BJR open最新文献

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.

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.

Vasculitides represent the wide-ranging series of complex inflammatory diseases that involve inflammation of blood vessel walls. These conditions are characterized according to the caliber of the predominantly involved vessels. The work-up of vasculitides often includes imaging to narrow a differential diagnosis and guide management. Findings from CT and MR angiography in conjunction with a thorough history and physical exam are of utmost importance in making an accurate diagnosis. Further, imaging can be used for follow-up, in order to monitor disease progression and response to treatment. This wide-ranging literature review serves as the primary resource for clinicians looking to diagnose and monitor the progression of rare vascular inflammatory conditions. This article provides a comprehensive summary of the main findings on imaging related to each of these vasculitides. For each of the named vasculitis conditions, a thorough overview of the diagnostic modalities and their respective findings is described. Many specific hallmarks of pathology are included in this review article.

Objectives: To identify issues of principle and practice giving rise to misunderstandings in reviewing evidence, to illustrate these by reference to the Nordic Cochrane Review (NCR) and its interpretation of two trials of mammographic screening, and to draw lessons for future reviewing of published results.

Methods: A narrative review of the publications of the Nordic Cochrane Review of mammographic screening (NCR), the Swedish Two-County Trial (S2C) and the Canadian National Breast Screening Study 1 and 2 (CNBSS-1 and CNBSS-2).

Results: The NCR concluded that the S2C was unreliable, despite the review's complaints being shown to be mistaken, by direct reference to the original primary publications of the S2C. Repeated concerns were expressed by others about potential subversion of randomisation in CNBSS-1 and CNBSS-2; however, the NCR continued to rely heavily on the results of these trials. Since 2022, however, eyewitness evidence of such subversion has been in the public domain.

Conclusions: An over-reliance on nominal satisfaction of checklists of criteria in systematic reviewing can lead to erroneous conclusions. This occurred in the case of the NCR, which concluded that mammographic screening was ineffective or minimally effective. Broader and more even-handed reviews of the evidence show that screening confers a substantial reduction in breast cancer mortality.

Advances in knowledge: Those carrying out systematic reviews should be aware of the dangers of over-reliance on checklists and guidelines. Readers of systematic reviews should be aware that a systematic review is just another study, with the capability that all studies have of coming to incorrect conclusions. When a review seems to overturn the current position, it is essential to revisit the publications of the primary research.

Objective: The primary aim of this study was to assess to what extent 99mTc-HDP Single photon emission computed tomography/computed tomography (SPECT/CT) will lead to change of diagnosis and treatment, in patients with suspected foot and ankle osteoarthritis (OA). Secondary aim was to assess the intraobserver variability.

Methods: Retrospectively 107 patients, with suspected foot and/or ankle OA of which a SPECT/CT was made, were included for analysis. All the clinical and radiological data were randomized and blinded before being scored by one experienced orthopaedic surgeon. Firstly, based on the clinical data and conventional radiographs, a diagnosis and treatment plan was scored. Secondly, the observer accessed the SPECT/CT and could change the diagnosis and treatment plan. Additionally, the intraobserver reliability was determined by data of 18 patients that were added in twofold to the dataset, without awareness of the observer and by calculating the κ values.

Results: The diagnosis changed in 53% (57/107) and treatment plans changed in 26% (28/107) of the patients. Intraobserver reliability for the conventional workup was k = 0.54 (moderate strength of agreement), compared to k = 0.66 (substantial strength of agreement) when SPECT/CT data were added.

Conclusions: This study describes the influence of SPECT/CT on diagnosis and treatment plans in patients with suspected symptomatic OA. Also, it shows SPECT/CT leads to a higher intraobserver variability. We believe SPECT/CT has a promising role in the workup for foot and ankle OA.

Advances in knowledge: In addition to what was found in complex foot and ankle cases, this study shows that in patients with non-complex foot and ankle problems, SPECT/CT has a substantial influence on the diagnosis (and subsequent treatment plan).

Objective: The microscopic analysis of biopsied lung nodules represents the gold-standard for definitive diagnosis of lung cancer. Deep learning has achieved pathologist-level classification of non-small cell lung cancer histopathology images at high resolutions (0.5-2 µm/px), and recent studies have revealed tomography-histology relationships at lower spatial resolutions. Thus, we tested whether patterns for histological classification of lung cancer could be detected at spatial resolutions such as those offered by ultra-high-resolution CT.

Methods: We investigated the performance of a deep convolutional neural network (inception-v3) to classify lung histopathology images at lower spatial resolutions than that of typical pathology. Models were trained on 2167 histopathology slides from The Cancer Genome Atlas to differentiate between lung cancer tissues (adenocarcinoma (LUAD) and squamous-cell carcinoma (LUSC)), and normal dense tissue. Slides were accessed at 2.5 × magnification (4 µm/px) and reduced resolutions of 8, 16, 32, 64, and 128 µm/px were simulated by applying digital low-pass filters.

Results: The classifier achieved area under the curve ≥0.95 for all classes at spatial resolutions of 4-16 µm/px, and area under the curve ≥0.95 for differentiating normal tissue from the two cancer types at 128 µm/px.

Conclusions: Features for tissue classification by deep learning exist at spatial resolutions below what is typically viewed by pathologists.

Advances in knowledge: We demonstrated that a deep convolutional network could differentiate normal and cancerous lung tissue at spatial resolutions as low as 128 µm/px and LUAD, LUSC, and normal tissue as low as 16 µm/px. Our data, and results of tomography-histology studies, indicate that these patterns should also be detectable within tomographic data at these resolutions.

Artificial intelligence (AI) has transitioned from the lab to the bedside, and it is increasingly being used in healthcare. Radiology and Radiography are on the frontline of AI implementation, because of the use of big data for medical imaging and diagnosis for different patient groups. Safe and effective AI implementation requires that responsible and ethical practices are upheld by all key stakeholders, that there is harmonious collaboration between different professional groups, and customised educational provisions for all involved. This paper outlines key principles of ethical and responsible AI, highlights recent educational initiatives for clinical practitioners and discusses the synergies between all medical imaging professionals as they prepare for the digital future in Europe. Responsible and ethical AI is vital to enhance a culture of safety and trust for healthcare professionals and patients alike. Educational and training provisions for medical imaging professionals on AI is central to the understanding of basic AI principles and applications and there are many offerings currently in Europe. Education can facilitate the transparency of AI tools, but more formalised, university-led training is needed to ensure the academic scrutiny, appropriate pedagogy, multidisciplinarity and customisation to the learners' unique needs are being adhered to. As radiographers and radiologists work together and with other professionals to understand and harness the benefits of AI in medical imaging, it becomes clear that they are faced with the same challenges and that they have the same needs. The digital future belongs to multidisciplinary teams that work seamlessly together, learn together, manage risk collectively and collaborate for the benefit of the patients they serve.