Automation: A revolutionary vision of artificial intelligence in theranostics.

The last two decades have witnessed an extraordinary evolution of automation and artificial intelligence (AI), which has become an integral part of our daily lives. Lately, AI has also been assimilated in the field of medicine to upgrade overall healthcare system and encourage personalized treatment. Theranostics literally meaning combination of diagnosis and therapeutics, is a targeted pharmacotherapy, based on specific targeted diagnostic tests. Numerous theranostic agents/biomarkers are available which can identify the most beneficial treatment, correct dose or predict response to a medicine, thus, maximizing drug efficacy, minimizing toxicity and providing informed treatment choice. For instance, a statistics based Cluster-FLIM technology provides precise data on drug-receptor binding behavior in biological tissues using fluorescence real experimental imaging. Automated Idylla™ qPCR System is another approach in oncology to determine the EGFR mutations at initial stage as well as during the treatment and also assists the oncologist in designing the treatment protocol. Recent incorporation of automation and AI in theranostics has brought a drastic change in early detection and treatment protocols for various diseases such as cancer and diabetes. Also, it leads to quick analysis of number of diverse experimental datum with accuracy. The approach mainly uses computer algorithms to unveil relevant and significant information from clinical data, thereby assisting in making accurate, logical and pertinent decisions. This review highlights the emerging uses/role of automation and AI in theranostics, technical difficulties and focuses on its future prospects to facilitate a patient specific, reliable and efficient pharmacotherapy.

Gulsheen P ，Batra S ，Sharma S 《-》

Theranostics and artificial intelligence: new frontiers in personalized medicine.

The field of theranostics is rapidly advancing, driven by the goals of enhancing patient care. Recent breakthroughs in artificial intelligence (AI) and its innovative theranostic applications have marked a critical step forward in nuclear medicine, leading to a significant paradigm shift in precision oncology. For instance, AI-assisted tumor characterization, including automated image interpretation, tumor segmentation, feature identification, and prediction of high-risk lesions, improves diagnostic processes, offering a precise and detailed evaluation. With a comprehensive assessment tailored to an individual's unique clinical profile, AI algorithms promise to enhance patient risk classification, thereby benefiting the alignment of patient needs with the most appropriate treatment plans. By uncovering potential factors unseeable to the human eye, such as intrinsic variations in tumor radiosensitivity or molecular profile, AI software has the potential to revolutionize the prediction of response heterogeneity. For accurate and efficient dosimetry calculations, AI technology offers significant advantages by providing customized phantoms and streamlining complex mathematical algorithms, making personalized dosimetry feasible and accessible in busy clinical settings. AI tools have the potential to be leveraged to predict and mitigate treatment-related adverse events, allowing early interventions. Additionally, generative AI can be utilized to find new targets for developing novel radiopharmaceuticals and facilitate drug discovery. However, while there is immense potential and notable interest in the role of AI in theranostics, these technologies do not lack limitations and challenges. There remains still much to be explored and understood. In this study, we investigate the current applications of AI in theranostics and seek to broaden the horizons for future research and innovation.

Belge Bilgin G ，Bilgin C ，Burkett BJ ，Orme JJ ，Childs DS ，Thorpe MP ，Halfdanarson TR ，Johnson GB ，Kendi AT ，Sartor O ... -  《Theranostics》

Artificial intelligence-aided optical imaging for cancer theranostics.

The use of artificial intelligence (AI) to assist biomedical imaging have demonstrated its high accuracy and high efficiency in medical decision-making for individualized cancer medicine. In particular, optical imaging methods are able to visualize both the structural and functional information of tumors tissues with high contrast, low cost, and noninvasive property. However, no systematic work has been performed to inspect the recent advances on AI-aided optical imaging for cancer theranostics. In this review, we demonstrated how AI can guide optical imaging methods to improve the accuracy on tumor detection, automated analysis and prediction of its histopathological section, its monitoring during treatment, and its prognosis by using computer vision, deep learning and natural language processing. By contrast, the optical imaging techniques involved mainly consisted of various tomography and microscopy imaging methods such as optical endoscopy imaging, optical coherence tomography, photoacoustic imaging, diffuse optical tomography, optical microscopy imaging, Raman imaging, and fluorescent imaging. Meanwhile, existing problems, possible challenges and future prospects for AI-aided optical imaging protocol for cancer theranostics were also discussed. It is expected that the present work can open a new avenue for precision oncology by using AI and optical imaging tools.

Xu M ，Chen Z ，Zheng J ，Zhao Q ，Yuan Z ... -  《-》

Theranostics - a sure cure for cancer after 100 years?

Cancer has remained a formidable challenge in medicine and has claimed an enormous number of lives worldwide. Theranostics, combining diagnostic methods with personalized therapeutic approaches, shows huge potential to advance the battle against cancer. This review aims to provide an overview of theranostics in oncology: exploring its history, current advances, challenges, and prospects. We present the fundamental evolution of theranostics from radiotherapeutics, cellular therapeutics, and nanotherapeutics, showcasing critical milestones in the last decade. From the early concept of targeted drug delivery to the emergence of personalized medicine, theranostics has benefited from advances in imaging technologies, molecular biology, and nanomedicine. Furthermore, we emphasize pertinent illustrations showcasing that revolutionary strategies in cancer management enhance diagnostic accuracy and provide targeted therapies customized for individual patients, thereby facilitating the implementation of personalized medicine. Finally, we describe future perspectives on current challenges, emerging topics, and advances in the field.

Song Y ，Zou J ，Castellanos EA ，Matsuura N ，Ronald JA ，Shuhendler A ，Weber WA ，Gilad AA ，Müller C ，Witney TH ，Chen X ... -  《Theranostics》

[Artificial intelligence and its applications in medicine I: introductory background to AI and robotics].

Technology and medicine follow a parallel path during the last decades. Technological advances are changing the concept of health and health needs are influencing the development of technology. Artificial intelligence (AI) is made up of a series of sufficiently trained logical algorithms from which machines are capable of making decisions for specific cases based on general rules. This technology has applications in the diagnosis and follow-up of patients with an individualized prognostic evaluation of them. Furthermore, if we combine this technology with robotics, we can create intelligent machines that make more efficient diagnostic proposals in their work. Therefore, AI is going to be a technology present in our daily work through machines or computer programs, which in a more or less transparent way for the user, will become a daily reality in health processes. Health professionals have to know this technology, its advantages and disadvantages, because it will be an integral part of our work. In these two articles we intend to give a basic vision of this technology adapted to doctors with a review of its history and evolution, its real applications at the present time and a vision of a future in which AI and Big Data will shape the personalized medicine that will characterize the 21st century.

Avila-Tomás JF ，Mayer-Pujadas MA ，Quesada-Varela VJ 《-》