skeletal Class III malocclusion were collected. Preoperatively, the inter-group differences were significant in craniofacial pattern (68.14 ± 3.552 degree vs. 79.63 ± 2.497 degree, p < .0001) and the NHP (68.77 ± 11.02 degree vs. 82.83 ± 7.738 degree, p = .0002) while not significant in PAS; after surgery, the intergroup differences in craniofacial pattern and the NHP between groups decreased, and the PAS increased in both groups. CONCLUSION: Orthognathic surgery may improve compromised NHP and increase PAS in Skeletal Class II and III malocclusion patients.

Diagnostic test accuracy of externally validated convolutional neural network (CNN) artificial intelligence (AI) models for emergency head CT scans - A systematic review.

BACKGROUND: The surge in emergency head CT imaging and artificial intelligence (AI) advancements, especially deep learning (DL) and convolutional neural networks (CNN), have accelerated the development of computer-aided diagnosis (CADx) for emergency imaging. External validation assesses model generalizability, providing preliminary evidence of clinical potential. OBJECTIVES: This study systematically reviews externally validated CNN-CADx models for emergency head CT scans, critically appraises diagnostic test accuracy (DTA), and assesses adherence to reporting guidelines. METHODS: Studies comparing CNN-CADx model performance to reference standard were eligible. The review was registered in PROSPERO (CRD42023411641) and conducted on Medline, Embase, EBM-Reviews and Web of Science following PRISMA-DTA guideline. DTA reporting were systematically extracted and appraised using standardised checklists (STARD, CHARMS, CLAIM, TRIPOD, PROBAST, QUADAS-2). RESULTS: Six of 5636 identified studies were eligible. The common target condition was intracranial haemorrhage (ICH), and intended workflow roles auxiliary to experts. Due to methodological and clinical between-study variation, meta-analysis was inappropriate. The scan-level sensitivity exceeded 90 % in 5/6 studies, while specificities ranged from 58,0-97,7 %. The SROC 95 % predictive region was markedly broader than the confidence region, ranging above 50 % sensitivity and 20 % specificity. All studies had unclear or high risk of bias and concern for applicability (QUADAS-2, PROBAST), and reporting adherence was below 50 % in 20 of 32 TRIPOD items. CONCLUSION: 0.01 % of identified studies met the eligibility criteria. The evidence on the DTA of CNN-CADx models for emergency head CT scans remains limited in the scope of this review, as the reviewed studies were scarce, inapt for meta-analysis and undermined by inadequate methodological conduct and reporting. Properly conducted, external validation remains preliminary for evaluating the clinical potential of AI-CADx models, but prospective and pragmatic clinical validation in comparative trials remains most crucial. In conclusion, future AI-CADx research processes should be methodologically standardized and reported in a clinically meaningful way to avoid research waste.