Marrow Fat-Cortical Bone Relationship in ß-Thalassemia: A Study Using MRI.

BACKGROUND: Growing evidence suggests that marrow adipocytes play an active role in the regulation of bone metabolism and hematopoiesis. However, research on the relationship between bone and fat in the context of hematological diseases, particularly ß-thalassemia, remains limited. PURPOSE: To investigate the relationship between marrow fat and cortical bone thickness in ß-thalassemia and to identify key determinants influencing these variables. STUDY TYPE: Prospective. SUBJECTS: Thirty-five subjects in four subject groups of increasing disease severity: 6 healthy control (25.0 ± 5.3 years, 2 male), 4 ß-thalassemia minor, 13 intermedia, and 12 major (29.1 ± 6.4 years, 15 male). FIELD STRENGTH/SEQUENCE: 3.0 T, 3D fast low angle shot sequence and T1-weighted turbo spin echo. ASSESSMENT: Analyses on proton density fat fraction (PDFF) and R2* values in femur subregions (femoral head, greater trochanter, intertrochanteric, diaphysis, distal) and cortical thickness (CBI) of the subjects' left femur. Clinical data such as age, sex, body mass index (BMI), and disease severity were also included. STATISTICAL TESTS: One-way analysis of variance (ANOVA), mixed ANOVA, Pearson correlation and multiple regression. P-values <0.05 were considered significant. RESULTS: Bone marrow PDFF significantly varied between the femur subregions, F(2.89,89.63) = 44.185 and disease severity, F(1,3) = 12.357. A significant interaction between subject groups and femur subregions on bone marrow PDFF was observed, F(8.67,89.63) = 3.723. Notably, a moderate positive correlation was observed between PDFF and CBI (r = 0.33-0.45). Multiple regression models for both PDFF (R2 = 0.476, F(13,151) = 10.547) and CBI (R2 = 0.477, F(13,151) = 10.580) were significant. Significant predictors for PDFF were disease severity (ßTMi = 0.36, ßTMa = 0.17), CBI (ß = 0.24), R2* (ß = -0.32), and height (ß = -0.29) while for CBI, the significant determinants were sex (ß = -0.27), BMI (ß = 0.55), disease severity (ßTMi = 2.15), and PDFF (ß = 0.25). DATA CONCLUSION: This study revealed a positive correlation between bone marrow fat fraction and cortical bone thickness in ß-thalassemia with varying disease severity, potentially indicating a complex interplay between bone health and marrow composition. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Shear wave elastography in chronic kidney disease - the physics and clinical application.

Chronic kidney disease is a leading public health problem worldwide. The global prevalence of chronic kidney disease is nearly five hundred million people, with almost one million deaths worldwide. Estimated glomerular filtration rate, imaging such as conventional ultrasound, and histopathological findings are necessary as each technique provides specific information which, when taken together, may help to detect and arrest the development of chronic kidney disease, besides managing its adverse outcomes. However, estimated glomerular filtration rate measurements are hampered by substantial error margins while conventional ultrasound involves subjective assessment. Although histopathological assessment is the best tool for evaluating the severity of the renal pathology, it may lead to renal insufficiency and haemorrhage if complications occurred. Ultrasound shear wave elastography, an emerging imaging that quantifies tissue stiffness non-invasively has gained interest recently. This method applies acoustic force pulses to generate shear wave within the tissue that propagate perpendicular to the main ultrasound beam. By measuring the speed of shear wave propagation, the tissue stiffness is estimated. This paper reviews the literature and presents our combined experience and knowledge in renal shear wave elastography research. It discusses and highlights the confounding factors on shear wave elastography, current and future possibilities in ultrasound renal imaging and is not limited to new sophisticated techniques.

Opportunistic Extraction of Quantitative CT Biomarkers: Turning the Incidental Into Prognostic Information.

The past two decades have seen a significant increase in the use of CT, with a corresponding rise in the mean population radiation dose. This rise in CT use has caused improved diagnostic certainty in conditions that were not previously routinely evaluated using CT, such as headaches, back pain, and chest pain. Unused data, unrelated to the primary diagnosis, embedded within these scans have the potential to provide organ-specific measurements that can be used to prognosticate or risk-profile patients for a wide variety of conditions. The recent increased availability of computing power, expertise and software for automated segmentation and measurements, assisted by artificial intelligence, provides a conducive environment for the deployment of these analyses into routine use. Data gathering from CT has the potential to add value to examinations and help offset the public perception of harm from radiation exposure. We review the potential for the collection of these data and propose the incorporation of this strategy into routine clinical practice.

Dielectric properties of urine in relation to bladder cancer.

Many studies have investigated the dielectric properties of human and animal tissues, particularly to differentiate between normal cells and tumors. However, these studies are invasive as tissue samples have to be excised to measure the properties. This study aims to investigate the dielectric properties of urine in relation to bladder cancer, which is safe and non-invasive to patients. 30 healthy subjects and 30 bladder cancer patients were recruited. Their urine samples were subjected to urinalysis and cytology assessment. A vector network analyzer was used to measure the dielectric constant (Ɛ') and loss factor (Ɛ″) at microwave frequencies of between 0.2 and 50 GHz at 25 °C, 30 °C and 37 °C. Significant differences in Ɛ' and Ɛ″ were observed between healthy subjects and patients, especially at frequencies of between 25 and 40 GHz at 25 °C. Bladder cancer patients had significant lower Ɛ' and higher Ɛ″ compared with healthy subjects. The Ɛ' was negatively correlated with urinary exfoliated urothelial cell number, and Ɛ″ was positively correlated. The study achieved a receiver operating characteristic area under curve (ROC-AUC) score of 0.69099 and an optimum accuracy of 75% with a sensitivity of 80% and a specificity of 70%. The number of exfoliated urothelial cell had significant effect on the dielectric properties, especially in bladder cancer patients. Urinary dielectric properties could potentially be used as a tool to detect bladder cancer.

Classification and assessment techniques of breast ptosis: A systematic review.

BACKGROUND: Breast ptosis is characterized by the inferolateral descent of the glandular area and nipple-areola complex. A high degree of ptosis may negatively impact a woman's attractiveness and self-confidence. There are various classifications and measurement techniques for breast ptosis used as references in the medical and garment industry. A practical and comprehensive classification will provide accurate standardized definitions of the degrees of ptosis to facilitate the development of corrective surgeries and well-fitting undergarments for women in need. METHODS: A systematic review on the classification and assessment techniques to measure breast ptosis was carried out based on the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias was assessed using the modified Newcastle-Ottawa scale for observational studies, whereas the Revised Cochrane risk-of-bias tool for randomized trials (RoB2) was used to evaluate randomized studies. RESULTS: Of 2550 articles identified in the literature search, 16 observational and 2 randomized studies describing the classification and assessment techniques of breast ptosis were included in the review. A total of 2033 subjects were involved. Half of the total observational studies had a Newcastle-Ottawa scale score of 5 and above. In addition, all randomized trials recorded a low overall bias. CONCLUSION: A total of 7 classifications and 4 measurement techniques for breast ptosis were identified. However, most studies did not demonstrate a clear derivation of sample size beside lacking robust statistical analysis. Hence, further studies that apply the latest technology to combine the strength of previous assessment techniques are needed to develop better classification system that is applicable to all affected women.

Three-dimensional topological radiogenomics of epidermal growth factor receptor Del19 and L858R mutation subtypes on computed tomography images of lung cancer patients.

OBJECTIVES: To elucidate a novel radiogenomics approach using three-dimensional (3D) topologically invariant Betti numbers (BNs) for topological characterization of epidermal growth factor receptor (EGFR) Del19 and L858R mutation subtypes. METHODS: In total, 154 patients (wild-type EGFR, 72 patients; Del19 mutation, 45 patients; and L858R mutation, 37 patients) were retrospectively enrolled and randomly divided into 92 training and 62 test cases. Two support vector machine (SVM) models to distinguish between wild-type and mutant EGFR (mutation [M] classification) as well as between the Del19 and L858R subtypes (subtype [S] classification) were trained using 3DBN features. These features were computed from 3DBN maps by using histogram and texture analyses. The 3DBN maps were generated using computed tomography (CT) images based on the Cech complex constructed on sets of points in the images. These points were defined by coordinates of voxels with CT values higher than several threshold values. The M classification model was built using image features and demographic parameters of sex and smoking status. The SVM models were evaluated by determining their classification accuracies. The feasibility of the 3DBN model was compared with those of conventional radiomic models based on pseudo-3D BN (p3DBN), two-dimensional BN (2DBN), and CT and wavelet-decomposition (WD) images. The validation of the model was repeated with 100 times random sampling. RESULTS: The mean test accuracies for M classification with 3DBN, p3DBN, 2DBN, CT, and WD images were 0.810, 0.733, 0.838, 0.782, and 0.799, respectively. The mean test accuracies for S classification with 3DBN, p3DBN, 2DBN, CT, and WD images were 0.773, 0.694, 0.657, 0.581, and 0.696, respectively. CONCLUSION: 3DBN features, which showed a radiogenomic association with the characteristics of the EGFR Del19/L858R mutation subtypes, yielded higher accuracy for subtype classifications in comparison with conventional features.

Evaluation of physical properties and image of polyvinyl chloride as breast tissue equivalence for dual-modality (mammography and ultrasound).

TMP is gradually becoming a fundamental element for quality assurance and control in ionizing and non-ionizing radiation imaging modalities as well as in the development of different techniques. This study aimed to evaluate and obtain polyvinyl chloride tissue mimicking material for dual-modality breast phantoms in mammography and ultrasound. Breast tissue equivalence was evaluated based on X-ray attenuation properties, speed of sound, attenuation, and acoustic impedance. There are six samples of PVC-plasticizer material with variations of PVC concentration and additives. The evaluation of X-ray attenuation was carried out using mammography from 23 to 35 kV, while the acoustic properties were assessed with mode A ultrasound and a transducer frequency of 5 MHz. A breast phantom was created from TMP material with tissue equivalence and was then evaluated using mammography as well as ultrasound to analyze its image quality. The results showed that samples A (PVC 5%, DOP 95%), B (PVC 7%, DOP 93%), C (PVC 10%, DOP 90%), E (PVC 7%, DOP 90%, graphite 3%), and F (PVC 7%, DOP 90%, silicone oil 3%) have the closest equivalent to the ACR breast phantom material with a different range of 0.01-1.39 in the 23-35 kV range. Based on the evaluation of the acoustic properties of ultrasound, A had high similarity to fat tissue with a difference of 0.03 (dB cm- 1 MHz- 1) and 0.07 (106 kg m- 2 s- 1), while B was close to the glandular tissue with a difference of 9.2 m s- 1. Multilayer breast phantom images' results showed gray levels in mammography and ultrasound modalities. Therefore, this study succeeded in establishing TMP material for mammography and ultrasound. It can also be used for simple quality assurance and control programs.

Ultrasound shear wave elastography for the evaluation of renal pathological changes in adult patients.

OBJECTIVE: Many studies have conflicting findings in using shear wave elastography (SWE) to assess renal fibrosis. This study reviews the use of SWE to evaluate pathological changes in native kidneys and renal allografts. It also tries to elucidate the confounding factors and care taken to ensure the results are consistent and reliable. METHODS: The review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Literature search was conducted in Pubmed, Web of Science and Scopus database up to 23 October 2021. To evaluate risk and bias applicability, the Cochrane risk-of bias tool and GRADE was used. The review was registered under PROSPERO CRD42021265303. RESULTS: A total of 2921 articles were identified. 104 full texts were examined and 26 studies included in systematic review. 11 studies performed on native kidneys and 15 studies on transplanted kidney. A wide range of impact factors was found that affect the accuracy of SWE of renal fibrosis in adult patients. CONCLUSIONS: Compared to point SWE, two-dimensional SWE with elastogram could enable better selection of the region of interest in kidneys, leading to reproducible results. Tracking waves were attenuated as the depth from skin to region of interest increased, therefore, SWE is not recommended for overweight or obese patients. Variable transducer forces might also affect SWE reproducibility, thus, training of operators to ensure consistent operator-dependent transducer forces may be helpful. ADVANCES IN KNOWLEDGE: This review provides a holistic insight on the efficiency of using SWE in evaluating pathological changes in native and transplanted kidneys, thereby contributing to the knowledge of its utilisation in clinical practice.

Development of the modified safety attitude questionnaire for the medical imaging department.

Introduction: Medical errors commonly occur in medical imaging departments. These errors are frequently influenced by patient safety culture. This study aimed to develop a suitable patient safety culture assessment tool for medical imaging departments. Methods: Staff members of a teaching hospital medical imaging department were invited to complete the generic short version of the Safety Attitude Questionnaire (SAQ). Internal consistency and reliability were evaluated using Cronbach's α. Confirmatory factor analysis (CFA) was conducted to examine model fit. A cut-off of 60% was used to define the percentage positive responses (PPR). PPR values were compared between occupational groups. Results: A total of 300 complete responses were received and the response rate was 75.4%. In reliability analysis, the Cronbach's α for the original 32-item SAQ was 0.941. Six subscales did not demonstrate good fit with CFA. A modified five-subscale, 22-item model (SAQ-MI) showed better fit (goodness-to-fit index ≥0.9, comparative fit index ≥ 0.9, Tucker-Lewis index ≥0.9 and root mean square error of approximation ≤0.08). The Cronbach's α for the 22 items was 0.921. The final five subscales were safety and teamwork climate, job satisfaction, stress recognition, perception of management and working condition, with PPR of 62%, 68%, 57%, 61% and 60%, respectively. Statistically significant differences in PPR were observed between radiographers, doctors and others occupational groups. Conclusion: The modified five-factor, 22-item SAQ-MI is a suitable tool for the evaluation of patient safety culture in a medical imaging department. Differences in patient safety culture exist between occupation groups, which will inform future intervention studies.

Quality Improvement Report: Safety Program for Prevention of Central Line-associated Bloodstream Infections.

The increasing usage of peripherally inserted central catheters (PICCs) in medical imaging departments has led to a corresponding increase in cases of central line-associated bloodstream infection (CLABSI). However, this condition is preventable with proper monitoring and use of aseptic techniques. A Comprehensive Unit-based Safety Program (CUSP) is a quality improvement (QI) measure implemented by health care institutions to reduce the incidence of CLABSI. However, effective strategies have yet to be established. The authors describe a QI project that evaluated the implementation of CUSP at a teaching hospital to reduce PICC-associated bloodstream infection (BSI). The framework consists of a five-step process: understand and train staff on the science of safety, assemble a team, engage senior executives, identify defects through sensemaking, and implement teamwork and communication strategies in a series of related and sequential steps that use QI tools. Targets were identified for improvement from existing processes, and the workflow was reengineered. Nine months after the start of the CUSP intervention, PICC-associated BSI incidence in the hospital had been reduced from 3.4 to 2.7 per 1000 central lines days after intervention. The incidence of BSI was also reduced correspondingly from 8.8% to 5.9%. The QI processes in this study may be adopted by other hospitals, as they involve minimal cost with significant impact on patient safety and well-being. The QI sequential steps described capture the implementation processes that can be modified for use in other department settings where patient safety could be compromised. Online supplemental material is available for this article. ©RSNA, 2022.

Utilizing 3D Slicer to incorporate tomographic images into GATE Monte Carlo simulation for personalized dosimetry in yttrium-90 radioembolization.

PURPOSE: Monte Carlo (MC) simulation is an important technique that can help design advanced and challenging experimental setups. GATE (Geant4 application for tomographic emission) is a useful simulation toolkit for applications in nuclear medicine. Transarterial radioembolization is a treatment for liver cancer, where microspheres embedded with yttrium-90 (90 Y) are administered intra-arterially to the tumor. Personalized dosimetry for this treatment may provide higher dosimetry accuracy compared to the conventional partition model (PM) calculation. However, incorporation of three-dimensional tomographic input data into MC simulation is an intricate process. In this article, 3D Slicer, free and open-source software, was utilized for the incorporation of patient tomographic images into GATE to demonstrate the feasibility of personalized dosimetry in hepatic radioembolization with 90 Y. METHODS: In this article, the steps involved in importing, segmenting, and registering tomographic images using 3D Slicer were thoroughly described, before importing them into GATE for MC simulation. The absorbed doses estimated using GATE were then compared with that of PM. SlicerRT, a 3D Slicer extension, was then used to visualize the isodose from the MC simulation. RESULTS: A workflow diagram consisting of all the steps taken in the utilization of 3D Slicer for personalized dosimetry in 90 Y radioembolization has been presented in this article. In comparison to the MC simulation, the absorbed doses to the tumor and normal liver were overestimated by PM by 105.55% and 20.23%, respectively, whereas for lungs, the absorbed dose estimated by PM was underestimated by 25.32%. These values were supported by the isodose distribution obtained via SlicerRT, suggesting the presence of beta particles outside the volumes of interest. These findings demonstrate the importance of personalized dosimetry for a more accurate absorbed dose estimation compared to PM. CONCLUSION: The methodology provided in this study can assist users (especially students or researchers who are new to MC simulation) in navigating intricate steps required in the importation of tomographic data for MC simulation. These steps can also be utilized for other radiation therapy related applications, not necessarily limited to internal dosimetry.

Automated Classification of Atherosclerotic Radiomics Features in Coronary Computed Tomography Angiography (CCTA).

Radiomics is the process of extracting useful quantitative features of high-dimensional data that allows for automated disease classification, including atherosclerotic disease. Hence, this study aimed to quantify and extract the radiomic features from Coronary Computed Tomography Angiography (CCTA) images and to evaluate the performance of automated machine learning (AutoML) model in classifying the atherosclerotic plaques. In total, 202 patients who underwent CCTA examination at Institut Jantung Negara (IJN) between September 2020 and May 2021 were selected as they met the inclusion criteria. Three primary coronary arteries were segmented on axial sectional images, yielding a total of 606 volume of interest (VOI). Subsequently, the first order, second order, and shape order of radiomic characteristics were extracted for each VOI. Model 1, Model 2, Model 3, and Model 4 were constructed using AutoML-based Tree-Pipeline Optimization Tools (TPOT). The heatmap confusion matrix, recall (sensitivity), precision (PPV), F1 score, accuracy, receiver operating characteristic (ROC), and area under the curve (AUC) were analysed. Notably, Model 1 with the first-order features showed superior performance in classifying the normal coronary arteries (F1 score: 0.88; Inverse F1 score: 0.94), as well as in classifying the calcified (F1 score: 0.78; Inverse F1 score: 0.91) and mixed plaques (F1 score: 0.76; Inverse F1 score: 0.86). Moreover, Model 2 consisting of second-order features was proved useful, specifically in classifying the non-calcified plaques (F1 score: 0.63; Inverse F1 score: 0.92) which are a key point for prediction of cardiac events. Nevertheless, Model 3 comprising the shape-based features did not contribute to the classification of atherosclerotic plaques. Overall, TPOT shown promising capabilities in terms of finding the best pipeline and tailoring the model using CCTA-based radiomic datasets.

Current challenges of implementing artificial intelligence in medical imaging.

The idea of using artificial intelligence (AI) in medical practice has gained vast interest due to its potential to revolutionise healthcare systems. However, only some AI algorithms are utilised due to systems' uncertainties, besides the never-ending list of ethical and legal concerns. This paper intends to provide an overview of current AI challenges in medical imaging with an ultimate aim to foster better and effective communication among various stakeholders to encourage AI technology development. We identify four main challenges in implementing AI in medical imaging, supported with consequences and past events when these problems fail to mitigate. Among them is the creation of a robust AI algorithm that is fair, trustable and transparent. Another issue is on data governance, in which best practices in data sharing must be established to promote trust and protect the patients' privacy. Next, stakeholders, such as the government, technology companies and hospital management, should come to a consensus in creating trustworthy AI policies and regulatory frameworks, which is the fourth challenge, to support, encourage and spur innovation in digital AI healthcare technology. Lastly, we discussed the efforts of various organizations such as the World Health Organisation (WHO), American College of Radiology (ACR), European Society of Radiology (ESR) and Radiological Society of North America (RSNA), who are already actively pursuing ethical developments in AI. The efforts by various stakeholders will eventually overcome hurdles and the deployment of AI-driven healthcare applications in clinical practice will become a reality and hence lead to better healthcare services and outcomes.

Overcoming the Fukushima Wastewater Crisis: What the Japanese Authorities Could Do to Address Opposing Views.

ABSTRACT: In April 2021, the Japanese authorities' announcement of their decision to release processed wastewater from the damaged Fukushima Daiichi nuclear power plant into the Pacific Ocean over 30 y, beginning in 2023, triggered strong domestic and international opposition. Failure to handle this situation tactfully can lead to public disorder, civil disobedience, loss of trust in the authorities, and even diplomatic sanctions. In this article, we explain the underlying reasons behind this resistance, and we offer some strategic methods that the Japanese authorities can deploy to address opposing views and overcome the Fukushima wastewater crisis.

Magnetic Resonance Imaging Phenotypes of Breast Cancer Molecular Subtypes: A Systematic Review.

OBJECTIVE: Magnetic resonance imaging (MRI) is the most sensitive imaging modality in detecting breast cancer. The purpose of this systematic review is to investigate the role of human extracted MRI phenotypes in classifying molecular subtypes of breast cancer. METHODS: We performed a literature search of published articles on the application of MRI phenotypic features in invasive breast cancer molecular subtype classifications by radiologists' interpretation on Medline Complete, Pubmed, and Google scholar from 1st January 2000 to 31st March 2021. Of the 1453 literature identified, 42 fulfilled the inclusion criteria. RESULTS: All studies were case-controlled, retrospective study and research-based. The majority of the studies assessed the MRI features using American College of Radiology- Breast Imaging Reporting and Data System (ACR-BIRADS) classification and using dynamic contrast-enhanced (DCE) kinetic features, Apparent Diffusion Coefficient (ADC) values, and T2 sequence. Most studies divided invasive breast cancer into 4 main subtypes, luminal A, luminal B, HER2, and triple-negative (TN) cancers, and used 2 readers. We present a summary of the radiologists' extracted breast MRI phenotypical features and their correlating breast cancer subtypes classifications. The characteristic features are morphology, enhancement kinetics, and T2 signal intensity. We found that the TN subtype has the most distinctive MRI features compared to the other subtypes and luminal A and B have many similar features. CONCLUSION: The MRI features which are predictive of each subtype are the morphology, internal enhancement features, and T2 signal intensity, predominantly between TN and the rest. Radiologists' visual interpretation of some of MRI features may offer insight into the respective invasive breast cancer molecular subtype. However, current evidence are still limited to "suggestive" features instead of a diagnostic standard.  Further research is recommended to explore this potential application, for example, by augmentation of radiologists' visual interpretation by artificial intelligence.