Establishment of CTPA Local Diagnostic Reference Levels with Noise Magnitude as a Quality Indicator in a Tertiary Care Hospital

Revising and exploring the variations in methodologies for establishing the diagnostic reference levels for paediatric PET/CT imaging

PET-computed tomography (PET/CT) is a hybrid imaging technique that combines anatomical and functional information; to investigate primary cancers, stage tumours, and track treatment response in paediatric oncology patients. However, there is debate in the literature about whether PET/CT could increase the risk of cancer in children, as the machine is utilizing two types of radiation, and paediatric patients have faster cell division and longer life expectancy. Therefore, it is essential to minimize radiation exposure by justifying and optimizing PET/CT examinations and ensure an acceptable image quality. Establishing diagnostic reference levels (DRLs) is a crucial quantitative indicator and effective tool to optimize paediatric imaging procedures. This review aimed to distinguish and acknowledge variations among published DRLs for paediatric patients in PET/CT procedures. A search of relevant articles was conducted using databases, that is, Embase, Scopus, Web of Science, and Medline, using the keywords: PET-computed tomography, computed tomography, PET, radiopharmaceutical, DRL, and their synonyms. Only English and full-text articles were included, with no limitations on the publication year. After the screening, four articles were selected, and the review reveals different DRL approaches for paediatric patients undergoing PET/CT, with primary variations observed in patient selection criteria, reporting of radiation dose values, and PET/CT equipment. The study suggests that future DRL methods for paediatric patients should prioritize data collection in accordance with international guidelines to better understand PET/CT dose discrepancies while also striving to optimize radiation doses without compromising the quality of PET/CT images.

Reproducibility and Repeatability of Coronary Computed Tomography Angiography (CCTA) Image Segmentation in Detecting Atherosclerosis: A Radiomics Study

Atherosclerosis is known as the leading factor in heart disease with the highest mortality rate among the Malaysian population. Usually, the gold standard for diagnosing atherosclerosis is by using the coronary computed tomography angiography (CCTA) technique to look for plaque within the coronary artery. However, qualitative diagnosis for noncalcified atherosclerosis is vulnerable to false-positive diagnoses, as well as inconsistent reporting between observers. In this study, we assess the reproducibility and repeatability of segmenting atherosclerotic lesions manually and semiautomatically in CCTA images to identify the most appropriate CCTA image segmentation method for radiomics analysis to quantitatively extract the atherosclerotic lesion. Thirty (30) CCTA images were taken retrospectively from the radiology image database of Hospital Canselor Tuanku Muhriz (HCTM), Kuala Lumpur, Malaysia. We extract 11,700 radiomics features which include the first-order, second-order and shape features from 180 times of image segmentation. The interest vessels were segmentized manually and semiautomatically using LIFEx (Version 7.0.15, Institut Curie, Orsay, France) software by two independent radiology experts, focusing on three main coronary blood vessels. As a result, manual segmentation with a soft-tissuewindowing setting yielded higher repeatability as compared to semiautomatic segmentation with a significant intraclass correlation coefficient (intra-CC) 0.961 for thefirst-order and shape features; intra-CC of 0.924 for thesecond-order features with p < 0.001. Meanwhile, the semiautomatic segmentation has higher reproducibility as compared to manual segmentation with significant interclass correlation coefficient (inter-CC) of 0.920 (first-order features) and a good interclass correlation coefficient of 0.839 for the second-order features with p < 0.001. The first-order, shape order and second-order features for both manual and semiautomatic segmentation have an excellent percentage of reproducibility and repeatability (intra-CC > 0.9). In conclusion, semi-automated segmentation is recommended for inter-observer study while manual segmentation with soft tissue-windowing can be used for single observer study.

Mechanical and Imaging Properties of a Clinical-Grade Kidney Phantom Based on Polydimethylsiloxane and Elastomer

Medical imaging phantoms are considered critical in mimicking the properties of human tissue for calibration, training, surgical planning, and simulation purposes. Hence, the stability and accuracy of the imaging phantom play a significant role in diagnostic imaging. This study aimed to evaluate the influence of hydrogen silicone (HS) and water (H₂O) on the compression strength, radiation attenuation properties, and computed tomography (CT) number of the blended Polydimethylsiloxane (PDMS) samples, and to verify the best material to simulate kidney tissue. Four samples with different compositions were studied, including samples S1, S2, S3, and S4, which consisted of PDMS 100%, HS/PDMS 20:80, H₂O/PDMS 20:80, and HS/H₂O/PDMS 20:40:40, respectively. The stability of the samples was assessed using compression testing, and the attenuation properties of sample S2 were evaluated. The effective atomic number of S2 showed a similar pattern to the human kidney tissue at 1.50 × 10⁻¹ to 1 MeV. With the use of a 120 kVp X-ray beam, the CT number quantified for S2, as well measured 40 HU, and had the highest contrast-to-noise ratio (CNR) value. Therefore, the S2 sample formulation exhibited the potential to mimic the human kidney, as it has a similar dynamic and is higher in terms of stability as a medical phantom.