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The treatment of moving objects in simultaneous localization and mapping (SLAM) is a key challenge in contemporary robotics. In this paper, we propose an extension of the EKF-SLAM algorithm that incorporates moving objects into the estimation process, which we term KISS. We have extended the robotic vision toolbox to analyze the influence of moving objects in simulations. Two linear and one nonlinear motion models are used to represent the moving objects. The observation model remains the same for all objects. The proposed model is evaluated against an implementation of the state-of-the-art formulation for moving object tracking, DATMO. We investigate increasing numbers of static landmarks and dynamic objects to demonstrate the impact on the algorithm and compare it with cases where a moving object is mistakenly integrated as a static landmark (false negative) and a static landmark as a moving object (false positive). In practice, distances to dynamic objects are important, and we propose the safety-distance-error metric to evaluate the difference between the true and estimated distances to a dynamic object. The results show that false positives have a negligible impact on map distortion and ATE with increasing static landmarks, while false negatives significantly distort maps and degrade performance metrics. Explicitly modeling dynamic objects not only performs comparably in terms of map distortion and ATE but also enables more accurate tracking of dynamic objects with a lower safety-distance-error than DATMO. We recommend that researchers model objects with uncertain motion using a simple constant position model, hence we name our contribution Keep it Static SLAMMOT. We hope this work will provide valuable data points and insights for future research into integrating moving objects into SLAM algorithms.

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PURPOSE: Ultrasound imaging has emerged as a promising cost-effective and portable non-irradiant modality for the diagnosis and follow-up of diseases. Motion analysis can be performed by segmenting anatomical structures of interest before tracking them over time. However, doing so in a robust way is challenging as ultrasound images often display a low contrast and blurry boundaries. METHODS: In this paper, a robust descriptor inspired from the fractal dimension is presented to locally characterize the gray-level variations of an image. This descriptor is an adaptive grid pattern whose scale locally varies as the gray-level variations of the image. Robust features are then located based on the gray-level variations, which are more likely to be consistently tracked over time despite the presence of noise. RESULTS: The method was validated on three datasets: segmentation of the left ventricle on simulated echocardiography (Dice coefficient, DC), accuracy of diaphragm motion tracking for healthy subjects (mean sum of distances, MSD) and for a scoliosis patient (root mean square error, RMSE). Results show that the method segments the left ventricle accurately ( DC = 0.84 ) and robustly tracks the diaphragm motion for healthy subjects ( MSD = 1.10 mm) and for the scoliosis patient ( RMSE = 1.22 mm). CONCLUSIONS: This method has the potential to segment structures of interest according to their texture in an unsupervised fashion, as well as to help analyze the deformation of tissues. Possible applications are not limited to US image. The same principle could also be applied to other medical imaging modalities such as MRI or CT scans.

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Background: The radial nerve, originating from the posterior cord of the brachial plexus, traverses the posterior humerus. Incidences of radial nerve injury have been noted following surgical interventions like fracture fixation and exploration in this area. There's a paucity of literature detailing soft tissue anatomical cues for radial nerve dissection. This study aimed to identify reliable soft tissue and bony landmarks (triceps aponeurosis and deltoid tuberosity) that can be of substantial importance in dissecting the radial nerve and reducing iatrogenic nerve injury utilizing the posterior approach. Methods: Thirty-two fresh-frozen cadaver specimens underwent dissection using a posterior triceps-splitting approach to expose the radial nerve. The distance between the apex of the triceps aponeurosis and the radial nerve was measured, alongside noting the radial nerve's position relative to the deltoid tuberosity. Results: Of the cadavers, 78% were female, and 22% were male, with a mean age of 76 (range: 62-85). The average distance between the aponeurosis apex and the radial nerve was 40.3 mm (range: 28-60). The radial nerve was consistently found in all specimens, situated posteriorly at the humerus's mid-axial level at the distal part of the deltoid tuberosity. Conclusion: The triceps aponeurosis and distal deltoid tuberosity serve as reliable and practical landmarks for dissecting and exploring the radial nerve during posterior humeral approaches. These landmarks prove especially valuable when fractures obscure conventional anatomical cues.

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Fascioliasis, only foodborne trematodiasis of worldwide distribution, is caused by Fasciola hepatica and F. gigantica, liver flukes transmitted by freshwater snails. Southern and southeastern Asia is an emerging hot spot of F. gigantica, despite its hitherto less involvement in human infection. In Vietnam, increasing cases have been reported since 1995, whereas only sixteen throughout 1800-1994. A database was created to include epidemiological data of fascioliasis patients from the 63 Vietnam provinces throughout 1995-2019. Case profiles were based on serology, symptoms, eosinophilia, imaging techniques, stool egg finding, and post-specific-treatment recovery. Radio broadcasting about symptoms and costless diagnosis/treatment led patients to hospitals after symptom onset. Yearly case numbers were modelled and spatio-temporally analyzed. Missing data and confounders were assessed. The countrywide spread has no precedent. It started in the central coast, including 53,109 patients, mostly adults and females. Seasonality, linked to vegetable consumption, peaks in June, although the intensity of this peak differs according to relief/climatic zones. Incidence data and logistic regression curves are obtained for the first time in human fascioliasis. Fasciolid hybrids accompanying the spreading F. gigantica flukes, and climate change assessed by risk index correlations, are both ruled out as outbreak causes. Human-guided movements of livestock from an original area prove to be the way used by fasciolids and lymnaeid vectors to expand geographically. Radix viridis, a highly efficient transmitting and colonizing vector, played a decisive role in the spread. The use of irrigated crop fields, widely inhabited by R. viridis, for livestock grazing facilitated the transmission and spread of the disease. General physician awareness and diagnostic capacity improvement proved the successful impact of such knowledge transfer in facilitating and increasing patient infection detection. Information, education and communication to the public by radio broadcasting demonstrated to be very helpful. Fasciola gigantica is able to cause epidemic and endemic situations similar to F. hepatica. The magnitude of the human outbreak in Vietnam is a health wake-up call for southern and southeastern countries of Asia which present the highest human population densities with increasing food demands, uncontrolled livestock inter-country exchange, foreign import practices, and monsoon's increasing climate change impact.

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BACKGROUND: The rhomboid fossa (RF) is a crucial anatomical region in brainstem surgery as it contains essential structures such as the reticular formation and cranial nerve nuclei. This study aimed to provide a detailed understanding of the complex microsurgical anatomy of the RF, which is vital for the safe execution of neurosurgical procedures. METHODS: Morphometric analysis was conducted on 45 adult human brainstems preserved in 10% formalin. Under 20× magnification, 13 linear measurements were performed using a millimeter graph to identify key anatomical landmarks. RESULTS: The RF measured 34.65 mm in length and 22.61 mm in width. The facial colliculus measured 4.26 mm in length on the left and 4.45 mm on the right, with corresponding widths of 3.77 mm and 3.50 mm. The distance between the sulcus limitans incisures was 9.52 mm, and the distance from the upper border of the medullary striae to obex was 11.53 mm. The proximity of the facial colliculus to the median sulcus was measured at 0.86 mm on the right and 0.96 mm on the left. Additionally, 2 safe entry zones-the suprafacial and infrafacial triangles-were identified, offering pathways to reach dorsal pons lesions through the RF. CONCLUSIONS: This comprehensive morphometric analysis of the RF enhances the understanding of its intricate anatomy. By describing safe entry zones, the suprafacial and infrafacial triangles, and providing precise measurements of key anatomical features, this study serves as a valuable resource for neurosurgeons in planning and executing brainstem surgeries.

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The blood-sucking flies of the genus Stomoxys Geoffroy, 1762 (Diptera: Muscidae) are significant ectoparasites that can cause irritation and transmit pathogens to both animals and humans. Within the genus Stomoxys, two species, Stomoxys bengalensis and Stomoxys sitiens, have similar morphology and coexist in the same habitat. Accurate species identification of these flies is crucial for understanding disease vectors and implementing effective control measures. In this study, we assessed the effectiveness of outline-based geometric morphometrics (GM) by analyzing the wing cell contour of the first posterior cell (R5) to distinguish between species and sexes of S. bengalensis and S. sitiens. Our results demonstrate that the outline-based GM method is highly effective in distinguishing between species and sexes of these flies based on contour shape, with accuracy scores ranging from 90.0% to 97.5%. Therefore, outline-based GM emerges as a promising alternative to landmark-based GM or as a supplementary tool in conjunction with traditional morphology-based methods for species identification.

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Background: Three-dimensional cephalometric analysis is crucial in craniomaxillofacial assessment, with landmarks detection in craniomaxillofacial (CMF) CT scans being a key component. However, creating robust deep learning models for this task typically requires extensive CMF CT datasets annotated by experienced medical professionals, a process that is time-consuming and labor-intensive. Conversely, acquiring large volume of unlabeled CMF CT data is relatively straightforward. Thus, semi-supervised learning (SSL), leveraging limited labeled data supplemented by sufficient unlabeled dataset, could be a viable solution to this challenge. Method: We developed an SSL model, named CephaloMatch, based on a strong-weak perturbation consistency framework. The proposed SSL model incorporates a head position rectification technique through coarse detection to enhance consistency between labeled and unlabeled datasets and a multilayers perturbation method which is employed to expand the perturbation space. The proposed SSL model was assessed using 362 CMF CT scans, divided into a training set (60 scans), a validation set (14 scans), and an unlabeled set (288 scans). Result: The proposed SSL model attained a detection error of 1.60 ± 0.87 mm, significantly surpassing the performance of conventional fully supervised learning model (1.94 ± 1.12 mm). Notably, the proposed SSL model achieved equivalent detection accuracy (1.91 ± 1.00 mm) with only half the labeled dataset, compared to the fully supervised learning model. Conclusions: The proposed SSL model demonstrated exceptional performance in landmarks detection using a limited labeled CMF CT dataset, significantly reducing the workload of medical professionals and enhances the accuracy of 3D cephalometric analysis.

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Objective: This retrospective study aims to assess the role of pre-contrast sequences of an MRI-guided breast biopsy (MRIB) exam in confident and accurate lesion site localization based on tissue landmarks. Methods: The charts of all consecutives MRIB that were performed between January 2018 and December 2020 were reviewed. The images of the eligible exams were analyzed by 3 breast radiologists. Each radiologist independently attempted to identify lesion site on pre-contrast MRIB sequences, while blinded to the post-contrast MRIB images. Confidence levels (I-confident, II-not confident, and III-unknown) were assigned by each reviewer. A fourth radiologist assessed the accuracy (≤5 mm-accurate, >5 mm-inaccurate) in lesion site localization using the actual biopsied lesion site and the post-contrast MRIB images as reference. Descriptive statistics were used to calculate the percentage of confidence and accuracy categories for each reviewer, with Chi-square tests applied to analyze relationships between categorical variables. Results: There were 174 female patients with 181 lesions eligible for the trial. When the lesion site is confidently identified on the pre-contrast MRIB images (level 1 confidence), mean grade 1 accuracy was 93.8% (P < .001). Accuracy decreased with Level II and III confidence (55.3% and 34.2% respectively). Up to 61.4% improved accuracy was demonstrated when combining the performance of 2 reviewers. No correlation was found between breast density, lesion morphology, or biopsy positioning with confidence level or accuracy grade. Conclusion: Careful review of the pre-contrast MRIB images and familiarization with the surrounding tissue landmarks are important steps in confidently and accurately detecting lesion site.

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BACKGROUND: Left ventricular assist device (LVAD) malposition has been linked to hemocompatibility-related adverse events (HRAEs). This study aimed to identify preoperative anatomical landmarks and postoperative pump position, associated with HRAEs during LVAD support. METHODS: Pre- and postoperative chest X-ray measures (≤14 days pre-implantation, first postoperative standing, 6, 12, 18, and 24 months post-implantation) were analyzed for their association with HRAEs over 24 months in 33 HeartMate 3 (HM3) patients (15.2% female, age 66 (9.5) years). RESULTS: HM3 patients with any HRAE showed significantly lower preoperative distances between left ventricle and thoracic outline (dLVT) (25.3 ± 10.2 mm vs. 40.3 ± 15.5 mm, p = 0.004). A ROC-derived cutoff dLVT ≤ 29.2 mm provided 85.7% sensitivity and 72.2% specificity predicting any HRAE during HM3 support (76.2% (>29.2 mm) vs. 16.7% (≤29.2 mm) freedom from HRAE, p < 0.001) and significant differences in cardiothoracic ratio (0.58 ± 0.04 vs. 0.62 ± 0.04, p = 0.045). Postoperative X-rays indicated lower pump depths in patients with ischemic strokes (9.1 ± 16.2 mm vs. 38.0 ± 18.5 mm, p = 0.007), reduced freedom from any neurological event (pump depth ≤ 28.7 mm: 45.5% vs. 94.1%, p = 0.004), and a significant correlation between pump depth and inflow cannula angle (r = 0.66, p < 0.001). Longitudinal changes were observed in heart-pump width (F(4,60) = 5.61, p < 0.001). CONCLUSION: Preoperative X-ray markers are associated with postoperative HRAE occurrence. Applying this knowledge in clinical practice may enhance risk stratification, guide therapy optimization, and improve HM3 recipient management.

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Navigational abilities decline with age, but the cognitive underpinnings of this cognitive decline remain partially understood. Navigation is guided by landmarks and self-motion cues, that we address when estimating our location. These sources of spatial information are often associated with noise and uncertainty, thus posing a challenge during navigation. To overcome this challenge, humans and other species rely on navigational cues according to their reliability: reliable cues are highly weighted and therefore strongly influence our spatial behavior, compared to less reliable ones. We hypothesize that older adults do not efficiently weigh spatial cues, and accordingly, the reliability levels of navigational cues may not modulate their spatial behavior, as with younger adults. To test this, younger and older adults performed a virtual navigational task, subject to modified reliability of landmarks and self-motion cues. The findings revealed that while increased reliability of spatial cues improved navigational performance across both age groups, older adults exhibited diminished sensitivity to changes in landmark reliability. The findings demonstrate a cognitive mechanism that could lead to impaired navigation abilities in older adults.

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BACKGROUND: Fluoroscopy guided interventions (FGIs) pose a risk of prolonged radiation exposure; personalized patient dosimetry is necessary to improve patient safety during these procedures. However, current FGIs systems do not capture the precise exposure regions of the patient, making it challenging to perform patient-procedure-specific dosimetry. Thus, there is a pressing need to develop approaches to extract and use this information to enable personalized radiation dosimetry for interventional procedures. PURPOSE: To propose a deep learning (DL) approach for the automatic localization of 3D anatomical landmarks on randomly collimated and magnified 2D head fluoroscopy images. MATERIALS AND METHODS: The model was developed with datasets comprising 800 000 pseudo 2D synthetic images (mixture of vessel-enhanced and non-enhancement), each with 55 annotated anatomical landmarks (two are landmarks for eye lenses), generated from 135 retrospectively collected head computed tomography (CT) volumetric data. Before training, dynamic random cropping was performed to mimic the varied field-size collimation in FGI procedures. Gaussian-distributed additive noise was applied to each individual image to enhance the robustness of the DL model in handling image degradation that may occur during clinical image acquisition in a clinical environment. The model was trained with 629 370 synthetic images for approximately 275 000 iterations and evaluated against a synthetic image test set and a clinical fluoroscopy test set. RESULTS: The model shows good performance in estimating in- and out-of-image landmark positions and shows feasibility to instantiate the skull shape. The model successfully detected 96.4% and 92.5% 2D and 3D landmarks, respectively, within a 10 mm error on synthetic test images. It demonstrated an average of 3.6 ± 2.3 mm mean radial error and successfully detected 96.8% 2D landmarks within 10 mm error on clinical fluoroscopy images. CONCLUSION: Our deep-learning model successfully localizes anatomical landmarks and estimates the gross shape of skull structures from collimated 2D projection views. This method may help identify the exposure region required for patient-specific organ dosimetry in FGIs procedures.

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Perineural anesthesia of the tibial nerve can be performed ultrasound-guided or blindly, with the latter still being commonly used in equine practice due to practical constraints, despite its lower accuracy and hence, common failure to achieve desensitization. This may be associated with anatomical variations or inadequate landmarks for injection. To examine the course of the tibial nerve, document potential anatomical variations, and determine optimal landmarks for perineural injection, dissection was conducted along the medial aspect of the tibia in 10 paired cadaver hindlimbs. No anatomical variations of the tibial nerve were observed. Mean tibial nerve thickness was 6 ± 1 mm. The junction with the plantar nerves was located at a maximum of 85 mm and the junction with the medial cutaneous branch was at a maximum of 150 mm proximal to the proximal aspect of the calcaneal tubercle. The mean distance of the tibial nerve to the cranial border of the superficial digital flexor was 11 ± 6 mm. In conclusion, problems with perineural anesthesia of the tibial nerve cannot simply be attributed to anatomical variations. The thickness of the nerve and the amount of perineural tissue may present specific challenges for achieving adequate desensitization. Our results support the generally recommended site for tibial nerve perineural injection at 100 mm proximal to the calcaneal tubercle and 11 mm cranial to the superficial digital flexor.

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Objective: Tibial plateau fractures are common intra-articular fractures that pose classification and treatment challenges for orthopedic surgeons. Objective: This study examines the value of 3D printing for classifying and planning surgery for complex tibial plateau fractures. Methods: We reviewed 54 complex tibial plateau fractures treated at our hospital from January 2017 to January 2019. Patients underwent preoperative spiral CT scans, with DICOM data processed using Mimics software. 3D printing technology created accurate 1:1 scale models of the fractures. These models helped subdivide the fractures into seven types based on the tibial plateau's geometric planes. Surgical approaches and simulated operations, including fracture reduction and plate placement, were planned using these models. Results: The 3D models accurately depicted the direction and extent of fracture displacement and plateau collapse. They facilitated the preoperative planning, allowing for precise reconstruction strategies and matching intraoperative details with the pre-printed models. Post-surgery, the anatomical structure of the tibial plateau was significantly improved in all 54 cases. Conclusion: 3D printing effectively aids in the classification and preoperative planning of complex tibial plateau fractures, enhancing surgical outcomes and anatomical restoration. Level of Evidence IV, Prospective Study.

Objetivo: As fraturas do planalto tibial são fraturas intra-articulares comuns de classificação e tratamento desafiadores aos cirurgiões ortopédicos. Objetivo: Este estudo investiga o uso de impressão 3D para classificar e planejar a cirurgia de fraturas complexas do planalto tibial. Métodos: 54 fraturas complexas do planalto tibial tratadas em nosso hospital de janeiro de 2017 a janeiro de 2019 foram revisadas. Os pacientes foram submetidos a tomografias computadorizadas em espiral pré-operatórias, com dados DICOM processados usando o software Mimics. A tecnologia de impressão 3D gerou modelos precisos em escala 1:1 das fraturas. Estes modelos ajudaram a subdividir as fraturas em sete tipos com base nos planos geométricos do planalto tibial. As abordagens cirúrgicas e as operações simuladas, incluindo a redução da fratura e a colocação de placa, foram planejadas utilizando estes modelos. Resultados: Os modelos 3D representaram com precisão a direção e a extensão da deslocação da fratura e do colapso do planalto. Os modelos facilitaram o planejamento pré-operatório, viabilizando estratégias de reconstrução precisas e a correspondência dos detalhes intraoperatórios com os modelos pré-impressos. Após a cirurgia, a estrutura anatômica do planalto tibial melhorou significativamente em todos os 54 casos. Conclusão: A impressão 3D ajuda na classificação e no planejamento pré-operatório de fraturas complexas do planalto tibial, melhorando os resultados cirúrgicos e a restauração anatômica. Nível de Evidência IV, Estudo Prospectivo.

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PURPOSE: This study aimed to examine and analyze the presence of sexual dimorphism and symmetry/asymmetry in fixed cadaveric heads and their contributions to clinical practice. METHODS: Measurements were conducted on 6 cadavers and 24 fixed cadaveric heads (n = 30) using a digital microcaliper to assess cranial dimensions, including surgical landmarks, facial index (FI), orbital index (OI), and the danger triangle of the face, offering crucial references for surgeons during surgical interventions. RESULTS: Analyses were conducted on cadavers consisting of 10 females (33.3%) and 20 males (66.7%). Males demonstrated significantly higher values than females in terms of Zy-Zy (Zy = Zygion), nasal body, and width/length of the columella. Hyperleptoprosop types were the most frequently observed, followed by the leptoprosop type. Females exhibited megaseme characteristics according to OI on both sides. Additionally, the danger triangle of the face was greater in males compared than in females, suggesting a higher risk of infection in this region among males. CONCLUSION: The observed sex differences in facial and nasal dimensions, along with facial indices, are crucial for customizing surgical procedures to individual patients. For example, the greater distance in the danger triangle among males highlights the importance of considering anatomical variations to avoid complications, such as septic cavernous sinus thrombosis. Integrating these measurements into preoperative planning can enhance the precision of facial reconstruction and aesthetic surgeries, thereby improving patient outcomes and safety.

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OBJECTIVE: The aim of this study was to estimate the chronological age (CA) of a growing individual using a new machine learning approach on Cone Beam Computed Tomography (CBCT). MATERIALS AND METHODS: The dataset included 48 CBCT and hand-wrist radiographs of growing individuals. 12 landmarks related to trigeminal trajectories were plotted on each CBCT and principal component analysis was applied for dimensionality reduction. The estimated CA was obtained using a decision tree. Finally, a genetic algorithm was implemented to select the best set of landmarks that would optimize the estimation. The age was also assessed following Greulich and Pyle's (GP) method on hand-wrist radiographs. The results (GP and Machine Learning) were then compared to the true CA. RESULTS: Among the 12 landmarks, the genetic algorithm selected 7 optimal features, and 12 principal components out of 36. The best results for age prediction were obtained by a combination of genetic algorithm, principal component analysis, and regression tree where the Mean Squared Error (MSE) and Mean Absolute Error (MAE) were respectively 1.29 and 0.92. These outcomes showed improved accuracy compared to those of the hand-wrist method (MSE = 2.038 and MAE = 1.775). CONCLUSIONS: A numerical application on a dataset of CBCT showed that the proposed machine learning method achieved an improved accuracy compared to conventional methods and had satisfying performance in assessing age for forensic purposes. Validation of the presented method on a larger and more diverse sample would pave the way for future applications in forensic science as a tool for age prediction.

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INTRODUCTION: Central venous catheter (CVC) tip placement guided by chest X-ray (CXR) landmarks is currently prone to inconsistency and malpositioning. This study aims to better define the relationship between the cavoatrial junction (CAJ) and selected X-ray landmarks. METHODS: Chest CTs of 100 patients were retrospectively assessed. CT images were converted to a 'virtual CXR' using a digital workstation, enabling simultaneous localisation of the CAJ and evaluation of CXR landmarks. Vertical distances between the CAJ and selected landmarks were measured for each patient. Measurements were assessed for correlation with age and compared between age groups and sexes. RESULTS: The mean vertical distance of the following landmarks above the CAJ was found: the carina (46.2 mm), the intersection of the bronchus intermedius and the right heart border (7.6 mm) and the superior inflection of the right heart border (Sup-RHB) (13.0 mm). The maximum lateral bulge of the right heart border (Lat-RHB) was 18.4 mm below the CAJ. A new landmark: the mid-superior right heart border, defined as the mid-point between the Sup-RHB and Lat-RHB, was the closest to the CAJ, lying 2.6 mm below the CAJ. CONCLUSION: We propose that the CVC tip can be placed at the mid-superior right heart border landmark.

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Purpose: Traditional CT acquisition planning is based on scout projection images from planar anterior-posterior and lateral projections where the radiographer estimates organ locations. Alternatively, a new scout method utilizing ultra-low dose helical CT (3D Landmark Scan) offers cross-sectional imaging to identify anatomic structures in conjunction with artificial intelligence based Anatomic Landmark Detection (ALD) for automatic CT acquisition planning. The purpose of this study is to quantify changes in scan length and radiation dose of CT examinations planned using 3D Landmark Scan and ALD and performed on next generation wide volume CT versus examinations planned using traditional scout methods. We additionally aim to quantify changes in radiation dose reduction of scans planned with 3D Landmark Scan and performed on next generation wide volume CT. Methods: Single-center retrospective analysis of consecutive patients with prior CT scan of the same organ who underwent clinical CT using 3D Landmark Scan and automatic scan planning. Acquisition length and dose-length-product (DLP) were collected. Data was analyzed by paired t-tests. Results: 104 total CT examinations (48.1 % chest, 15.4 % abdomen, 36.5 % chest/abdomen/pelvis) on 61 individual consecutive patients at a single center were retrospectively analyzed. 79.8 % of scans using 3D Landmark Scan had reduction in acquisition length compared to the respective prior acquisition. Median acquisition length using 3D Landmark Scan was 26.7 mm shorter than that using traditional scout methods (p < 0.001) with a 23.3 % median total radiation dose reduction (245.6 (IQR 150.0-400.8) mGy cm vs 320.3 (IQR 184.1-547.9) mGy cm). CT dose index similarly was overall decreased for scans planned with 3D Landmark and ALD and performed on next generation CT versus traditional methods (4.85 (IQR 3.8-7) mGy vs. 6.70 (IQR 4.43-9.18) mGy, respectively, p < 0.001). Conclusion: Scout imaging using reduced dose 3D Landmark Scan images and Anatomic Landmark Detection reduces acquisition range in chest, abdomen, and chest/abdomen/pelvis CT scans. This technology, in combination with next generation wide volume CT reduces total radiation dose.

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INTRODUCTION: Ultrasound examination of the left adrenal gland is generally associated with relatively low sensitivity and specificity and is strongly influenced by the operator's experience, patient characteristics, and the type of equipment available. In particular, the left adrenal gland remains a structure that is difficult to investigate, even in expert hands. The possibility of improving the ultrasound exploitability of the left adrenal gland and therefore contributing to enhancing the overall diagnostic sensitivity of the technique, allowing for a more widespread application, could be represented by the addition, alongside traditional structural landmarks, of vascular landmarks. The improvement in the diagnostic sensitivity of ultrasound may allow for the use of this technique in selected categories of patients, particularly in the remote monitoring of already-known adrenal pathologies. METHODOLOGY: In ultrasound, the normal adrenal gland is described as a solid formation of 6-8 +/-2 mm in thickness with the shape of an inverted V or Y letter or a λ shape consisting of a thin, linear, hyperechoic (medullary) central area surrounded by a hypoechoic (cortical) layer and possibly by a capsule that delimits it from the surrounding adipose tissue of the adrenal lodge. The ultrasound exploration of the adrenal gland is traditionally performed using a Convex 1-6 mHz probe, using structural landmarks such as the liver, spleen, upper renal pole, and diaphragm. On the right side, the liver provides a good acoustic window to the adrenal space, allowing visualization of the adrenal gland in approximately 90% of cases [1x, 2x]. On the left side, the spleen is used as an acoustic window, but its smaller size compared to the liver often cannot overcome the acoustic barrier represented by residual gas in the gastric and transverse colon/left colic flexure, even after intestinal preparation, reducing the possibility of visualizing the left adrenal gland up to 40-50% [1x, 2xy]. The exploration initially takes place with the patient supine to reduce meteoric overlap, then in the right lateral decubitus position; once the upper pole of the left kidney is identified with longitudinal and coronal sections along the mid and posterior axillary line, the left adrenal gland is located in the triangular space between the spleen, upper renal pole, and diaphragmatic crux by angling the probe anteriorly. As the kidney section decreases and disappears, the adrenal region becomes visible. Once the location is identified, the probe can be rotated on a traverse plane, considering that the left adrenal gland is medially located between the upper renal pole and the renal hilum, with the gland lying between the aorta medially and the kidney laterally. Considering that most adrenal expansions on the left tend to develop downward and inward, the left adrenal gland can also be explored, especially through an anterior approach, both in the long and short axes, using vascular landmarks, given the tight and consistent anatomical relationships of the gland with the large venous and arterial vessels in the region. The presence of gas-filled hollow organs can be partially reduced by conducting the exploration with moderate and constant pressure with the probe to displace them from the field of view. The vascular landmarks are represented by the: 1) abdominal aorta at the level of the emergence of the superior mesenteric artery, 2) the splenic vein, and 3) the vascular pedicle of the left kidney. The adrenal gland is located in the space between the aorta medially, the renal pedicle caudally, and the splenic vein anteriorly. Therefore, with a left paramedian axial section, the abdominal aorta is sought at the level of D12, where the superior mesenteric artery originates. Aligning with the splenic vein, which acts as the roof of the space under examination, the area of interest is explored by tilting the probe superiorly and medially towards the aorta, inferiorly and medially towards the left renal vein, and superiorly and laterally towards the renal border, trying to maintain the view of the splenic vein as the true anterior-lateral margin of the area. This position makes it possible to explore the tail of the pancreas and the Treitz. DISCUSSION: The ultrasound examination of the adrenal gland in adults is considered a method with low sensibility and highly operator -, patient-, and instrument-dependent compared to CT and MRI [3X] and currently has a limited and selective role in the management of patients with adrenal masses [4-6]. According to the International LLGG guidelines, the preferred methods for characterizing adrenal masses are CT, MRI, and PET/TC with 18F-fluorodeoxyglucose [4]. However, exploration of the adrenal glands has been considered an integral part of abdominal ultrasound studies since the 1990s [1X, 2X]. Under favorable conditions, the method is able to detect both neoplastic and non-neoplastic pathologies affecting the organ, contributing to the discovery of incidentalomas in this setting during an examination performed for reasons or symptoms not immediately related to the presence of an adrenal mass. [5]. The prevalence of adrenal incidentalomas detected during abdominal diagnostic investigations is reported to be around 5% of cases [7-10]. The sensitivity, in experienced hands, can be high even for masses smaller than 20 mm, especially on the right side [7]. The ultrasound examination may be indicated if the diagnostic workup of the adrenal mass does not reveal an immediate surgical indication and instead requires periodic monitoring. In cases where the conditions allow for accurate visualization and measurement of the lesion, for the absence of radiation exposure, simplicity of execution, and low cost, ultrasound examination may be preferred to CT for long-term surveillance [6-12], especially in young individuals. CONCLUSION: The addition of non-conventional acoustic windows and vascular landmarks characterized by anatomical constancy to the standard ultrasound examination can contribute to improving the sensitivity of the method, allowing for the identification of a greater number of incidentalomas and expanding the population that may benefit from ultrasound surveillance of known adrenal masses, especially of the left adrenal gland. A comparative study between the gold standard and the ultrasound method enhanced by vascular landmarks is desirable to quantify any potential improvement in sensitivity and specificity of the method in exploring the adrenal gland. This would serve as a premise for its practical application on a larger scale.

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This work proposes a functional data analysis approach for morphometrics in classifying three shrew species (S. murinus, C. monticola, and C. malayana) from Peninsular Malaysia. Functional data geometric morphometrics (FDGM) for 2D landmark data is introduced and its performance is compared with classical geometric morphometrics (GM). The FDGM approach converts 2D landmark data into continuous curves, which are then represented as linear combinations of basis functions. The landmark data was obtained from 89 crania of shrew specimens based on three craniodental views (dorsal, jaw, and lateral). Principal component analysis and linear discriminant analysis were applied to both GM and FDGM methods to classify the three shrew species. This study also compared four machine learning approaches (naïve Bayes, support vector machine, random forest, and generalised linear model) using predicted PC scores obtained from both methods (a combination of all three craniodental views and individual views). The analyses favoured FDGM and the dorsal view was the best view for distinguishing the three species.

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