Lung density in the trajectory path — a strong indicator of patients sustaining a pneumothorax during CT-guided lung biopsy

Introduction: The purpose is to evaluate the prognostic significance of lung parenchymal density during percutaneous coaxial cutting needle lung biopsy (PNLB). Materials and methods: Retrospective analysis of 179 consecutive patients (106 males, 73 females; mean age 59.16 ± 16.34 years) undergoing PNLB was included. Mean lobar parenchymal lung density, mean densities anterior to the lesion and posterior to the chest wall in the needle trajectory path were measured in HU. Lesion location and needle trajectory were also measured. Fisher’s exact test and Chi-square test were conducted to analyze the categorical variables. ANOVA test was done to examine continuous and normally distributed variables. Statistical significance was considered when p < 0.05. Results: Mean lobar parenchymal lung density (p < 0.05) and mean parenchymal lung density relative to the needle trajectory path were below -800 HU in patients who sustained a pneumothorax. Increase in the number of pleural passes was significantly associated with the risk of patients having pneumothorax (p < 0.05). The mean distance from the skin to the lesion and needle trajectory angle were not statistically different among patients with and without pneumothorax (p > 0.05). Conclusion: Lobar parenchymal density and lung parenchymal density anterior to the lesion and posterior to the chest wall in the needle trajectory path could be used as predicting parameters in patients undergoing PNLB who sustained a pneumothorax. These findings can help interventional radiologist further assess risk of pneumothorax when preforming such procedure

Contrast media volume is significantly related to patient lung volume during CT pulmonary angiography when employing a patient-specific contrast protocol

Aim: The purpose of this study is to investigate the relationship between contrast media volume and patient lung volume when employing a patient-specific contrast media formula during pulmonary computed tomography angiography (CTA). Materials and methods: IRB approved this retrospective study. CTA of the pulmonary arteries was performed on 200 patients with suspected pulmonary embolism (PE). The contrast media volume (CMV) was calculted by employing a patient-specific contrast formula. Lung volume was quantified employing semi-automated lung software that calculated lung volumes (intellispace -Philips). The mean cross-sectional opacification profile of central and peripheral pulmonary arteries and veins were measured for each patient and arteriovenous contrast ratio (AVCR) calculated for each lung segment.  Mean body mass index (BMI) and lung volume were quantified. Receiver operating (ROC) and visual grading characteristics (VGC) measured reader confidence in emboli detection and image quality respectively. Inter and intra-observer variations were investigated employing Cohen’s kappa methodology. Results: Results showed that the mean pulmonary arterial opacification of the main pulmonary circulation (343.88±73HU), right lung; upper (316.51±23HU), middle (312.5±39HU) and lower (315.23±65HU) lobes and left; upper (318.76±83HU), and lower (321.91±12HU) lobes. The mean venous opacification of all pulmonary veins was below 182±72HU. AVCR was observed at all anatomic locations (p<0.0002) where this ratio was calculated. Moreover, larger volumes of contrast significantly correlated with larger lung volumes (r=0.89, p<0.03) and radiation dose (p<0.03). VGC and ROC analysis demonstrated increased area under the curve: 0.831 and 0.99 respectively (p<0.02). Inter-observer variation was observed as excellent (κ = 0.71). Conclusion: We conclude that increased CMV is significantly correlated to increased patient lung volume and radiation dose when employing a patient-specific contrast formula. The effects patient habitus is highlighted

Contrast medium administration and image acquisition parameters in renal CT angiography: what radiologists need to know

Over the last decade, exponential advances in computed tomography (CT) technology have resulted in improved spatial and temporal resolution. Faster image acquisition enabled renal CT angiography to become a viable and effective noninvasive alternative in diagnosing renal vascular pathologies. However, with these advances, new challenges in contrast media administration have emerged. Poor synchronization between scanner and contrast media administration have reduced the consistency in image quality with poor spatial and contrast resolution. Comprehensive understanding of contrast media dynamics is essential in the design and implementation of contrast administration and image acquisition protocols. This review includes an overview of the parameters affecting renal artery opacification and current protocol strategies to achieve optimal image quality during renal CT angiography with iodinated contrast media, with current safety issues highlighted

Referral Physicians’ Knowledge of Radiation Dose: A Cross-sectional Study

AIM: The purpose of the study was to evaluate the knowledge of referring physicians of general practitioners, residents, and medical specialists in Jordan and the Middle East on radiation dose and its impact on vulnerable patients. MATERIALS AND METHODS: The Institutional Review Board approved this study before data collection. A cross-sectional study employed questionnaire that was distributed to respondents (n = 293) of general practitioners, residents, specialists, and therapists. The questionnaire consisted of 29 questions. Nine questions concerned with demographics and the remaining 20 questions were divided into five sections: Radiation dose, ionizing radiation, pediatric radiation, pregnant women radiation, and radiation risks. The mean score was computed out of 20. Chi-squared test of independence was utilized to analyze each question. To compare the responses between the demographic variables groups, Kruskal–Wallis and Mann–Whitney tests were used. RESULTS: Out of the 293 respondents, 128 (43.7%) were aware of radiation. The average score of the questionnaire was 9.5 out of 20 (47.5%). Within each section, the level of knowledge varied. Physicians had the highest level of knowledge in radiation risk (85.7%) followed by ionizing radiation (62.1%). The questionnaire revealed lower levels of knowledge in the areas of pediatric radiation, pregnant women radiation, and radiation dose. The percentages of respondents, (with fair to good level of knowledge), were 47.1%, 34.5%, and 24.6%, respectively. CONCLUSION: The results of this study were consistent with previous studies that demonstrated a poor level of general knowledge in referring physicians regarding radiation dose, ionizing radiation, pediatric radiation, pregnant women radiation, and radiation risks

Establishment of diagnostic reference levels in cardiac computed tomography

The aim of this study was to determine diagnostic reference levels (DRLs) for cardiac computed tomography (CCT) in Jordan. Volume computed tomography dose index (CTDIvol) and dose–length product (DLP) were collected from 228 CCTs performed at seven Jordanian hospitals specialized in cardiac CT. DRLs for cardiac CT were defined at the 75th percentile of CTDIvol and DLP. CTDIvol and DLP were collected from 30 successive cardiac CT in each center except for one center (18 scans). The 75th percentile of the CTDIvol and the DLP of the centers calculated from mixed retrospective and prospective gated modes were 47.74 milligray (mGy) and 1035 mGy/cm, respectively. This study demonstrated wide dose variations among the surveyed hospitals for cardiac CT scans; there was a 5.1-fold difference between the highest and lowest median DLP with a range of 223.2–1146.7 mGy/cm. Differences were associated with variations in the mAs and kVp. This study confirmed large variability in CTDIvol and DLP for cardiac CT scans; variation was associated with acquisition protocols and highlights the need for dose optimization. DRLs are proposed for CCT; there remains substantial potential for optimization of cardiac CT examinations for adults in Jordan

An optimised patient-specific contrast formula based on cardiovascular dynamics improves vascular visualisation during computed tomography angiography

Purpose The purpose of this thesis is to improve arterial opacification during computed tomography angiography (CTA) of the head and neck, thoracic and pulmonary vasculature by employing a novel patient-specific contrast regimen for each anatomic region. Methods CTA of the head and neck, thoracic and pulmonary vasculature was performed on 720 patients with suspected vascular pathology using a 64 channel computed tomography scanner and a dual barrel contrast injector. Patients were randomly assigned into two equal protocol groups: regimen A, the department’s conventional protocol, employed a fixed contrast volume, intravenously injected at a flow rate of 4.5 mL/s; regimen B involved the use of a patient-specific contrast formula based on measured patient cardiovascular dynamics. Each study calculated the mean cross-sectional opacification profile of the arteries and veins in their anatomical region and an arteriovenous contrast ratio (AVCR) and Mann-Whitney U non-parametric statistics were used to compare regimens. The diagnostic efficacy in head and neck CTA and thoracic CTA (non-gated and gated ECG technique) was assessed by receiver operating characteristic (ROC) analysis using Dorfman-Berbaum-Metz methodology, whilst the thoracic CTA additionally measured visual grading characteristic (VGC) . Pulmonary CTA comparisons employed jackknife alternative free-response receiver operating characteristic (JAFROC) methodology. Inter-observer variations were investigated using Kappa methods. Results Mean arterial opacification in all anatomical locations were up to 58% higher (p <0.001) following regimen B compared with A. In the venous system, attenuation was significantly lower in regimen B than in regimen A with a maximum reduction of up to 93% (p <0.0001). There were significant (p <0.0001) improvements in AVCR at each anatomical level by up to 93%. ROC area under the curve (Az), JAFROC figure of merit (FOM) and VGC scores and the interobserver variability were significantly higher in regimen B compared to A (p<0.002, p<0.0002 and p<0.02, p<0.004) respectively. The contrast volume in regimen B was significantly lower compared to A by up to 67 % (p<0.001). Conclusion Novel individualised acquisition/contrast regimen significantly improves visualisation of head and neck, thoracic and pulmonary arterial vasculature, whilst reducing contrast volume and the potential risks of contrast induced nephrotoxicity during CTA

A progressive and cross-domain deep transfer learning framework for wrist fracture detection

There has been an amplified focus on and benefit from the adoption of artificial intelligence (AI) in medical imaging applications. However, deep learning approaches involve training with massive amounts of annotated data in order to guarantee generalization and achieve high accuracies. Gathering and annotating large sets of training images require expertise which is both expensive and time-consuming, especially in the medical field. Furthermore, in health care systems where mistakes can have catastrophic consequences, there is a general mistrust in the black-box aspect of AI models. In this work, we focus on improving the performance of medical imaging applications when limited data is available while focusing on the interpretability aspect of the proposed AI model. This is achieved by employing a novel transfer learning framework, progressive transfer learning, an automated annotation technique and a correlation analysis experiment on the learned representations. Progressive transfer learning helps jump-start the training of deep neural networks while improving the performance by gradually transferring knowledge from two source tasks into the target task. It is empirically tested on the wrist fracture detection application by first training a general radiology network RadiNet and using its weights to initialize RadiNetwrist, that is trained on wrist images to detect fractures. Experiments show that RadiNetwrist achieves an accuracy of 87% and an AUC ROC of 94% as opposed to 83% and 92% when it is pre-trained on the ImageNet dataset. This improvement in performance is investigated within an explainable AI framework. More concretely, the learned deep representations of RadiNetwrist are compared to those learned by the baseline model by conducting a correlation analysis experiment. The results show that, when transfer learning is gradually applied, some features are learned earlier in the network. Moreover, the deep layers in the progressive transfer learning framework are shown to encode features that are not encountered when traditional transfer learning techniques are applied. In addition to the empirical results, a clinical study is conducted and the performance of RadiNetwrist is compared to that of an expert radiologist. We found that RadiNetwrist exhibited similar performance to that of radiologists with more than 20 years of experience. This motivates follow-up research to train on more data to feasibly surpass radiologists’ performance, and investigate the interpretability of AI models in the healthcare domain where the decision-making process needs to be credible and transparent

Diagnostic reference levels for paediatric CT in Jordan

This study aimed to investigate the current status of Diagnostic Reference Levels (DRL) in paediatric CT across Jordan. The dose data for four main CT examinations (brain, chest, abdominopelvic, and Chest, Abdomen and Pelvis (CAP)) in hospitals and imaging centres (n = 4) were measured. The volume CT dose index (CTDIvol) and Dose Length Product (DLP) values were compared within the different hospitals and age groups (&amp;lt;1 year, 1-4 years, 5-10 years and 11-18 years). DRL in Jordan were compared to international DRLs. The paediatric population consisted of 1,818 children; 61.4% of them were male. There were significant variations between the DRLs for each CT scanner with an up to four-fold difference in dose between hospitals. There were apparent significant differences between Jordan and other countries with the DLPs in Jordan being relatively high. However, for CTDIvol, the values in Jordan were close to those of other countries. This study confirmed variations in the CTDIvol and DLP values of paediatric CT scans in Jordan. These variations were attributed to the different protocols and equipment used. There is a need to optimise paediatric CT examinations doses in Jordan

A new approach to dose reference levels in pediatric CT: Age and size-specific dose estimation

Background: Although paediatrics' are more radio-sensitivity than adults, the number of requested paediatric CT examinations is increasing globally. Significant efforts have been focused on achieving the lowest possible radiation dose for paediatric patients, particularly adjusting for size differences. This study aims to establish Diagnostic Reference Levels (DRLs) for paediatric patients based on size-specific dose estimates (SSDE). Method: In this retrospective national study, CT scans for brain, chest, abdominopelvic, and chest, abdomen, and pelvis (CAP) were collected from four hospitals in Jordan undergoing paediatric CT scans. A total of 1818 cases were randomly selected in four age categories (<1 year, 1–4 years, 5–10 years, 11–18 years). The SSDE values were determined by multiplying the volume CT dose index (CTDIvol) with the conversion factor extracted from the American Association of Physicists in Medicine Report 204. Results: Variations exist between the DRLs between the different hospitals, age groups, and variations in protocols with different types of CT scanners. The DRL values (CTDIvol, dose-length product (DLP) and SSDE) for the four age categories were as follows; <1 year: brain (47.88 mGy, 741.67 mGy cm and 58.40 mGy), chest (5.65 mGy, 124 mGy cm and 13.91 mGy), abdominopelvic (12.65 mGy, 321.5 mGy cm and 28.72 mGy) and CAP (16.12 mGy, 507.72 mGy cm and 38.04 mGy). 1–4 years, brain (54.79 mGy, 979.12 mGy cm and 55.88 mGy), chest (7.37 mGy, 220.85 mGy cm and 14.68 mGy), abdominopelvic (16.16 mGy, 424.72 mGy cm and 32.68 mGy) and CAP (16.13 mGy, 742.1 mGy cm and 33.54 mGy). 5–10 years: brain (65.03 mGy, 1129.94 mGy cm and 55.92 mGy), chest (12.57 mGy, 383.9 mGy cm and 22.45 mGy), abdominopelvic (12.34 mGy, 450.75 mGy cm and 22.23 mGy) and CAP (13.46 mGy, 748.85 mGy cm and 25.69 mGy). 11–18 years, brain (60.7 mGy, 1207.9 mGy cm and 41.81 mGy), chest examination (12.94 mGy, 496.2 mGy cm and 20.49 mGy), abdominopelvic (16.13 mGy, 803.07 mGy cm and 23.06 mGy) and CAP (16.13 mGy, 1101.5 mGy cm and 23.85 mGy). Conclusion: There were increases in CTDIvol, DLP, and SSDE with ascending age groups. SSDE and age are closely matched to delivered radiation in paediatric CT; however, radiation dose levels remain high in Jordan. This work highlights the need for caution when administering radiation in the paediatric population