BJR open最新文献

Objectives: The aim of this study was to evaluate the length of time required to achieve full iodination using potassium tri-iodide as a contrast agent, prior to human fetal postmortem microfocus computed tomography (micro-CT) imaging.

Methods: Prospective assessment of optimal contrast iodination was conducted across 157 human fetuses (postmortem weight range 2-298 g; gestational age range 12-37 weeks), following micro-CT imaging. Simple linear regression was conducted to analyse which fetal demographic factors could produce the most accurate estimate for optimal iodination time.

Results: Postmortem body weight (r² = 0.6435) was better correlated with iodination time than gestational age (r² = 0.1384), producing a line of best fit, y = [0.0304 × body weight (g)] - 2.2103. This can be simplified for clinical use whereby immersion time (days) = [0.03 × body weight (g)] - 2.2. Using this formula, for example, a 100-g fetus would take 5.2 days to reach optimal contrast enhancement.

Conclusions: The simplified equation can now be used to provide estimation times for fetal contrast preparation time prior to micro-CT imaging and can be used to manage service throughput and parental expectation for return of their fetus.

Advances in knowledge: A simple equation from empirical data can now be used to estimate preparation time for human fetal postmortem micro-CT imaging.

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: The objectives of this study are: (1) to develop a convolutional neural network model that yields pseudo high-energy CT (CT_{pseudo_high}) from simple image processed low-energy CT (CT_low) images, and (2) to create a pseudo iodine map (IM_pseudo) and pseudo virtual non-contrast (VNC_pseudo) images for thoracic and abdominal regions.

Methods: Eighty patients who underwent dual-energy CT (DECT) examinations were enrolled. The data obtained from 55, 5, and 20 patients were used for training, validation, and testing, respectively. The ResUnet model was used for image generation model and was trained using CT_low and high-energy CT (CT_high) images. The proposed model performance was evaluated by calculating the CT values, image noise, mean absolute errors (MAEs), and histogram intersections (HIs).

Results: The mean difference in the CT values between CT_{pseudo_high} and CT_high images were less than 6 Hounsfield unit (HU) for all evaluating patients. The image noise of CT_{pseudo_high} was significantly lower than that of CT_high. The mean MAEs was less than 15 HU, and HIs were almost 1.000 for all the patients. The evaluation metrics of IM and VNC exhibited the same tendency as that of the comparison between CT_{pseudo_high} and CT_high images.

Conclusions: Our results indicated that the proposed model enables to obtain the DECT images and material-specific images from only single-energy CT images.

Advances in knowledges: We constructed the CNN-based model which can generate pseudo DECT image and DECT-derived material-specific image using only simple image-processed CT_low images for the thoracic and abdominal regions.

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.

Objective: The objective of this study was to assess the technical feasibility, safety, and efficacy of transperineal laser ablation (TPLA) guided by ultrasound/magnetic resonance (MR) fusion as a salvage treatment for refractory focal prostate cancer.

Methods: A total of five patients who had undergone radiation therapy (RT) for prostate carcinoma and biochemical recurrence, confirmed by both prostate-specific antigen (PSA) levels and MRI (3T mpMRI), were enrolled in this study. Focal ablation was performed using a 1064 nm diode laser. Post-ablation follow-up was conducted for a duration of 18 months, which included regular PSA sampling, 3T mpMRI, and ultrasound/MR fusion-guided biopsies systematic and targeted at the site of the focal treatment.

Results: The focal ablation procedure was carried out in an outpatient setting regimen with optimal clinical and biochemical outcomes. No recurrence was detected throughout the follow-up period.

Conclusion: TPLA focal treatment effectively manages local recurrences of RT refractory prostate cancer without side-effects or complications. Preservation of quality of life and functional outcomes, along with a >70% reduction in PSA, were achieved.

Advances in knowledge: Our study investigated TPLA as a salvage treatment for low-risk recurrent prostate cancer after RT, demonstrating its tolerability, feasibility, and effectiveness.

Objective: The objective of this review was to examine the impact of previous mammogram availability on radiologists' performance from screening populations and experimental studies.

Materials and methods: A search of the literature was conducted using five databases: MEDLINE, PubMed, Web of Science, ScienceDirect, and CINAHL as well as Google and reference lists of articles. Keywords were combined with "AND" or "OR" or "WITH" and included "prior mammograms, diagnostic performance, initial images, diagnostic efficacy, subsequent images, previous imaging, and radiologist's performance". Studies that assessed the impact of previous mammogram availability on radiologists' performance were reviewed. The Standard for Reporting Diagnostic Accuracy guidelines was used to critically appraise individual sources of evidence.

Results: A total of 15 articles were reviewed. The sample of mammogram cases used across these studies varied from 36 to 1,208,051. Prior mammograms did not affect sensitivity [with priors: 62-86% (mean = 73.3%); without priors: 69.4-87.4% (mean = 75.8%)] and cancer detection rate, but increased specificity [with priors: 72-96% (mean = 87.5%); without priors: 63-87% (mean = 80.5%)] and reduced false-positive rates [with priors: 3.7 to 36% (mean = 19.9%); without priors 13.3-49% (mean = 31.4%)], recall rates [with priors: 3.8-57% (mean = 26.6%); without priors: [4.9%-67.5% (mean = 37.9%)], and abnormal interpretation rate decreased by 4% with priors. Evidence for the associations between the availability of prior mammograms and positive-predictive value, area under the curve (AUC) from the receiver operating characteristic curve (ROC) and localisation ROC AUC, and positive-predictive value of recall is limited and unclear.

Conclusion: Availability of prior mammograms reduces recall rates, false-positive rates, abnormal interpretation rates, and increases specificity without affecting sensitivity and cancer detection rate.

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.

Objectives: We aimed to investigate whether daily computed tomography (CT) images could predict the daily gastroduodenal, small intestine, and large intestine doses of stereotactic body radiation therapy (SBRT) for pancreatic cancer based on the shortest distance between the gross tumor volume (GTV) and gastrointestinal (GI) tract.

Methods: Twelve patients with pancreatic cancer received SBRT of 40 Gy in five fractions. We recalculated the reference clinical SBRT plan (PLAN_ref) using daily CT images and calculated the shortest distance from the GTV to each GI tract. The maximum dose delivered to 0.5 cc (D_0.5cc) was evaluated for each planning at-risk volume of the GI tract. Spearman's correlation test was used to determine the association between the daily change in the shortest distance (Δshortest distance) and the ratio of ΔD_0.5cc dose to D_0.5cc dose in PLAN_ref (ΔD_0.5cc/PLAN_ref) for quantitative analysis.

Results: The median shortest distance in PLAN_ref was 0 mm in the gastroduodenum (interquartile range, 0-2.7), 16.7 mm in the small intestine (10.0-23.7), and 16.7 mm in the large intestine (8.3-28.1 mm). The D_0.5cc of PLAN_ref in the gastroduodenum was >30 Gy in all patients, with 10 (83.3%) having the highest dose. A significant association was found between the Δshortest distance and ΔD_0.5cc/ PLAN_ref in the small or large intestine (p < 0.001) but not in the gastroduodenum (p = 0.404).

Conclusions: The gastroduodenum had a higher D_0.5cc and predicting the daily dose was difficult. Daily dose calculations of the GI tract are recommended for safe SBRT.

Advances in knowledge: This study aimed to predict the daily doses in SBRT for pancreatic cancer from the shortest distance between the GTV and the gastrointestinal tract.Daily changes in the shortest distance can predict the daily dose to the small or large intestines, but not to the gastroduodenum.

Amide proton transfer-weighted (APTw) imaging is a non-invasive molecular MRI technique with a wide range of applications in neuroradiology and particularly neuro-oncology imaging. More than 15 years of pre-clinical experiments and clinical studies have demonstrated that APTw metrics are reproducible and reliable, leading to large-scale clinical acceptance. At present, major vendors of MRI scanners provide APTw sequences upon request. However, most neuroradiologists are unfamiliar with this advanced MRI contrast, its related metrics, and its established added value to patient care. In this manuscript, we present the APTw contrast and illustrate its clinical potential for glioma patients, before and after tumor therapy. We also show common artifacts of APTw imaging and discuss potential limitations and future refinements. Our goal is to suggest how this emerging technique can aid in diffuse gliomas work-up.

Magnetic resonance imaging (MRI) plays a significant role in the routine imaging workflow, providing both anatomical and functional information. 19F MRI is an evolving imaging modality where instead of 1H, 19F nuclei are excited. As the signal from endogenous 19F in the body is negligible, exogenous 19F signals obtained by 19F radiofrequency coils are exceptionally specific. Highly fluorinated agents targeting particular biological processes (i.e., the presence of immune cells) have been visualised using 19F MRI, highlighting its potential for non-invasive and longitudinal molecular imaging. This article aims to provide both a broad overview of the various applications of 19F MRI, with cancer imaging as a focus, as well as a practical guide to 19F imaging. We will discuss the essential elements of a 19F system and address common pitfalls during acquisition. Last but not least, we will highlight future perspectives that will enhance the role of this modality. While not an exhaustive exploration of all 19F literature, we endeavour to encapsulate the broad themes of the field and introduce the world of 19F molecular imaging to newcomers. 19F MRI bridges several domains, imaging, physics, chemistry, and biology, necessitating multidisciplinary teams to be able to harness this technology effectively. As further technical developments allow for greater sensitivity, we envision that 19F MRI can help unlock insight into biological processes non-invasively and longitudinally.