Apple Vision Pro for Healthcare: "The Ultimate Display"? -- Entering the Wonderland of Precision Medicine

At the Worldwide Developers Conference (WWDC) in June 2023, Apple introduced the Vision Pro. The Vision Pro is a Mixed Reality (MR) headset, more specifically it is a Virtual Reality (VR) device with an additional Video See-Through (VST) capability. The VST capability turns the Vision Pro also into an Augmented Reality (AR) device. The AR feature is enabled by streaming the real world via cameras to the (VR) screens in front of the user's eyes. This is of course not unique and similar to other devices, like the Varjo XR-3. Nevertheless, the Vision Pro has some interesting features, like an inside-out screen that can show the headset wearers' eyes to "outsiders" or a button on the top, called "Digital Crown", that allows you to seamlessly blend digital content with your physical space by turning it. In addition, it is untethered, except for the cable to the battery, which makes the headset more agile, compared to the Varjo XR-3. This could actually come closer to the "Ultimate Display", which Ivan Sutherland had already sketched in 1965. Not available to the public yet, like the Ultimate Display, we want to take a look into the crystal ball in this perspective to see if it can overcome some clinical challenges that - especially - AR still faces in the medical domain, but also go beyond and discuss if the Vision Pro could support clinicians in essential tasks to spend more time with their patients.Comment: This is a Preprint under CC BY. This work was supported by NIH/NIAID R01AI172875, NIH/NCATS UL1 TR001427, the REACT-EU project KITE and enFaced 2.0 (FWF KLI 1044). B. Puladi was funded by the Medical Faculty of the RWTH Aachen University as part of the Clinician Scientist Program. C. Gsaxner was funded by the Advanced Research Opportunities Program from the RWTH Aachen Universit

Radiomics in head and neck cancer outcome predictions

The data are publicly available on The Cancer Image Archive (TCIA) [41] website and can be downloaded using the NBIA Data Retriever [42]: https://wiki.cancerimagingarchive.net/display/Public/Head-Neck-PET-CT, accessed on 11 October 2022. The source code is available on GitHub: https://github.com/MariaGoncalves3/Radiomics_for_Head_And_Neck_Cancer, accessed on 11 October 2022.Head and neck cancer has great regional anatomical complexity, as it can develop in different structures, exhibiting diverse tumour manifestations and high intratumoural heterogeneity, which is highly related to resistance to treatment, progression, the appearance of metastases, and tumour recurrences. Radiomics has the potential to address these obstacles by extracting quantitative, measurable, and extractable features from the region of interest in medical images. Medical imaging is a common source of information in clinical practice, presenting a potential alternative to biopsy, as it allows the extraction of a large number of features that, although not visible to the naked eye, may be relevant for tumour characterisation. Taking advantage of machine learning techniques, the set of features extracted when associated with biological parameters can be used for diagnosis, prognosis, and predictive accuracy valuable for clinical decision-making. Therefore, the main goal of this contribution was to determine to what extent the features extracted from Computed Tomography (CT) are related to cancer prognosis, namely Locoregional Recurrences (LRs), the development of Distant Metastases (DMs), and Overall Survival (OS). Through the set of tumour characteristics, predictive models were developed using machine learning techniques. The tumour was described by radiomic features, extracted from images, and by the clinical data of the patient. The performance of the models demonstrated that the most successful algorithm was XGBoost, and the inclusion of the patients’ clinical data was an asset for cancer prognosis. Under these conditions, models were created that can reliably predict the LR, DM, and OS status, with the area under the ROC curve (AUC) values equal to 0.74, 0.84, and 0.91, respectively. In summary, the promising results obtained show the potential of radiomics, once the considered cancer prognosis can, in fact, be expressed through CT scans.This work received funding from the Austrian Science Fund (FWF) KLI 678-B31: “enFaced-Virtual and Augmented Reality Training and Navigation Module for 3D-Printed Facial Defect Reconstructions”,FWF KLI 1044: “enFaced 2.0-Instant AR Tool for Maxillofacial Surgery” (https://enfaced2.ikim.nrw/, accessed on 11 October 2022), “CAMed” (COMET K-Project 871132), which is funded by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT), the Austrian Federal Ministry for Digital and Economic Affairs (BMDW), the Styrian Business Promotion Agency (SFG), and the FCT-Fundação para a Ciência e a Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. Further, we acknowledge the REACT-EU project KITE (Plattform für KI-Translation Essen, https://kite.ikim.nrw/, accessed on 11 October 2022)

Open-Source Skull Reconstruction with MONAI

We present a deep learning-based approach for skull reconstruction for MONAI, which has been pre-trained on the MUG500+ skull dataset. The implementation follows the MONAI contribution guidelines, hence, it can be easily tried out and used, and extended by MONAI users. The primary goal of this paper lies in the investigation of open-sourcing codes and pre-trained deep learning models under the MONAI framework. Nowadays, open-sourcing software, especially (pre-trained) deep learning models, has become increasingly important. Over the years, medical image analysis experienced a tremendous transformation. Over a decade ago, algorithms had to be implemented and optimized with low-level programming languages, like C or C++, to run in a reasonable time on a desktop PC, which was not as powerful as today's computers. Nowadays, users have high-level scripting languages like Python, and frameworks like PyTorch and TensorFlow, along with a sea of public code repositories at hand. As a result, implementations that had thousands of lines of C or C++ code in the past, can now be scripted with a few lines and in addition executed in a fraction of the time. To put this even on a higher level, the Medical Open Network for Artificial Intelligence (MONAI) framework tailors medical imaging research to an even more convenient process, which can boost and push the whole field. The MONAI framework is a freely available, community-supported, open-source and PyTorch-based framework, that also enables to provide research contributions with pre-trained models to others. Codes and pre-trained weights for skull reconstruction are publicly available at: https://github.com/Project-MONAI/research-contributions/tree/master/SkullRe

Variants of arterial supply to the inferior (diaphragmatic) surface of the ventricles of the heart and the influence on age at death

Coronary artery systems of the inferior wall of the ventricles vary considerably. Schlesinger's concept distinguishes dominance of the right or left coronary artery (LCA) or balanced type. LCA dominance has been reported to be associated with increased mortality. Early angiography studies have shown that the anterior interventricular artery (AIVA), a branch of the LCA, often continues on the inferior surface of the heart and may replace the inferior interventricular artery. Others considered an AIVA on the inferior surface of the heart a rare variant. A long AIVA is a strong predictor of death in acute anterior wall myocardial infarction. We determined coronary artery variance at the inferior surface of the ventricles in 134 dissected human hearts and analyzed a possible association between coronary artery variance and age at death. The AIVA extended to the inferior side in 64.9% of the hearts, but rarely reached the basal half of the inferior interventricular groove. Most frequently (53%), it extended into the apical two-fifths of the length of the inferior ventricular walls. An AIVA extending to the apical 40% of the length of the inferior ventricular walls may therefore be considered a common variant. In 20.1% of the hearts, a right inferior diagonal artery was also found. Statistical analysis neither revealed an association between mean AIVA length at the inferior ventricular surface and type of coronary artery dominance nor an association between AIVA length at the inferior ventricular surface or coronary artery dominance type and age at death

The relation between tau pathology and granulovacuolar degeneration of neurons

Neurofibrillary tangles arising from aggregated microtubule-associated protein tau occur in aged brains and are hallmarks of neurodegenerative diseases. A subset of neurons containing aggregated tau displays granulovacuolar degeneration (GVD) that is characterized by membrane-bound cytoplasmic vacuoles, each containing an electron dense granule (GVB). Tau pathology induces GVBs in experimental models, but GVD does not generally follow tau pathology in the human brain. The entorhinal cortex, DRN, and LC are among the regions that display pathological changes of tau earliest, whereas neurons with GVBs occur first in the hippocampus and have been found in oral raphe nuclei only at the most advanced GVD stage. To date, there is no detailed report about neurons with GVD in aminergic nuclei. We studied the relation between tau pathology and GVD in field CA1 of the hippocampus, entorhinal cortex, dorsal (DRN) and median (MRN) raphe nucleus, and locus coeruleus from elderly subjects with Braak & Braak stages of tau pathology ranging from 0 to VI. Tau pathology and GVBs were visualized by means of immunolabeling and quantified. Percentages of neurons containing GVBs were significantly related to percentages of AT8-positive neurons in the regions examined. GVD and tau pathology were found together in neurons to a different extent in regions of the brain. 53.2% of AT8-immunoreactive neurons in CA1, 19.8% in layer II of the entorhinal cortex, 29.6% in the DRN, and 31.4% in the locus coeruleus contained GVBs. Age-related factors, the percentage of neurons with pretangles in a region of the brain, and the metabolism of a neuron possibly influence the prevalence of neurons with GVBs

Effect of tau-pathology on charged multivesicular body protein 2b (CHMP2B)

Charged multivesicular body protein 2b (CHMP2B) is a subunit of the endosomal sorting complex required for transport (ESCRT)-III that mediates scission of budded membranes. Neurons with CHMP2B-positive granulovacuolar inclusions in the cytoplasm are much more frequent in hippocampi of cases with Alzheimer's disease when compared with controls. We analyzed immunolabeled brain sections from tau-transgenic mice, APP-transgenic mice, non-transgenic mice, and human hippocampi to investigate the relation between CHMP2B and tau and plaque pathology that are major histopathological features of Alzheimer's disease. Neurons undergoing granulovacuolar degeneration (GVD) were found in human hippocampi and old tau-trangenic mice but not in the APP-transgenic strains. 57% of neurons with GVD displayed GVD-granules double-labeled for CHMP2B and the GVD-marker casein kinase 1 delta in 24 months-old tau-transgenic mice and 5.7% of neurons with tau hyperphosphorylated at Thr212 and Ser214 (immunoreactive with antibody AT100) displayed CHMP2B-positive GVD-granules, in human hippocampi it was 100% and 46% respectively. The number of neurons with GVD-inclusions increased in tau-transgenic mice with the number of AT100-positive neurons, suggesting a link between tau-pathology and GVD. GVD-granules in human hippocampi also displayed immunoreactivity for Vps4a, another protein component of ESCRT-III. In cases with aging-related tau astrogliopathy (ARTAG), astrocytes containing hyper-phosphorylated tau immunoreactive with antibody AT8 displayed strong CHMP2B immunoreactivity. The results suggest dysregulation of CHMP2B together with tau-pathology and possibly a disturbance of the regulation of vesicular compartments. The absence of combined A beta- and tau-associated pathology in the transgenic mice may account for the difference in CHMP2B-immunoreactivity between the transgenic mice and human hippocampus

Dental Pulp Inflammation Initiates the Occurrence of Mast Cells Expressing the α₁ and β₁ Subunits of Soluble Guanylyl Cyclase

The binding of nitric oxide (NO) to heme in the β1 subunit of soluble guanylyl cyclase (sGC) activates both the heterodimeric α1β1 and α2β1 isoforms of the enzyme, leading to the increased production of cGMP from GTP. In cultured human mast cells, exogenous NO is able to inhibit mast cell degranulation via NO-cGMP signaling. However, under inflammatory oxidative or nitrosative stress, sGC becomes insensitive to NO. The occurrence of mast cells in healthy and inflamed human tissues and the in vivo expression of the α1 and β1 subunits of sGC in human mast cells during inflammation remain largely unresolved and were investigated here. Using peroxidase and double immunohistochemical incubations, no mast cells were found in healthy dental pulp, whereas the inflammation of dental pulp initiated the occurrence of several mast cells expressing the α1 and β1 subunits of sGC. Since inflammation-induced oxidative and nitrosative stress oxidizes Fe2+ to Fe3+ in the β1 subunit of sGC, leading to the desensitization of sGC to NO, we hypothesize that the NO- and heme-independent pharmacological activation of sGC in mast cells may be considered as a regulatory strategy for mast cell functions in inflamed human dental pulp

Automated PD-L1 Scoring Using Artificial Intelligence in Head and Neck Squamous Cell Carcinoma

Immune checkpoint inhibitors (ICI) represent a new therapeutic approach in recurrent and metastatic head and neck squamous cell carcinoma (HNSCC). The patient selection for the PD-1/PD-L1 inhibitor therapy is based on the degree of PD-L1 expression in immunohistochemistry reflected by manually determined PD-L1 scores. However, manual scoring shows variability between different investigators and is influenced by cognitive and visual traps and could therefore negatively influence treatment decisions. Automated PD-L1 scoring could facilitate reliable and reproducible results. Our novel approach uses three neural networks sequentially applied for fully automated PD-L1 scoring of all three established PD-L1 scores: tumor proportion score (TPS), combined positive score (CPS) and tumor-infiltrating immune cell score (ICS). Our approach was validated using WSIs of HNSCC cases and compared with manual PD-L1 scoring by human investigators. The inter-rater correlation (ICC) between human and machine was very similar to the human-human correlation. The ICC was slightly higher between human-machine compared to human-human for the CPS and ICS, but a slightly lower for the TPS. Our study provides deeper insights into automated PD-L1 scoring by neural networks and its limitations. This may serve as a basis to improve ICI patient selection in the future

Inflammation in the human periodontium induces downregulation of the α1_1- and β1_1-subunits of the sGC in cementoclasts

Nitric oxide (NO) binds to soluble guanylyl cyclase (sGC), activates it in a reduced oxidized heme iron state, and generates cyclic Guanosine Monophosphate (cGMP), which results in vasodilatation and inhibition of osteoclast activity. In inflammation, sGC is oxidized and becomes insensitive to NO. NO- and heme-independent activation of sGC requires protein expression of the α$_1$- and β$_1$-subunits. Inflammation of the periodontium induces the resorption of cementum by cementoclasts and the resorption of the alveolar bone by osteoclasts, which can lead to tooth loss. As the presence of sGC in cementoclasts is unknown, we investigated the α$_1$- and β$_1$-subunits of sGC in cementoclasts of healthy and inflamed human periodontium using double immunostaining for CD68 and cathepsin K and compared the findings with those of osteoclasts from the same sections. In comparison to cementoclasts in the healthy periodontium, cementoclasts under inflammatory conditions showed a decreased staining intensity for both α$_1$- and β$_1$-subunits of sGC, indicating reduced protein expression of these subunits. Therefore, pharmacological activation of sGC in inflamed periodontal tissues in an NO- and heme-independent manner could be considered as a new treatment strategy to inhibit cementum resorption