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oncology Oncology

Next Generation Radiotheranostics Promoting Precision Medicine.

In Annals of oncology : official journal of the European Society for Medical Oncology

Radiotheranostics is a field of rapid growth with some approved treatments including 131I for thyroid cancer, 223Ra for osseous metastases, 177Lu-Dotatate for neuroendocrine tumors, and 177Lu-PSMA for prostate cancer, and several more under investigation. In this review, we will cover the fundamentals of radiotheranostics, the key clinical studies that have led to current success, future developments with new targets, radionuclides and platforms, challenges with logistics and reimbursement and, lastly, forthcoming considerations regarding dosimetry, identifying the right line of therapy, artificial intelligence and more.

Pomykala K L, Hadaschik B A, Sartor O, Gillessen S, Sweeney C J, Maughan T, Hofman M S, Herrmann K

2023-Mar-14

(177)Lu-Dotatate, (177)Lu-PSMA, endoradiotherapy, positron emission tomography, radiotheranostics, targeted radioligand therapy

Radiology Radiology

Osteoarthritis Year in Review 2022: Imaging.

In Osteoarthritis and cartilage ; h5-index 62.0

PURPOSE : This narrative review summarizes original research focusing on imaging in osteoarthritis (OA) published between April 1st 2021 and March 31st 2022. We only considered English publications that were in vivo human studies.

METHODS : The PubMed, Medline, Embase, Scopus, and ISI Web of Science databases were searched for "Osteoarthritis/OA" studies based on the search terms: "Radiography", "Ultrasound/US", "Computed Tomography/CT", "DXA", "Magnetic Resonance Imaging/MRI", "Artificial Intelligence/AI", and "Deep Learning". This review highlights the anatomical focus of research on the structures within the tibiofemoral, patellofemoral, hip, and hand joints. There is also a noted focus on artificial intelligence applications in OA imaging.

RESULTS : Over the last decade, the increasing trend of using open-access large databases has reached a plateau (from 17 to 37). Compositional MRI has had the most prominent use in OA imaging and its biomarkers have been used in the detection of preclinical OA and prediction of OA outcomes. Most noteworthy, there has been an accelerated rate of publications on the implications of artificial intelligence, used in developing prediction models and performing trabecular texture analysis, in OA imaging (from 17 to 154).

CONCLUSIONS : While imaging has maintained its key role in OA research, publication trends have shown an emphasis on the integration of AI. During the past year, MRI has maintained the highest prevalence in usage while US and CT remain as readily available modalities. Finally, there has been a notable uptake in the development and validation of AI techniques used to perform texture analysis and predict OA progression.

Demehri Shadpour, Kasaeian Arta, Roemer Frank W, Guermazi Ali

2023-Mar-14

Artificial intelligence, Imaging, Osteoarthritis, Review

Public Health Public Health

An automatic entropy method to efficiently mask histology whole-slide images.

In Scientific reports ; h5-index 158.0

Tissue segmentation of histology whole-slide images (WSI) remains a critical task in automated digital pathology workflows for both accurate disease diagnosis and deep phenotyping for research purposes. This is especially challenging when the tissue structure of biospecimens is relatively porous and heterogeneous, such as for atherosclerotic plaques. In this study, we developed a unique approach called 'EntropyMasker' based on image entropy to tackle the fore- and background segmentation (masking) task in histology WSI. We evaluated our method on 97 high-resolution WSI of human carotid atherosclerotic plaques in the Athero-Express Biobank Study, constituting hematoxylin and eosin and 8 other staining types. Using multiple benchmarking metrics, we compared our method with four widely used segmentation methods: Otsu's method, Adaptive mean, Adaptive Gaussian and slideMask and observed that our method had the highest sensitivity and Jaccard similarity index. We envision EntropyMasker to fill an important gap in WSI preprocessing, machine learning image analysis pipelines, and enable disease phenotyping beyond the field of atherosclerosis.

Song Yipei, Cisternino Francesco, Mekke Joost M, de Borst Gert J, de Kleijn Dominique P V, Pasterkamp Gerard, Vink Aryan, Glastonbury Craig A, van der Laan Sander W, Miller Clint L

2023-Mar-15

General General

Weibo users and Academia's foci on tourism safety: Implications from institutional differences and digital divide.

In Heliyon

Tourism safety is essential for tourists and tourism practitioners. This study conducted a bibliometric analysis using VOSviewer and CiteSpace for 2018 articles indexed on the Web of Science (WoS). It also analysed 7293 Weibo posts between 1977 and 2022 using Python, MYSQL, AI sentiment, and Tableau. The first tourism safety publication on WoS appeared in 1977, while the first Weibo microblog dated was dated back to 2011. Compared to the information posted on Weibo, the annual publications about tourism safety on WoS recorded a stable increment. On Web of Science (WoS), the academic staff and universities produced the largest number of tourism safety posts. On the flip side, the most productive organisations on Weibo are government agencies in popular tourism destinations. "Accident", "medical tourism", "environment", "mediating role", and "hospitality" were important burst nodes in tourism safety on WoS. "Quality", "accident", and health-related words were the foci on both Weibo and WoS. On Web of Science, the top 10 most popular keywords of tourism safety-related articles could be classified into two groups: health ("Covid-19", "restoration", "pandemics", "Sars-Cov-2", "Sars", "mental health") and IT terminologies ("big data", "artificial intelligence"). It has been concluded that "artificial intelligence (AI)" is more likely to be included in the keywords on tourism researched by academia. In contrast, the public may not know about or use AI in the tourism industry. Besides, the top 10 most popular keywords on Weibo related to tourism risks and hazards were drowning and traffic risks and hazards, such as drowning and traffic risks. The digital divide may explain such a difference: the academic circle benefits more from the digital age than laypersons. It may also be the result of institutional differences and information asymmetry.

Zeng Liyun, Li Rita Yi Man, Zeng Huiling

2023-Mar

Artificial intelligence, Bibliometrics, Comparative analysis, Digital divide, Information asymmetry, Tourism safety, Web of science, Weibo

General General

Progressive Content-aware Coded Hyperspectral Compressive Imaging

ArXiv Preprint

Hyperspectral imaging plays a pivotal role in a wide range of applications, like remote sensing, medicine, and cytology. By acquiring 3D hyperspectral images (HSIs) via 2D sensors, the coded aperture snapshot spectral imaging (CASSI) has achieved great success due to its hardware-friendly implementation and fast imaging speed. However, for some less spectrally sparse scenes, single snapshot and unreasonable coded aperture design tend to make HSI recovery more ill-posed and yield poor spatial and spectral fidelity. In this paper, we propose a novel Progressive Content-Aware CASSI framework, dubbed PCA-CASSI, which captures HSIs with multiple optimized content-aware coded apertures and fuses all the snapshots for reconstruction progressively. Simultaneously, by mapping the Range-Null space Decomposition (RND) into a deep network with several phases, an RND-HRNet is proposed for HSI recovery. Each recovery phase can fully exploit the hidden physical information in the coded apertures via explicit $\mathcal{R}$$-$$\mathcal{N}$ decomposition and explore the spatial-spectral correlation by dual transformer blocks. Our method is validated to surpass other state-of-the-art methods on both multiple- and single-shot HSI imaging tasks by large margins.

Xuanyu Zhang, Bin Chen, Wenzhen Zou, Shuai Liu, Yongbing Zhang, Ruiqin Xiong, Jian Zhang

2023-03-17

General General

ChatGPT(Generative Pre-trained Transformer): Why we should embrace this technology.

In American journal of obstetrics and gynecology

With the advent of artificial intelligence (AI) that not only learns from us, but can communicate with us in plain language, humans are embarking on a brave new future. The interaction between humans and AI has never been so widespread. ChatGPT (Generative Pre-trained Transformer) is an AI resource that has potential uses in the practice of medicine. As clinicians, we have the opportunity to help guide and develop new ways to utilize this powerful tool. Optimal use of any tool requires a certain level of comfort. This is best achieved by appreciating its power and its limitations. Being part of the process is crucial in maximizing its utility for our field. This clinical opinion demonstrates the potential uses of ChatGPT for obstetrician-gynecologists and encourages readers to serve as the driving force behind this resource.

Chavez Martin R, Butler Thomas S, Rekawek Patricia, Heo Hye, Kinzler Wendy L

2023-Mar-14

ChatGPT, Generative Pre-trained Transformer, OpenAI, artificial intelligence, future of medicine, large language models, plain conversational language interfaces