Identification Of Anatomical Structures Research Articles

Outcomes of ventricular tachycardia ablation with intracardiac echocardiography-a retrospective cohort study of the national inpatient sample

Abstract Background Intracardiac echocardiography (ICE) is being increasingly used in VT ablation. Sparse literature indicates that ICE reduces repeat VT ablation and VT-related admissions (1). Objective To determine if ICE reduced procedural complications, mortality, length of stay, and hospitalization costs in VT ablation. Methods Utilizing the National Inpatient Sample (NIS) of the years 2016 to 2020, we compared the differences between patients who had VT ablation with and without ICE. We used multivariable logistic and linear regression models as appropriate to determine if ICE was associated with improved outcomes as defined above. Results We included 15,480 hospitalizations (95% CI 14,513-16,446) with VT ablations. ICE was used in 1815 (11.7%) of the patients. The mortality rate was 2.2%(95% CI 1.1-4.3) in the ICE group and 3.2% (95% CI 2.6-3.9) in the non-ICE group, and composite complications rate was 18.4% (95% CI 14.7-22.7) in the ICE group and 19.2% (17.7-20.8) in the non-ICE group. On univariate and multivariate analysis, ICE was not associated with a decrease in mortality, composite complications, or hospitalization charges but with a reduction in length of stay (Tables 1 and 2). ICE was associated with sepsis on univariate analysis but not on multivariate analysis (aOR 0.51, 95% CI 0.26-1.00, P=0.051) Conclusion Our study demonstrates that ICE was not associated with a reduction in mortality or complications in VT ablation but was associated with a slightly shorter length of stay. Although our observational study did not demonstrate a major benefit with ICE, given the multiple advantages of ICE in VT ablations, such as real-time recognition of myocardial substrate, identification of anatomical structures to guide ablation, and prompt recognition of intra-procedural complications, we recommend randomized controlled studies to evaluate the efficacy of ICE(2). Our study is limited by its retrospective nature and reliance on ICD codes for data extraction.

Enhancing Multi-Object Detection in Ultrasound Images Through Semi-Supervised Learning, Focal Loss and Relation of Frame

ObjectiveTo identify musculoskeletal anatomical structures in real time by using deep learning techniques. MethodsAn automated annotation system based on deep learning neural networks was designed to aid in the real-time identification of anatomical structures. Additionally, novel algorithms aimed at diminishing model training duration while enhancing accuracy were introduced. In this study, we proposed a semi-supervised learning (SSL) approach that substantially reduced annotation time. We also adopted the focal loss (FL) method to enhance the accuracy of challenging structures. Additionally, during the inference stage, we harnessed the temporal continuity of video frames, which involved leveraging information from preceding frames to facilitate recognition of structures in the current image. Training the model through a combination of SSL and FL yielded superior performance compared with supervised learning, while also substantially mitigating any expense linked to annotations. During inference, the incorporation of frame continuity helped to avoid discontinuity and bolster accuracy. ResultsForearm tissue detection was demonstrated by properly configuring the SSL approach, including FL and the filtering threshold. Comparable performance with supervised learning was achieved while only using 30% of the training data. The real-time experimental results also demonstrated that implementing relation of frame reduced the number of missing frames during inference and successfully increased the confidence scores of detected objects. ConclusionThis proposed system has the potential to aid medical professionals in efficiently and effectively diagnosing musculoskeletal disorders, ultimately leading to enhanced patient outcomes.

Artificial intelligence-assisted ultrasound-guided regional anaesthesia: An explorative scoping review.

The present study reviews the available scientific literature on artificial intelligence (AI)-assisted ultrasound-guided regional anaesthesia (UGRA) and evaluates the reported intraprocedural parameters and postprocedural outcomes. A literature search was performed on 19 September2023, using the Medline, EMBASE, CINAHL, Cochrane Library and Google Scholar databases by experts in electronic searching. All study designs were considered with no restrictions regarding patient characteristics or cohort size. Outcomes assessed included the accuracy of AI-model tracking, success at the first attempt, differences in outcomes between AI-assisted and unassisted UGRA, operator feedbackand case-report data. A joint adaptive median binary pattern (JAMBP) has been applied to improve the tracking procedure, while a particle filter (PF) is involved in feature extraction. JAMBP combined with PF was most accurate on all images for landmark identification, with accuracy scores of 0.83, 0.93and 0.93 on original, preprocessedand filtered images, respectively. Evaluation of first-attempt success of spinal needle insertion revealed first-attempt success in most patients. When comparing AI application versus UGRA alone, a significant statistical difference (p < 0.05) was found for correct block view, correct structure identificationand decrease in mean injection time, needle track adjustments and bone encountersin favour of having AI assistance. Assessment of operator feedback revealed that expert and nonexpert operator feedback was overall positive. AI appears promising to enhance UGRA as well as to positively influence operator training. AI application of UGRA may improve the identification of anatomical structures and provide guidance for needle placement, reducing the risk of complications and improving patient outcomes. Level IV.

MADR-Net: multi-level attention dilated residual neural network for segmentation of medical images

Medical image segmentation has made a significant contribution towards delivering affordable healthcare by facilitating the automatic identification of anatomical structures and other regions of interest. Although convolution neural networks have become prominent in the field of medical image segmentation, they suffer from certain limitations. In this study, we present a reliable framework for producing performant outcomes for the segmentation of pathological structures of 2D medical images. Our framework consists of a novel deep learning architecture, called deep multi-level attention dilated residual neural network (MADR-Net), designed to improve the performance of medical image segmentation. MADR-Net uses a U-Net encoder/decoder backbone in combination with multi-level residual blocks and atrous pyramid scene parsing pooling. To improve the segmentation results, channel-spatial attention blocks were added in the skip connection to capture both the global and local features and superseded the bottleneck layer with an ASPP block. Furthermore, we introduce a hybrid loss function that has an excellent convergence property and enhances the performance of the medical image segmentation task. We extensively validated the proposed MADR-Net on four typical yet challenging medical image segmentation tasks: (1) Left ventricle, left atrium, and myocardial wall segmentation from Echocardiogram images in the CAMUS dataset, (2) Skin cancer segmentation from dermoscopy images in ISIC 2017 dataset, (3) Electron microscopy in FIB-SEM dataset, and (4) Fluid attenuated inversion recovery abnormality from MR images in LGG segmentation dataset. The proposed algorithm yielded significant results when compared to state-of-the-art architectures such as U-Net, Residual U-Net, and Attention U-Net. The proposed MADR-Net consistently outperformed the classical U-Net by 5.43%, 3.43%, and 3.92% relative improvement in terms of dice coefficient, respectively, for electron microscopy, dermoscopy, and MRI. The experimental results demonstrate superior performance on single and multi-class datasets and that the proposed MADR-Net can be utilized as a baseline for the assessment of cross-dataset and segmentation tasks.

Diagnostic yield of dental radiography and digital tomosynthesis for the identification of anatomic structures in cats.

Digital tomosynthesis (DT) has emerged as a potential imaging modality for evaluating anatomic structures in veterinary medicine. This study aims to validate the diagnostic yield of DT in identifying predefined anatomic structures in feline cadaver heads, comparing it with conventional intraoral dental radiography (DR). A total of 16 feline cadaver heads were utilized to evaluate 19 predefined clinically relevant anatomic structures using both DR and DT. A semi-quantitative scoring system was employed to characterize the ability of each imaging method to identify these structures. DT demonstrated a significantly higher diagnostic yield compared to DR for all evaluated anatomic structures. Orthogonal DT imaging identified 13 additional anatomic landmarks compared to a standard 10-view feline set obtained via DR. Moreover, DT achieved statistically significant higher scores for each of these landmarks, indicating improved visualization over DR. These findings validate the utility of DT technology in reliably identifying clinically relevant anatomic structures in the cat skull. This validation serves as a foundation for further exploration of DT imaging in detecting dentoalveolar and other maxillofacial bony lesions and pathologies in cats.

Ultrasound identification of hand and wrist anatomical structures by hand surgeons new to ultrasonographic techniques.

Ultrasound is becoming an essential tool for hand surgeons, but most of them are trained on the job, without any diploma or dedicated training. The aim of this study was to assess the ability of hand surgeons new to ultrasound to identify hand and wrist anatomical structures. A monocentric study was conducted from January 2022 to April 2022. Ten residents and five attending hand surgeons, ultrasound novices, were involved in this study. The participants underwent two tests, wherein they were required to identify 17 anatomical structures using ultrasound, on the same subject. The second test was similar and carried out 2 to 6 weeks later by all participants. The number of structures successfully identified and if it was the case, the detection time per structure, were recorded. The correlations between participants age, years of surgical experience, surgical background (orthopedic or plastic) and the ability to perform immediately during the first test or to progress between the two tests were also assessed. The average number of structures identified during the first test (T1) was 14.1+/-2.1 (82.9%), versus 16.2+/-0.8 (95.3%) structures during the second test (T2) (p = 0.001). The mean detection time per structure was 53.4 +/- 18.9s during T1 versus 27.7 +/- 7.2s during T2 (p < 0.0001). A moderate negative correlation between the progression in the number of anatomical structures identified between the two tests and the years of surgical experience (ρ=-0.56; p = 0.029) was found. The other parameters were neither correlated with the ability to perform at the first test nor with the progression between the two tests. Hand surgeons new to ultrasound are most of the time able to identify hand and wrist anatomical structures. Comparison of their first and second tests showed significant potential for improvement in anatomical structure identification and detection time of those, especially in surgeons with limited surgical experience.

Retrospective evaluation of condylar morphology using panoramic radiography in a sample of Turkish population.

The temporomandibular joint is one of the most complex anatomic structures. It takes a great role in masticatory system and helps to make possible some functions such as speaking, chewing and swallowing. Clinicians should have sufficient anatomical knowledge to assess relationships of the hard and soft tissues, including the mandibular condyle, glenoid fossa, articular eminence of the temporal bone, the articular disc and its attachments. The aim of this study was to evaluate the frequency of different types of mandibular condyles and its distribution according to the age and gender. It was also evaluated whether the condyle types were bilaterally symmetrical or not. A total of 1315 digital panoramic images which obtained from the patients suffering from the dental problems were assessed. Demographic data, condylar morphology were noted. All obtained data were analysed by using descriptive statistics. Morphology of mandibular condyles were classified into four shapes as identified in other studies, namely: type I - oval shape, type II - diamond shape, type III - bird beak shape, type IV - crooked finger shape. Two independent examiners, who have 19 and 7 years of experience in oral and dentomaxillofacial radiology, made a consensus and evaluated all images. A total of 1315 digital panoramic images were assessed. Seven hundred sixty-seven [58.3%] the patients were female and 548 [41.6%] were male. The age range of patients was from 18 to 84 years. Right-left condyle types were found to be symmetrical in the range of 67% of the subpopulation examined in the study. For the consensus, 'oval' condyle was common on both the right and left, while 'crooked finger' condyle was the rarest. The temporomandibular joint is the most important structure for all jaw functions such as speech, swallowing. In order for all these functions to continue in a healthy way, the anatomical structure should be known very well down to the finest detail. Identification of anatomical structures and their variations can play an important role in implant dentistry. Clinicians commonly prefer conventional radiologic methods to evaluate dentomaxillofacial region. Although the most of the variations are asymptomatic and require no treatment,correct identification of these findings will reduce unnecessary further diagnostic assessments and will provide more appropriate treatment plans.

Computed Tomography Evaluation of Frozen or Glycerinated Bradypus variegatus Cadavers: A Comprehensive View with Emphasis on Anatomical Aspects

Bradypus variegatus has unique anatomical characteristics, and many of its vascular and digestive tract aspects have yet to be clearly understood. This lack of information makes clinical diagnoses and surgical procedures difficult. The aim of this study was to evaluate the anatomical aspects of frozen and glycerinated corpses of B. variegatus using computed tomography (CT), emphasizing vascular and digestive contrast studies. Nine corpses that died during routine hospital were examined via CT in the supine position with scanning in the craniocaudal direction. In frozen cadavers, the contrast was injected into a cephalic vein after thawing and, subsequently, was administered orally. In addition to bone structures, CT allowed the identification of organs, soft tissues, and vascular structures in specimens. Visualization of soft tissues was better after contrast been administered intravenously and orally, even without active vascularization. Furthermore, the surfaces of the organs were highlighted by the glycerination method. With this technique, it was possible to describe part of the vascularization of the brachial, cervical, thoracic, and abdominal regions, in addition to highlighting the esophagus and part of the stomach. CT can be another tool for the evaluation of B. variegatus cadavers by anatomists or pathologists, contributing to the identification of anatomical structures.

Living and post-mortem CT scans in the gross anatomy lab: A study investigating differences in first-year medical students' exam performance and perceptions.

Basic competency in radiological imaging is essential for physicians to identify and manage diseases. An optimal place in which to include imaging in the medical curriculum is during anatomy as students can correlate the 3D anatomy from their body donors with the 2D cross-sectional anatomy. The goal of this project was to enhance first-year medical students' knowledge of cross-sectional imaging in the gross anatomy lab and to investigate whether there are benefits to learning cross sectional imaging via scans from body donors versus living individuals. Student participant performance was evaluated on laboratory practical examinations, CT image questions and spatial anatomical knowledge in the thorax and abdomen sections of gross anatomy. Students learned the cross-sectional imaging during dissections where they accessed the images relevant to their study on Pacsbin, a web-based Digital Imaging and Communication in Medicine viewer, via iPads. Results showed no statistically significant differences in practical examination scores, spatial anatomical knowledge, or identification of anatomical structures on CT image questions between participants who learned from images on body donors versus living individuals. In a questionnaire given at the end of the course, participants cited that the CT images improved their anatomical and imaging knowledge and that they felt better prepared to use imaging software and interpret diagnostic imaging results upon entering clerkships. While there were no differences in academic performance between the groups, positive outcomes regarding student perceptions of anatomical and imaging knowledge and preparedness for use of imaging software were identified in this study.

Comparison of quality and interpretation of newborn ultrasound screening examinations for developmental dysplasia of the hip by basically trained nurses and junior physicians with no previous ultrasound experience.

We are obliged to give babies the chance to profit from a nationwide screening of developmental dysplasia of the hip in very rural areas of Mongolia, where trained physicians are scarce. This study aimed to compare the quality and interpretation of hip ultrasound screening examinations performed by nurses and junior physicians. A group of 6 nurses and 6 junior physician volunteers with no previous ultrasound experience underwent Graf's standard training in hands-on practice. Newborns were examined before discharge from the hospital, according to the national guideline. Two standard documentation images of each hip were saved digitally. The groups were compared on the proportion of good quality of sonograms and correct interpretation. Two Swiss supervisors' agreed diagnosis according to Graf was considered the final reference for the study purposes. A total of 201 newborns (402 hips or 804 sonograms) were examined in the study, with a mean age of 1.3±0.8 days at examination. Junior physicians examined 100 newborns (200 hips or 400 sonograms), while nurses examined 101 newborns (202 hips or 404 sonograms). The study subjects of the two groups were well balanced for the distribution of baseline characteristics. The study observed no statistically significant difference in the quality of Graf's standard plane images between the providers. Eventually, 92.0% (92) of the physician group and 89.1% (90) of the nurse group were correctly diagnosed as "Group A" (Graf's Type 1 hip) or "Non-Group A" hips (p = 0.484). The most common errors among the groups were a missing lower limb, wrong measurement lines, and technical problems. Our study provides evidence that while there might be a trend of slightly more technical mistakes in the nurse group, the overall diagnosis accuracy is similar to junior physicians after receiving standard training in Graf's hip ultrasound method. However, after basic training, regular quality control is a must and all participants should receive refresher trainings. More specifically, nurses need training in the identification of anatomical structures.

Use of artificial intelligence in total mesorectal excision in rectal cancer surgery: State of the art and perspectives

BACKGROUND Colorectal cancer is a major public health problem, with 1.9 million new cases and 953000 deaths worldwide in 2020. Total mesorectal excision (TME) is the standard of care for the treatment of rectal cancer and is crucial to prevent local recurrence, but it is a technically challenging surgery. The use of artificial intelligence (AI) could help improve the performance and safety of TME surgery. AIM To review the literature on the use of AI and machine learning in rectal surgery and potential future developments. METHODS Online scientific databases were searched for articles on the use of AI in rectal cancer surgery between 2020 and 2023. RESULTS The literature search yielded 876 results, and only 13 studies were selected for review. The use of AI in rectal cancer surgery and specifically in TME is a rapidly evolving field. There are a number of different AI algorithms that have been developed for use in TME, including algorithms for instrument detection, anatomical structure identification, and image-guided navigation systems. CONCLUSION AI has the potential to revolutionize TME surgery by providing real-time surgical guidance, preventing complications, and improving training. However, further research is needed to fully understand the benefits and risks of AI in TME surgery.

Variability between human experts and artificial intelligence in identification of anatomical structures by ultrasound in regional anaesthesia: a framework for evaluation of assistive artificial intelligence

BackgroundScanNavTMAnatomy Peripheral Nerve Block (ScanNav™) is an artificial intelligence (AI)-based device that produces a colour overlay on real-time B-mode ultrasound to highlight key anatomical structures for regional anaesthesia. This study compares consistency of identification of sono-anatomical structures between expert ultrasonographers and ScanNav™. MethodsNineteen experts in ultrasound-guided regional anaesthesia (UGRA) annotated 100 structures in 30 ultrasound videos across six anatomical regions. These annotations were compared with each other to produce a quantitative assessment of the level of agreement amongst human experts. The AI colour overlay was then compared with all expert annotations. Differences in human–human and human–AI agreement are presented for each structure class (artery, muscle, nerve, fascia/serosal plane) and structure. Clinical context is provided through subjective assessment data from UGRA experts. ResultsFor human–human and human–AI annotations, agreement was highest for arteries (mean Dice score 0.88/0.86), then muscles (0.80/0.77), and lowest for nerves (0.48/0.41). Wide discrepancy exists in consistency for different structures, both with human–human and human–AI comparisons; highest for sartorius muscle (0.91/0.92) and lowest for the radial nerve (0.21/0.27). ConclusionsHuman experts and the AI system both showed the same pattern of agreement in sono-anatomical structure identification. The clinical significance of the differences presented must be explored; however the perception that human expert opinion is uniform must be challenged. Elements of this assessment framework could be used for other devices to allow consistent evaluations that inform clinical training and practice. Anaesthetists should be actively engaged in the development and adoption of new AI technology.

Near-infrared fluorescence tattooing: a new approach for endoscopic marking of tumors in minimally invasive colorectal surgery using a persistent near-infrared marker

IntroductionIntraoperative accurate localization of tumors in the lower gastrointestinal tract is essential to ensure oncologic radicality. In minimally invasive colon surgery, tactile identification of tumors is challenging due to diminished or absent haptics. In clinical practice, preoperative endoscopic application of a blue dye (ink) to the tumor site has become the standard for marking and identification of tumors in the colon. However, this method has the major limitation that accidental intraperitoneal spillage of the dye can significantly complicate the identification of anatomical structures and surgical planes. In this work, we describe a new approach of NIR fluorescent tattooing using a near-infrared (NIR) fluorescent marker instead of a blue dye (ink) for endoscopic tattooing.MethodsAFS81x is a newly developed NIR fluorescent marker. In an experimental study with four domestic pigs, the newly developed NIR fluorescent marker (AFS81x) was used for endoscopic tattooing of the colon. 7–12 endoscopic submucosal injections of AFS81x were placed per animal in the colon. On day 0, day 1, and day 10 after endoscopic tattooing with AFS81x, the visualization of the fluorescent markings in the colon was evaluated during laparoscopic surgery by two surgeons and photographically documented.ResultsThe detection rate of the NIR fluorescent tattoos at day 0, day 1, and day 10 after endoscopic tattooing was 100%. Recognizability of anatomical structures during laparoscopy was not affected in any of the markings, as the markings were not visible in the white light channel of the laparoscope, but only in the NIR channel or in the overlay of the white light and the NIR channel of the laparoscope. The brightness, the sharpness, and size of the endoscopic tattoos did not change significantly on day 1 and day 10, but remained almost identical compared to day 0.ConclusionThe new approach of endoscopic NIR fluorescence tattooing using the newly developed NIR fluorescence marker AFS81x enables stable marking of colonic sites over a long period of at least 10 days without compromising the recognizability of anatomical structures and surgical planes in any way.

Compartments of the crural fascia: clinically relevant ultrasound, anatomical and histological findings

PurposeCompartment syndrome is a surgical emergency that can occur in any part of the body and can cause cell necrosis when maintained over time. The resulting defects can affect the nerves, muscle cells, bone tissue, and other connective tissues inside the compartment, and fasciotomy has to be performed. The anatomical and histological characteristics of the leg make acute, chronic, and exertional compartment syndrome more likely in this limb. For these reasons, knowledge of the ultrasound, anatomical, and histological features of the crural fascia can help in the treatment of leg compartment syndrome.MethodsTwenty-one cryopreserved lower limbs from adult cadavers and from one 29-week-old fetus were obtained from the dissection room. They were examined by ultrasound and a subsequent anatomical dissection and microscopy to study the crural fascia and its relationship with the different muscles. Anthropometric measurements were taken of the distances from the head of the fibula and lateral malleolus to the origin of the tibialis anterior muscle in the crural fascia, the exit of the superficial fibular nerve, and the fascia covering the deep posterior muscles of the leg.ResultsThe crural fascia has very important clinical relationships, which can be identified by ultrasound, as the origin of the tibialis anterior muscle at 16.25 cm from the head of the fibula and the exit of the superficial fibular nerve that crosses this fascia at 21.25 cm from the head of the fibula. Furthermore, the presence of a septum that fixes the deep posterior muscles of the leg and the vessels and nerve can be seen by ultrasound and can explain the possible development of a posterior compartmental syndrome of the leg. Awareness of these features will help to keep these structures safe during the surgical treatment of compartment syndrome.ConclusionThe ultrasound study allows identification of anatomical structures in the leg and, thus, avoids damage to them during surgery for compartmental syndromes.

Usefulness of T2-Weighted Images with Deep-Learning-Based Reconstruction in Nasal Cartilage.

This study aims to evaluate the feasibility of visualizing nasal cartilage using deep-learning-based reconstruction (DLR) fast spin-echo (FSE) imaging in comparison to three-dimensional fast spoiled gradient-echo (3D FSPGR) images. This retrospective study included 190 set images of 38 participants, including axial T1- and T2-weighted FSE images using DLR (T1WIDL and T2WIDL, belong to FSEDL) and without using DLR (T1WIO and T2WIO, belong to FSEO) and 3D FSPGR images. Subjective evaluation (overall image quality, noise, contrast, artifacts, and identification of anatomical structures) was independently conducted by two radiologists. Objective evaluation including signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) was conducted using manual region-of-interest (ROI)-based analysis. Coefficient of variation (CV) and Bland-Altman plots were used to demonstrate the intra-rater repeatability of measurements for cartilage thickness on five different images. Both qualitative and quantitative results confirmed superior FSEDL to 3D FSPGR images (both p < 0.05), improving the diagnosis confidence of the observers. Lower lateral cartilage (LLC), upper lateral cartilage (ULC), and septal cartilage (SP) were relatively well delineated on the T2WIDL, while 3D FSPGR showed poorly on the septal cartilage. For the repeatability of cartilage thickness measurements, T2WIDL showed the highest intra-observer (%CV = 8.7% for SP, 9.5% for ULC, and 9.7% for LLC) agreements. In addition, the acquisition time for T1WIDL and T2WIDL was respectively reduced by 14.2% to 29% compared to 3D FSPGR (both p < 0.05). Two-dimensional equivalent-thin-slice T1- and T2-weighted images using DLR showed better image quality and shorter scan time than 3D FSPGR and conventional construction images in nasal cartilages. The anatomical details were preserved without losing clinical performance on diagnosis and prognosis, especially for pre-rhinoplasty planning.

Ambient light exposure of photostimulable phosphor plates: is there a safe limit for acceptable image quality?

To subjectively assess radiographs obtained with photostimulable phosphor (PSP) plates exposed to clinical levels of ambient light prior to read-out to potentially set a safe limit for acceptable image quality. Six dental regions of a dry human skull were X-rayed using PSP plates from VistaScan and Express under four exposure times: 0.1, 0.2, 0.32, and 0.4 s. Before read-out, the PSP plates were exposed to ambient light for 0, 5, 10, 30, 60, and 90 s. Six observers were asked to classify the 288 resulting radiographs as acceptable or unacceptable based on the identification of anatomical structures and global image quality. The number of answers classifying radiographs as unacceptable was used to calculate a rejection rate; a pairwise comparison for better image quality was further conducted among radiographs considered acceptable. Reproducibility was tested by having 25% of all experimental groups reassessed. Intra- and interobserver agreement ranged from 0.87 to 1.00 and from 0.81 to 0.92, respectively. Exposure of PSP plates to ambient light increased rejection rates mostly as of 10 s. In the pairwise comparison, subtle differences were observed between radiographs obtained with PSP plates not exposed and those exposed to ambient light for 5 s. Ambient light exposure of PSP plates impairs the image quality of radiographs. A safe limit of ambient light exposure of 5 s for VistaScan and Express should be considered. Ambient light exposure of PSP plates within safe limits can avoid retakes and reduce unnecessary patient exposure to X-rays.

Clutch & Grasp: Activation gestures and grip styles for device-based interaction in medical spatial augmented reality

Presenting medical volume data using augmented reality (AR) can facilitate the identification of anatomical structures, the perception of their spatial relations and the development of mental maps compared to more commonly used monitors. However, interaction methods explored in these conventional settings may not be applicable in AR environments, or perform differently. In terms of mode activation, gestural interaction was shown to be a viable, touchless alternative to traditional input devices, which is desirable in sterile medical use cases. Therefore, we present a user study (n = 21) comparing hand and foot gestures with voice commands for the activation of interaction modes within a projector-based, spatial AR prototype to visualize medical volume data. Interaction itself was performed via hand movements captured by a data glove. Consistent, statistically significant results across measured variables suggest advantages of voice commands. In addition, a second experiment (n = 17) compared the hand-based interaction with two motion-sensitive devices held in power and in precision grip respectively. All modes were activated using voice commands. No considerable differences between tested grip styles could be determined. The findings suggest that the choice of preferable interaction devices is user and use case dependent.

A novel recognition of artificial intelligence in regional anaesthesia

Mechanised analysis of algorithms for problem solving, object recognition and decision-making assistance defines the general concept underlining artificial intelligence (AI).[1] The former presents notable applications in perioperative medicine across diverse situations like depth of anaesthesia monitoring, closed-loop anaesthesia delivery, risk-predictive models, pain-management through objective analgo-scoring, operating-room planning logistics and, guidance of perioperative ultrasonography. The recent Food and Drug Administration (FDA) approval[2] of the Scan Nav™ Anatomy Peripheral Nerve Block (PNB) system (Intelligent Ultrasound Group, Cardiff, United Kingdom)[3] only emerges as a novel recognition of the potential of AI in regional anaesthesia. Worthwhile to mention, Hemmerling et al.[4] described an encouraging seminal use of the robotic ultrasound-guided nerve block system or the Magellan system, almost a decade ago. Employing the same system, Morse et al.[5] went on to compare the performance parameters (learning curve and success rates) and subjective performance variability of manual versus robot-assisted ultrasonographic nerve blocks in a phantom model. The authors found that assistance of nerve blocks, enabled significant faster needle guidance (1.8 [1.6] seconds vs. 0.3 [0.3] seconds; P = 0.007), than for manual blocks. Inter-subject performance variability was also found to be considerably attenuated. Specific to the context of the recently FDA approved software medical device, ScanNav™ Anatomy PNB system uses deep-learning AI technology. During performance of a peripheral nerve block the ScanNav™ system identifies and grades a live ultrasound image using this technology. A distinctive colour overlay of the key sono-anatomical structures during a live ultrasound scan is a characteristic valuable attribute of the system.[3] This enhances standardisation and accuracy of the ultrasound image interpretation. This device colour highlights anatomy of 10 vital regions relevant to ultrasound-guided regional anaesthesia namely Interscalene, Supraclavicular, Axillary and Superior Trunk Brachial plexus of the upper limb; Erector Spinae Plane, Rectus Sheath and Supra-inguinal Fascia Iliaca sheath of truncal structures; and Femoral Nerve, Adductor canal and Popliteal nerve sheath of the lower limb. Furthermore, a 3-dimension inbuilt reference material provides a review of the relevant anatomy, probe-positioning technique; and demonstrates a virtual scan of the selected anatomical region. The system enables adjustments in the intensity of coloured highlighting according to user preference and allows for viewing the unmodified and highlighted images side-by-side for better comprehension of the sono-anatomy. The use of ScanNav™ system thereby facilitates as a labelling device alongside real-time anatomy visualisation during regional anaesthesia. The system also has inbuilt virtual scans that assist the clinician functioning as a 3D reference material of the relevant PNB anatomy scanned. Notably so, the software is compatible with the general-purpose ultrasound systems in addition to being a stand-alone device. Talking of the literature relevant to the ScanNav™ Anatomy PNB system, Bowness et al.[6] compared 240 ultrasound scans performed across 15 expert versus non-expert regional anaesthesia providers on evaluating its' role in promoting the uptake and generalisability of ultrasound-guided regional anaesthesia. The authors outlined that non-experts were more likely to submit positive feedback and less likely to submit negative reviews than the experts (P = 0.001). Positive feedbacks were obtained on the role of the device in training (37/60, 61.7%) and utility for teaching (30/60, 50.0%). Meanwhile the non-experts appreciated the anatomic structure identification and learning, as the contextual benefits, some nonexperts and experts thought the device could decrease the scanning confidence. Additionally, expert providers reported a potentially increased, yet insignificant, risk in 12/254 (4.7%) vs. 8/254 (3.1%, P = 0.362) scans for needle trauma to “safety” structures. The discussion elaborates the tremendous opportunity AI has to offer in guiding regional anaesthesia, awaiting prospective validation outside the core 10 block areas. The utility of this device can be further extended to sympathetic blocks like the stellate-ganglion, celiac-plexus and other blocks for treatment of chronic pain syndromes like complex regional pain syndrome. The times might not be distant when perioperative physicians have routine access to ultrasound machines integrated with AI-assisted colour reframing for anatomical landmark “coding” side by side with the present B-mode, M-mode and colour/pulse Doppler profiling.

Identification of orbital arteries by means of stamp-pad ink on embalmed cadavers

Vascular identification is an effective way of analysing the vascular system from large to very small blood vessels in cadaveric studies. A variety of vascular injection products have been utilised over the past decades to facilitate and demonstrate dissection of the blood vessels. The coloured dye used to demonstrate the branching patterns of the vascular system was introduced by Jean Riolan (1580 to 1657) (Doomernik et al., 2016). Although different identification techniques are available, only a few can be used on the specimens during dissections. A total of 118 human eyes from 59 bodies were dissected and all blood vessels were exposed. The ophthalmic artery (OA) and its branches were identified by means of fine dissections. The aid of a lighted magnifying glass made fine dissections of small blood vessels possible. After removing the orbital fat around the blood vessels, the arteries were then smoothly painted with the red stamp-pad ink and a paintbrush. Specimens were then allowed to dry at room temperature before photographic capturing and recording of the OA and its branches in each of the specimens were made. An accurate identification of the arterial system was possible as the arteries were followed intraorbitally from the point where the OA emerged from the optic canal on course with the optic nerve. All branches of the OA that were present were identified and recorded. The application of stamp-pad ink as a dye is useful in the marking and identification of anatomical structures and can be used in the anatomy training for both undergraduate and postgraduate students.

Application of a Self-developed, Low-budget Indocyanine Green Camera in Surgical Imaging – a Single Institution’s Experiences

Introduction: Indocyanine green is a fluorescent dye, the use of which is becoming more and more widespread in different areas of surgery. Several international studies deal with the dye’s usefulness in intraoperative angiography, the localization of tumors, the more precise identification of anatomical structures, the detection of lymph nodes and lymph ducts, etc. The application of the dye is safe, but a suitable equipment park is required for its use, which entails relatively high costs.Objectives: The aim of our research is to create a detector system on a low budget, to be used safely in everyday practice and to illustrate its operation with practical examples at our own institute.Methods: By modifying a web camera, using filter lenses and special LEDs, we created a device suitable for exciting and detecting indocyanine green fluorescence. We prove its excellent versatility during the following procedures at our institute: breast tumor surgery, kidney transplantation, bowel resection, parathyroid surgery and liver tumor resection.Results: The finished camera has an LED light source with a peak wavelength of 780 nm, and the incoming light is filtered by a bandpass filter with a center wavelength of 832 nm. A low budget ($112), easy-to-use tool was created, which is suitable for taking advantage of the opportunities provided by indocyanine green.