Novel and developing artificial intelligence (AI) systems can be integrated into healthcare settings in numerous ways. For example, in the case of automated image classification and natural language ...processing, AI systems are beginning to demonstrate near expert level performance in detecting abnormalities such as seizure activity. This paper, however, focuses on AI integration into clinical trials. During the clinical trial recruitment process, considerable labor and time is spent sifting through electronic health record and interviewing patients. With the advancement of deep learning techniques such as natural language processing, intricate electronic health record data can be efficiently processed. This provides utility to workflows such as recruitment for clinical trials. Studies are starting to show promise in shortening the time to recruitment and reducing workload for those involved in clinical trial design. Additionally, numerous guidelines are being constructed to encourage integration of AI into the healthcare setting with meaningful impact. The goal would be to improve the clinical trial process by reducing bias in patient composition, improving retention of participants, and lowering costs and labor.
There have been many applications and influences of Artificial intelligence (AI) in many sectors and its professionals, that of radiotherapy and the medical physicist is no different. AI and ...technological advances have necessitated changing roles of medical physicists due to the development of modernized technology with image-guided accessories for the radiotherapy treatment of cancer patients. Given the changing role of medical physicists in ensuring patient safety and optimal care, AI can reshape radiotherapy practice now and in some years to come. Medical physicists’ roles in radiotherapy practice have evolved to meet technology for the management of better patient care in the age of modern radiotherapy. This short review provides an insight into the influence of AI on the changing role of medical physicists in each specific chain of the workflow in radiotherapy in which they are involved.
Objective
To evaluate patient characteristics, risk factors, disease course, and management of cervical vertebral osteomyelitis in patients who had radiation for head and neck cancers.
Methods
A ...retrospective cohort study (case series) of patients diagnosed with post-radiation osteomyelitis of the cervical spine between 2012 and 2021. Data were collected from the patient’s medical files.
Results
Seven patients (71% male) with post-radiation cervical osteomyelitis were reviewed. The median patient age was 64 years. The mean interval between diagnosis of osteomyelitis and the first and last radiotherapy course was 8.3 and 4.0 years, respectively. A medical or surgical event preceded the diagnosis in four patients (57%) by a mean of 46.25 days. Common imaging findings were free air within the cervical structures and fluid collection. Four patients recovered from osteomyelitis during the follow-up within an average of 65 days.
Conclusion:
Post-radiation osteomyelitis is characterized by a subtle presentation, challenging diagnosis, prolonged treatment, and poor outcome. Clinicians should maintain a high index of suspicion for the long-term after radiotherapy. Multidisciplinary evaluation and management are warranted.
Advances in knowledge:
The study describes post-radiotherapy osteomyelitis of the cervical spine, a rare and devastating complication. Literature data regarding this complication are sparse.
Objective
Evaluate whether biomarkers measured by automated artificial intelligence (AI)-based algorithms are suggestive of future fall risk.
Methods
In this retrospective age- and sex-matched ...case–control study, 9029 total patients underwent initial abdominal CT for a variety of indications over a 20-year interval at one institution. 3535 case patients (mean age at initial CT, 66.5 ± 9.6 years; 63.4% female) who went on to fall (mean interval to fall, 6.5 years) and 5494 controls (mean age at initial CT, 66.7 ± 9.8 years; 63.4% females; mean follow-up interval, 6.6 years) were included. Falls were identified by electronic health record review. Validated and fully automated quantitative CT algorithms for skeletal muscle, adipose tissue, and trabecular bone attenuation at the level of L1 were applied to all scans. Uni- and multivariate assessment included hazard ratios (HRs) and area under the receiver operating characteristic (AUROC) curve.
Results
Fall HRs (with 95% CI) for low muscle Hounsfield unit, high total adipose area, and low bone Hounsfield unit were 1.82 (1.65–2.00), 1.31 (1.19–1.44) and 1.91 (1.74–2.11), respectively, and the 10-year AUROC values for predicting falls were 0.619, 0.556, and 0.639, respectively. Combining all these CT biomarkers further improved the predictive value, including 10-year AUROC of 0.657.
Conclusion
Automated abdominal CT-based opportunistic measures of muscle, fat, and bone offer a novel approach to risk stratification for future falls, potentially by identifying patients with osteosarcopenic obesity.
Advances in knowledge
There are few well-established clinical tools to predict falls. We use novel AI-based body composition algorithms to leverage incidental CT data to help determine a patient’s future fall risk.
This review article visits the current state of artificial intelligence (AI) in radiotherapy clinical practice. We will discuss how AI has a place in the modern radiotherapy workflow at the level of ...automatic segmentation and planning, two applications which have seen real-work implementation. A special emphasis will be placed on the role AI can play in online adaptive radiotherapy, such as performed at MR-linacs, where online plan adaptation is a procedure which could benefit from automation to reduce on-couch time for patients. Pseudo-CT generation and AI for motion tracking will be introduced in the scope of online adaptive radiotherapy as well. We further discuss the use of AI for decision-making and response assessment, for example for personalized prescription and treatment selection, risk stratification for outcomes and toxicities, and AI for quantitative imaging and response assessment. Finally, the challenges of generalizability and ethical aspects will be covered. With this, we provide a comprehensive overview of the current and future applications of AI in radiotherapy.
Bibliometrics analysis is a widely used approach that enables influential research within specific fields to be identifiedTo identify the 100 most-cited articles in breast radiology and analyse the ...trend in breast imaging research.
A systematic search was conducted using the Thomson Rheuters Web of Science database. The results were ranked according to citation count and screened to create a single database. Data including first author, year of publication, journal, country of origin, primary institution, number of citations and average number of citations per year were extracted, as well as the impact factor and the 5-year impact factor of journals publishing the articles.
The systematic search yielded a total of 114,426 articles, after filters were applied to include papers that were available in English only. Citations for the 100 most-cited articles ranged from 515 to 3660. Half of the articles on the list were published between 2001 and 2010. Radiology has the most number of publications (
= 17), followed by JAMA-Journal of The American Medical Association (
= 9). CA-A Cancer Journal For Clinicians had the highest impact factor of 286.13. Mammogram (
= 49) was the most commonly studied modality, followed by Magnetic Resonance (
= 26). The most common topic of publication was diagnosis (
= 83).
This research serves as a guide to the most influential articles on the topic of breast radiology.
Objective
To compare a fixed-volume contrast medium (CM) protocol with a combined total body weight (TBW) and body composition-tailored protocol in chest CT.
Methods and materials
Patients referred ...for routine contrast enhanced chest CT were prospectively categorised as normal, muscular or overweight. Patients were accordingly randomised into two groups; Group 1 received a fixed CM protocol. Group 2 received CM volume according to a body composition-tailored protocol. Objective image quality comparisons between protocols and body compositions were performed. Differences between groups and correlation were analysed using t-test and Pearson’s r.
Results
A total of 179 patients were included: 87 in Group 1 (mean age, 51 ± 17 years); and 92 in Group 2 (mean age, 52 ± 17 years). Compared to Group 2, Group 1 showed lower vascular attenuation in muscular (mean 346 Hounsfield unit (HU) vs 396 HU; p = 0.004) and overweight categories (mean 342 HU vs 367 HU; p = 0.12), while normal category patients showed increased attenuation (385 vs 367; p = 0.61). In Group 1, strongest correlation was found between attenuation and TBW in muscular (r = −.49, p = 0.009) and waist circumference in overweight patients (r = −.50, p = 0.005). In Group 2, no significant correlations were found for the same body size parameters. In Group 1, 13% of the overweight patients was below 250 HU (p = 0.053).
Conclusion
A combined TBW and body composition-tailored CM protocol in chest CT resulted in more homogenous enhancement and fewer outliers compared to a fixed-volume protocol.
Advances in knowledge
This is, to our knowledge, the first study to investigate the impact of various body compositions on contrast medium enhancement in chest CT.
Proton therapy has a theoretical dosimetric advantage due to the Bragg peak, but the linear energy transfer (LET), and therefore the relative biological effectiveness (RBE), increase at the end of ...range. For patients with Hodgkin lymphoma, the distal edge of beam is often located within or close to the heart, where elevated RBE would be of potential concern. The purpose of this study was to investigate the impact of RBE and the choice of beam arrangement for adolescent patients with mediastinal Hodgkin lymphoma.
For three previously treated adolescent patients, proton plans with 1-3 fields were created to a prescribed dose of 19.8 Gy (RBE) in 11 fractions (Varian Eclipse v13.7), assuming an RBE of 1.1. Plans were recalculated using Monte-Carlo (Geant4 v10.3.3/Gate v8.1) to calculate dose-averaged LET. Variable RBE-weighted dose was calculated using the McNamara model, assuming an α/β ratio of 2 Gy for organs-at-risk.
Although the LET decreased as the number of fields increased, the difference in RBE-weighted dose (Δdose) to organs-at-risk did not consistently decrease. Δdose values varied by patient and organ and were mostly of the order of 0-3 Gy (RBE), with a worst-case of 4.75 Gy (RBE) in near-maximum dose to the left atrium for one plan.
RBE-weighted doses to organs-at-risk are sensitive to the choice of RBE model, which is of particular concern for the heart.
There is a need to remain cautious when evaluating proton plans for Hodgkin lymphoma, especially when near-maximum doses to organs-at-risk are considered.
In this review, we summarize state-of-the-art artificial intelligence applications for non-invasive cardiovascular imaging modalities including CT, MRI, echocardiography, and nuclear myocardial ...perfusion imaging.
Cutaneous lesions are derived from the epidermis, dermis and cutaneous appendages. Whilst imaging may occasionally be performed to evaluate such lesions, they may be undiagnosed and demonstrated for ...the first time on head and neck imaging studies. Although usually amenable to clinical examination and biopsy, CT or MRI studies may also demonstrate characteristic imaging features which aid the radiological differential diagnosis. In addition, imaging studies define the extent and staging of malignant lesions, as well as the complications of benign lesions. It is important for the radiologist to understanding the clinical significance and associations of these cutaneous conditions. This pictorial review will describe and depict the imaging appearances of benign, malignant, overgrowth, blistering, appendage and syndromic cutaneous lesions. An increasing awareness of the imaging characteristics of cutaneous lesions and related conditions will help the framing of a clinically relevant report.
