FLASH radiotherapy (RT) is a novel technique in which the ultrahigh dose rate (UHDR) (≥40 Gy/s) is delivered to the entire treatment volume. Recent outcomes of in vivo studies show that the UHDR RT has the potential to spare normal tissue without sacrificing tumor control. There is a growing interest in the application of FLASH RT, and the ultrahigh dose irradiation delivery has been achieved by a few experimental and modified linear accelerators. The underlying mechanism of FLASH effect is yet to be fully understood, but the oxygen depletion in normal tissue providing extra protection during FLASH irradiation is a hypothesis that attracts most attention currently. Monte Carlo simulation is playing an important role in FLASH, enabling the understanding of its dosimetry calculations and hardware design. More advanced Monte Carlo simulation tools are under development to fulfill the challenge of reproducing the radiolysis and radiobiology processes in FLASH irradiation. FLASH RT may become one of standard treatment modalities for tumor treatment in the future. This paper presents the history and status of FLASH RT studies with a focus on FLASH irradiation delivery modalities, underlying mechanism of FLASH effect, in vivo and vitro experiments, and simulation studies. Existing challenges and prospects of this novel technique are discussed in this manuscript.

Ultrasound imaging of the lung has played an important role in managing patients with COVID-19–associated pneumonia and acute respiratory distress syndrome (ARDS). During the COVID-19 pandemic, lung ultrasound (LUS) or point-of-care ultrasound (POCUS) has been a popular diagnostic tool due to its unique imaging capability and logistical advantages over chest X-ray and CT. Pneumonia/ARDS is associated with the sonographic appearances of pleural line irregularities and B-line artefacts, which are caused by interstitial thickening and inflammation, and increase in number with severity. Artificial intelligence (AI), particularly machine learning, is increasingly used as a critical tool that assists clinicians in LUS image reading and COVID-19 decision making. We conducted a systematic review from academic databases (PubMed and Google Scholar) and preprints on arXiv or TechRxiv of the state-of-the-art machine learning technologies for LUS images in COVID-19 diagnosis. Openly accessible LUS datasets are listed. Various machine learning architectures have been employed to evaluate LUS and showed high performance. This paper will summarize the current development of AI for COVID-19 management and the outlook for emerging trends of combining AI-based LUS with robotics, telehealth, and other techniques.

Many cancers result in metastasis in the spinal vertebrae, which can cause pain, neurological disability, and reduce quality of life [1,2]. To improve the local disease control and relieve symptoms...

Objectives: The purpose of this study is to investigate the dosimetric effect and clinical impact of delivering a focal radiotherapy boost dose to multiparametric MRI (mp-MRI)-defined dominant intraprostatic lesions (DILs) in prostate cancer using proton therapy. Methods: We retrospectively investigated 36 patients with pre-treatment mp-MRI and CT images who were treated using pencil beam scanning (PBS) proton radiation therapy to the whole prostate. DILs were contoured on co-registered mp-MRIs. Simultaneous integrated boost (SIB) plans using intensity-modulated proton therapy (IMPT) were created based on conventional whole-prostate-irradiation for each patient and optimized with additional DIL coverage goals and urethral constraints. DIL dose coverage and organ-at-risk (OAR) sparing were compared between conventional and SIB plans. Tumor control probability (TCP) and normal tissue complication probability (NTCP) were estimated to evaluate the clinical impact of the SIB plans. Results: Optimized SIB plans significantly escalated the dose to DILs while meeting OAR constraints. SIB plans were able to achieve 125, 150 and 175% of prescription dose coverage in 74, 54 and 17% of 36 patients, respectively. This was modeled to result in an increase in DIL TCP by 7.3–13.3% depending on α/β and DIL risk level. Conclusion: The proposed mp-MRI-guided DIL boost using proton radiation therapy is feasible without violating OAR constraints and demonstrates a potential clinical benefit by improving DIL TCP. This retrospective study suggested the use of IMPT-based DIL SIB may represent a strategy to improve tumor control. Advances in knowledge: This study investigated the planning of mp-MRI-guided DIL boost in prostate proton radiation therapy and estimated its clinical impact with respect to TCP and NTCP.