Radioactive iodine therapy requires individualized decisions regarding patient selection, administered activity planning, imaging assessment, and follow-up. This systematic review summarizes current applications of artificial intelligence (AI) in the [131]I treatment pathway and evaluates barriers limiting clinical implementation. Following PRISMA 2020 guidelines, PubMed, Scopus, Web of Science, and Wiley databases were searched for original studies involving human patients treated with [131]I for differentiated thyroid cancer or benign thyroid disease, where AI, deep learning (DL), or machine learning (ML) methods were utilized. Evidence was synthesized, and study quality was assessed using the NIH/NHLBI Study Quality Assessment Tool. Among 775 identified records, 24 studies met inclusion criteria. AI applications included pretreatment decision support, detection and characterization of iodine-avid disease, dosimetry and activity optimization, radiation-safety assessment, treatment response prediction, levothyroxine dose estimation, and recurrence-risk stratification. The available evidence was dominated by retrospective, single-center studies, primarily focused on differentiated thyroid cancer, with limited external validation. AI has the potential to improve standardization and personalization of [131]I therapy, but heterogeneous methodologies and insufficient evidence of clinical utility currently restrict routine adoption. Prospective multicenter studies with harmonized endpoints and robust validation are required to facilitate clinical translation.

Following the Fukushima Daiichi Nuclear Power Plant accident in 2011, Japan implemented extensive monitoring of radioactive materials in foods and established strict regulatory limits based on an annual effective dose of 1 mSv/year from artificial radionuclides. This review summarizes long-term surveillance data on radioactive cesium (r-Cs) in commercial foods and long-term assessments of dietary intake of r-Cs and strontium-90 ([90]Sr) using the total diet study (TDS)/market basket (MB) method. Monitoring of commercial foods demonstrated that pre-shipment inspections and production controls are highly effective for cultivated agricultural products and livestock products, with regulatory exceedances occurring almost exclusively in wild mushrooms, wild edible plants, and wildlife-derived foods. No r-Cs has been detected in any infant food sample since monitoring began. TDS-based assessments show that the committed effective dose from r-Cs declined rapidly during the first few years after the accident and has remained at a very low level (generally below 0.001 mSv/year) nationwide since around 2017, while [90]Sr levels exhibited no clear regional differences and remained comparable to pre-accident background levels. These findings confirm that Japan's long-term food safety controls have kept internal radiation exposure far below international safety limits. The integration of surveillance, TDS monitoring, and risk management provides a robust evidence-based model for ensuring food safety following nuclear events.

The [177]Lu complexes, [177]Lu-DOTATATE and [177]Lu-PSMA-617, have recently been approved by the FDA to treat neuroendocrine tumors and metastatic prostate cancer, respectively. In this chapter, we systematically introduce the classification of radioactive particles and the coordination chemistry and structure-activity relationship of the type complex. In addition, we discuss the challenges encountered in the development of nuclear medicines and propose that artificial intelligence provides new ideas for the design and development of new boron drugs.

High-salinity radioactive wastewater is challenging to treat because it contains radionuclides together with abundant coexisting ions. Solar-driven interfacial evaporation (SDIE) offers a low-energy method for radioactive wastewater treatment, but salt accumulation remains a key limitation. Herein, an electrospun MXene-based Janus membrane (PMPJ) was developed by integrating a hydrophobic PVDF/MXene photothermal layer with a hydrophilic PAN water-transport layer. Regulating the thickness ratio of the hydrophilic to hydrophobic layers of the Janus membrane reveals that appropriate adjustment of the bilayer ratio balances water delivery, heat localization, vapor escape, and suppresses salt accumulation. The optimized PMPJ-7 membrane exhibited strong light absorbance of 91.78%, asymmetric wettability, and structural stability. A relatively thin hydrophobic layer optimized the balance between heat generation, water transport, and vapor escape within the membrane, while a two-dimensional water transport structure improved water supply and heat localization at the evaporator level. Under 1 sun irradiation, PMPJ-7 exhibited an evaporation rate of 1.84 kg m[-2]·h[-1] and a photothermal conversion efficiency of 96.5%. When treating high-salinity simulated radioactive wastewater (HSCW), PMPJ-7 significantly reduced radionuclide concentrations in the condensate, achieving decontamination factors of 10[5.82], 10[5.09], 10[5.58], and 10[4.11] for Co[2+], Sr[2+], Cs[+], and I[-], respectively, with removal efficiencies exceeding 99.99% for all target ions. More importantly, the Janus membrane maintained stable cyclic evaporation by separating water supply from photothermal evaporation and vapor release under high salinity. This work provides a Janus membrane design strategy for stable SDIE and solar-assisted treatment of simulated radioactive wastewater.

The clinical management of biliary obstruction has long relied on mechanical drainage provided by stents, yet the inherent risks of re-occlusion, infection, and migration underscore the fundamental limitations of this passive support paradigm. This review proposes a four-stage paradigm evolution framework for biliary stent technology, demonstrating a shift from "passive physical support" to an "active therapeutic platform." The first stage, represented by plastic and self-expandable metallic stents, established anatomical drainage but is limited by biofilm deposition, tumor ingrowth, and migration. The first paradigm shift introduced functionalized stents incorporating drug-eluting, radionuclide, or photothermal/photodynamic coatings, transforming stents into active therapeutic carriers. The second paradigm shift emphasizes bio-adaptation through fully biodegradable stents achieving "temporary support followed by disappearance," alongside cell/matrix coatings to promote tissue regeneration. A third paradigm shift is emerging, focusing on intelligent responsiveness and personalization through closed-loop systems integrating biosensors, wireless communication, and artificial intelligence for real-time monitoring and on-demand therapy, combined with 3D/4D printing for patient-specific adaptation. Through critical assessment of each stage, this review dissects translational challenges including evaluation standards, long-term safety, cost-effectiveness, and regulatory complexities. Ultimately, we present a clinical decision-oriented technological spectrum delineating stent positioning across benign and malignant biliary diseases, envisioning future dynamic platforms integrating diagnosis, treatment, and monitoring to advance biliary intervention into an era of data-driven precision therapy. STATEMENT OF SIGNIFICANCE: This review establishes, for the first time, a four-stage paradigm evolution framework for biliary stent technology-from passive mechanical support to active functionalized intervention, bio-adaptive scaffolds, and ultimately intelligent diagnostic-therapeutic platforms. By systematically dissecting the irreconcilable contradictions inherent to each paradigm, this framework provides a design-philosophy navigational map that transcends conventional chronological classifications. The integration of materials science mechanisms, cross-technology quantitative comparisons, and evidence-based clinical decision pathways offers both clinicians and biomaterials researchers a comprehensive reference for understanding the past trajectory and future direction of biliary stenting.

The incidence of thyroid cancer has increased dramatically over the past four decades, making it the most common endocrine malignancy worldwide. Although well-differentiated thyroid carcinomas generally exhibit excellent survival rates following standard surgical and radioactive iodine interventions, the clinical management of high-risk variants, recurrent disease, and indeterminate nodules remains a significant challenge. Historically, the evaluation of thyroid nodules has relied on B-mode ultrasonography and fine-needle aspiration biopsy (FNAB). However, spatial and temporal tumor heterogeneity, coupled with the high rate of indeterminate cytology (Bethesda Categories III and IV), often leads to unnecessary diagnostic thyroidectomies. In recent years, liquid biopsy has emerged as a promising diagnostic approach, offering a non-invasive, dynamic, and comprehensive method for disease monitoring. This comprehensive review evaluates the biological mechanisms and clinical utility of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), and non-coding RNAs in thyroid oncology. Furthermore, it explores the clinical role of commercial molecular diagnostic panels (e.g., Afirma GSC, ThyroSeq v3) in guiding surgical decisions. This review highlights the diagnostic synergy achieved when these molecular biomarkers are integrated with advanced radiological modalities - including strain elastography, quantitative region-of-interest (ROI) analysis, ACR TI-RADS, and cross-sectional volumetric tracking - as well as nuclear medicine techniques like technetium-99m MIBI scintigraphy. Emerging applications of artificial intelligence and radiomics in image analysis, alongside the concept of minimal residual disease monitoring, are also discussed. Ultimately, we emphasize the need for a multidisciplinary team (MDT) approach in translating these multi-omics and multimodal imaging data into precision medicine, while acknowledging current limitations and charting future directions.

In recent decades, the global incidence of thyroid cancer has risen sharply mainly due to the high detection rate of papillary thyroid microcarcinoma and overdiagnosis, with its overall mortality staying steady. Classic pathogenic drivers encompass childhood radiation exposure, iodine disorder, and hallmark gene alterations including BRAF V600E, RET/PTC, RAS and PAX8/PPARγ. Modern multimodal diagnostic systems integrating artificial intelligence-assisted high-resolution ultrasound, Thyroseq-V2, Afirma, circulating tumor DNA detection and refined pathological examination achieve precise preoperative stratification. Aberrant activation of MAPK/ERK, PI3K/AKT and Wnt/β-catenin cascades, coupled with an immune-suppressive tumor microenvironment dominated by M2-type tumor-associated macrophages, regulatory T cells and PD-L1 overexpression, drives thyroid cancer progression and dedifferentiation. Current comprehensive integrated therapeutic strategies cover robotic surgery, radioactive iodine ablation, external radiotherapy, molecular targeted drugs (sorafenib, lenvatinib, vemurafenib combined with trametinib) and novel immunotherapy. Traditional Chinese Medicine (TCM), based on the TCM pathogenesis of liver qi stagnation, phlegm-blood stasis and qi-blood deficiency for goiter, serves as an adjuvant therapy for thyroid cancer. Active ingredients such as honokiol, artesunate, ginsenoside Rg3, astragalus polysaccharide and curcumin can suppress tumor proliferation, reshape anti-tumor immunity and inhibit metastasis via regulating reactive oxygen species, PI3K/AKT pathway, epithelial-mesenchymal transition and matrix metalloproteinases. Existing clinical observations confirm that TCM can relieve clinical discomfort, improve life quality and lower recurrence risk when combined with conventional radioiodine or anti-tumor treatment. However, the clinical application of TCM for thyroid cancer is greatly restricted by insufficient syndrome differentiation standardization, low-quality clinical evidence and unclear herbal safety risks. Most available studies are small-sample retrospective analyses lacking large-scale, multicenter randomized controlled trials to verify efficacy and safety. Future research should focus on standardized clinical trial design, in-depth pharmacological mechanism exploration, and construction of standardized thyroid cancer integrative diagnosis and treatment regimens combining Western precision therapy and TCM adjuvant intervention, to clarify the definite positioning of TCM in whole-course thyroid cancer management.

Environmental radioactivity in Qatar arises from a combination of naturally occurring radionuclides (NORM) and technically enhanced NORM (TENORM) associated with industrial activities. This study presents a comprehensive systematic review with quantitative synthesis of radionuclide concentrations across multiple environmental matrices, including soil, sediment, groundwater, seawater, building materials, and marine biota, extracted from research papers published between 1980 and September 2025. Data synthesis reveals those natural radionuclides such as [226]Ra, [238]U, [232]Th, and [40]K exhibit moderate spatial variability, influenced primarily by lithology, soil texture, and arid climatic conditions. In contrast, artificial radionuclides ([137]Cs, [90]Sr) are detected at trace levels, consistent with global fallout. Radiological risk assessment using indices such as radium equivalent activity, absorbed dose rate, annual effective dose, gonadal dose equivalent, and hazard indices indicates minimal risk for most soils, sediments, and conventional building materials. However, elevated activity concentrations and associated risk metrices are observed in industrial by-products, oil-field residues, and waste materials highlighting localized hazards. Key sources include geological formations, dust storms, hydrocarbon extraction, construction materials, and minor transboundary inputs. Despite the overall low exposure, continuous monitoring, strict management of industrial residues, and regional cooperation are recommended to mitigate potential health and environmental risks. This systematic review with quantitative synthesis provides a robust baseline for future environmental radioactivity research and policy development in arid regions.

Surrogate materials enable pre-treatment prediction of intra-hepatic distribution of therapeutic radioactive microsphere, facilitating patient-specific dosimetry for transarterial radioembolization (TARE). Technetium-99m macroaggregated albumin ([99]ᵐTc-MAA) has long constituted the clinical standard for SPECT-based surrogates, however, its fundamental physicochemical difference from therapeutic microspheres limits the reliability of MAA-based dosimetry and prediction for personalized treatment planning. Next-generation surrogate technology includes biodegradable polymeric microspheres engineered to closely replicate the therapeutic microsphere while affording post-procedural arterial recanalization through controlled biodegradation. Theranostic microspheres incorporating diverse radionuclides, positron-emitting PET compatible surrogates, and multimodal CT and MRI-visible surrogates have collectively expanded same-particle pre-treatment dosimetry capabilities. These material-level advances are synergistically coupled with computational dosimetry tools including artificial intelligence/deep learning algorithms for automated segmentation/dose-prediction, and Monte Carlo simulations that enhance voxel-based dosimetry precision. This review examines recent advances in surrogate materials design and integrated imaging/dosimetry methodologies that enhance TARE efficacy, safety, and personalized treatment outcomes.

Magnetic Particle Imaging (MPI) is an emerging tracer-based imaging modality that enables real-time, quantitative visualization with zero tissue background, high sensitivity, and depth-independent signal detection. Unlike conventional imaging methods that rely on intrinsic tissue contrast or radioactive decay, MPI image formation is governed by the nonlinear magnetization dynamics of superparamagnetic iron oxide nanoparticles, making imaging performance fundamentally dependent on nanoparticle properties and magnetic field generation. This review presents a system- and materials-oriented overview of MPI. We first summarize the physical principles of MPI, including nonlinear magnetization, relaxation dynamics, and field-free-region-based spatial encoding. We then review representative MPI system architectures, ranging from closed-bore preclinical scanners to open, single-sided, hand-held, and hybrid platforms, and discuss how scaling, power consumption, and accessibility influence system performance in preclinical and human-scale settings. We further highlight rational tracer engineering using a "Core-Shell-Function" framework, emphasizing how magnetic core design, surface modification, and functionalization together determine signal generation, in vivo behavior, and imaging performance. Finally, we summarize key biomedical applications, including cell tracking, angiography, tumor imaging, and intraoperative guidance, and discuss remaining challenges for clinical translation. This review provides an integrated framework for advancing MPI toward functional imaging and precision medicine.