Dual fluid silhouette in X-ray of the abdomen: a diagnostic flag for neurogenic bladder with urinary ascites.

A neonate presented with abdominal distension and decreased urinary output. X-ray revealed dual abdominal fluid condition-ascites with a distended bladder, along with vertebral anomalies. The possibility of urinary ascites and neurogenic bladder was kept, which was further confirmed on evaluation. Here, we emphasise the crucial role of abdominal X-ray as a diagnostic tool in uncovering this intricate medical puzzle. By detailing the clinical presentation, diagnostic approach and treatment strategy, the report contributes insights into the rare and complex abdominal condition.

Optimizing CT Abdomen-Pelvis Scan Radiation Dose: Examining the Role of Body Metrics (Waist Circumference, Hip Circumference, Abdominal Fat, and Body Mass Index) in Dose Efficiency.

Objective: This study investigates the correlation between patient body metrics and radiation dose in abdominopelvic CT scans, aiming to identify significant predictors of radiation exposure. Methods: Employing a cross-sectional analysis of patient data, including BMI, abdominal fat, waist, abdomen, and hip circumference, we analyzed their relationship with the following dose metrics: the CTDIvol, DLP, and SSDE. Results: Results from the analysis of various body measurements revealed that BMI, abdominal fat, and waist circumference are strongly correlated with increased radiation doses. Notably, the SSDE, as a more patient-centric dose metric, showed significant positive correlations, especially with waist circumference, suggesting its potential as a key predictor for optimizing radiation doses. Conclusions: The findings suggest that incorporating patient-specific body metrics into CT dosimetry could enhance personalized care and radiation safety. Conclusively, this study highlights the necessity for tailored imaging protocols based on individual body metrics to optimize radiation exposure, encouraging further research into predictive models and the integration of these metrics into clinical practice for improved patient management.

Optimization of smoothing parameter for block matching and 3D filtering algorithm in low-dose chest and abdominal computed tomography images.

Computed tomography (CT), known for its exceptionally high accuracy, is associated with a substantial dose of ionizing radiation. Low-dose protocols have been devised to address this issue; however, a reduction in the radiation dose can lead to a deficiency in the number of photons, resulting in quantum noise. Thus, the aim of this study was to optimize the smoothing parameter (σ-value) of the block matching and 3D filtering (BM3D) algorithm to effectively reduce noise in low-dose chest and abdominal CT images. Acquired images were subsequently analyze using quantitative evaluation metrics, including contrast to noise ratio (CNR), coefficient of variation (CV), and naturalness image quality evaluator (NIQE). Quantitative evaluation results demonstrated that the optimal σ-value for CNR, CV, and NIQE were 0.10, 0.11, and 0.09 in low-dose chest CT images respectively, whereas those in abdominal images were 0.12, 0.11, and 0.09, respectively. The average of the optimal σ-values, which produced the most improved results, was 0.10, considering both visual and quantitative evaluations. In conclusion, we demonstrated that the optimized BM3D algorithm with σ-value is effective for noise reduction in low-dose chest and abdominal CT images indicating its feasibility of in the clinical field.

Active learning using adaptable task-based prioritisation.

Supervised machine learning-based medical image computing applications necessitate expert label curation, while unlabelled image data might be relatively abundant. Active learning methods aim to prioritise a subset of available image data for expert annotation, for label-efficient model training. We develop a controller neural network that measures priority of images in a sequence of batches, as in batch-mode active learning, for multi-class segmentation tasks. The controller is optimised by rewarding positive task-specific performance gain, within a Markov decision process (MDP) environment that also optimises the task predictor. In this work, the task predictor is a segmentation network. A meta-reinforcement learning algorithm is proposed with multiple MDPs, such that the pre-trained controller can be adapted to a new MDP that contains data from different institutes and/or requires segmentation of different organs or structures within the abdomen. We present experimental results using multiple CT datasets from more than one thousand patients, with segmentation tasks of nine different abdominal organs, to demonstrate the efficacy of the learnt prioritisation controller function and its cross-institute and cross-organ adaptability. We show that the proposed adaptable prioritisation metric yields converging segmentation accuracy for a new kidney segmentation task, unseen in training, using between approximately 40% to 60% of labels otherwise required with other heuristic or random prioritisation metrics. For clinical datasets of limited size, the proposed adaptable prioritisation offers a performance improvement of 22.6% and 10.2% in Dice score, for tasks of kidney and liver vessel segmentation, respectively, compared to random prioritisation and alternative active sampling strategies.

Fully automated explainable abdominal CT contrast media phase classification using organ segmentation and machine learning.

BACKGROUND: Contrast-enhanced computed tomography (CECT) provides much more information compared to non-enhanced CT images, especially for the differentiation of malignancies, such as liver carcinomas. Contrast media injection phase information is usually missing on public datasets and not standardized in the clinic even in the same region and language. This is a barrier to effective use of available CECT images in clinical research. PURPOSE: The aim of this study is to detect contrast media injection phase from CT images by means of organ segmentation and machine learning algorithms. METHODS: A total number of 2509 CT images split into four subsets of non-contrast (class #0), arterial (class #1), venous (class #2), and delayed (class #3) after contrast media injection were collected from two CT scanners. Seven organs including the liver, spleen, heart, kidneys, lungs, urinary bladder, and aorta along with body contour masks were generated by pre-trained deep learning algorithms. Subsequently, five first-order statistical features including average, standard deviation, 10, 50, and 90 percentiles extracted from the above-mentioned masks were fed to machine learning models after feature selection and reduction to classify the CT images in one of four above mentioned classes. A 10-fold data split strategy was followed. The performance of our methodology was evaluated in terms of classification accuracy metrics. RESULTS: The best performance was achieved by Boruta feature selection and RF model with average area under the curve of more than 0.999 and accuracy of 0.9936 averaged over four classes and 10 folds. Boruta feature selection selected all predictor features. The lowest classification was observed for class #2 (0.9888), which is already an excellent result. In the 10-fold strategy, only 33 cases from 2509 cases (∼1.4%) were misclassified. The performance over all folds was consistent. CONCLUSIONS: We developed a fast, accurate, reliable, and explainable methodology to classify contrast media phases which may be useful in data curation and annotation in big online datasets or local datasets with non-standard or no series description. Our model containing two steps of deep learning and machine learning may help to exploit available datasets more effectively.

An investigation into augmentation and preprocessing for optimising X-ray classification in limited datasets: a case study on necrotising enterocolitis.

PURPOSE: Obtaining large volumes of medical images, required for deep learning development, can be challenging in rare pathologies. Image augmentation and preprocessing offer viable solutions. This work explores the case of necrotising enterocolitis (NEC), a rare but life-threatening condition affecting premature neonates, with challenging radiological diagnosis. We investigate data augmentation and preprocessing techniques and propose two optimised pipelines for developing reliable computer-aided diagnosis models on a limited NEC dataset. METHODS: We present a NEC dataset of 1090 Abdominal X-rays (AXRs) from 364 patients and investigate the effect of geometric augmentations, colour scheme augmentations and their combination for NEC classification based on the ResNet-50 backbone. We introduce two pipelines based on colour contrast and edge enhancement, to increase the visibility of subtle, difficult-to-identify, critical NEC findings on AXRs and achieve robust accuracy in a challenging three-class NEC classification task. RESULTS: Our results show that geometric augmentations improve performance, with Translation achieving +6.2%, while Flipping and Occlusion decrease performance. Colour augmentations, like Equalisation, yield modest improvements. The proposed Pr-1 and Pr-2 pipelines enhance model accuracy by +2.4% and +1.7%, respectively. Combining Pr-1/Pr-2 with geometric augmentation, we achieve a maximum performance increase of 7.1%, achieving robust NEC classification. CONCLUSION: Based on an extensive validation of preprocessing and augmentation techniques, our work showcases the previously unreported potential of image preprocessing in AXR classification tasks with limited datasets. Our findings can be extended to other medical tasks for designing reliable classifier models with limited X-ray datasets. Ultimately, we also provide a benchmark for automated NEC detection and classification from AXRs.

CNN application for automated determination of the patient's size to obtain the size-specific dose estimated in CT.

Introduction. The currently available dosimetry techniques in computed tomography can be inaccurate which overestimate the absorbed dose. Therefore, we aimed to provide an automated and fast methodology to more accurately calculate the SSDE usingDwobtained by using CNN from thorax and abdominal CT study images.Methods. The SSDE was determined from the 200 records files. For that purpose, patients' size was measured in two ways: (a) by developing an algorithm following the AAPM Report No. 204 methodology; and (b) using a CNN according to AAPM Report No. 220.Results. The patient's size measured by the in-house software in the region of thorax and abdomen was 27.63 ± 3.23 cm and 28.66 ± 3.37 cm, while CNN was 18.90 ± 2.6 cm and 21.77 ± 2.45 cm. The SSDE in thorax according to 204 and 220 reports were 17.26 ± 2.81 mGy and 23.70 ± 2.96 mGy for women and 17.08 ± 2.09 mGy and 23.47 ± 2.34 mGy for men. In abdomen was 18.54 ± 2.25 mGy and 23.40 ± 1.88 mGy in women and 18.37 ± 2.31 mGy and 23.84 ± 2.36 mGy in men.Conclusions. Implementing CNN-based automated methodologies can contribute to fast and accurate dose calculations, thereby improving patient-specific radiation safety in clinical practice.

Robustness of radiomic features in healthy abdominal parenchyma of patients with repeated examinations on dual-layer dual-energy CT.

OBJECTIVES: Robustness of radiomic features in physiological tissue is an important prerequisite for quantitative analysis of tumor biology and response assessment. In contrast to previous studies which focused on different tumors with mostly short scan-re-scan intervals, this study aimed to evaluate the robustness of radiomic features in cancer-free patients and over a clinically encountered inter-scan interval. MATERIALS AND METHODS: Patients without visible tumor burden who underwent at least two portal-venous phase dual energy CT examinations of the abdomen between May 2016 and January 2020 were included, while macroscopic tumor burden was excluded based upon follow-up imaging for all patients (≥3 months). Further, patients were excluded if no follow-up imaging was available, or if the CT protocol showed deviations between repeated examinations. Circular regions of interest were placed and proofread by two board-certified radiologists (4 years and 5 years experience) within the liver (segments 3 and 6), the psoas muscle (left and right), the pancreatic head, and the spleen to obtain radiomic features from normal-appearing organ parenchyma using PyRadiomics. Radiomic feature robustness was tested using the concordance correlation coefficient with a threshold of 0.75 considered indicative for deeming a feature robust. RESULTS: In total, 160 patients with 480 repeated abdominal CT examinations (range: 2-4 per patient) were retrospectively included in this single-center, IRB-approved study. Considering all organs and feature categories, only 4.58 % (25/546) of all features were robust with the highest rate being found in the first order feature category (20.37 %, 22/108). Other feature categories (grey level co-occurrence matrix, grey level dependence matrix, grey level run length matrix, grey level size zone matrix, and neighborhood gray-tone difference matrix) yielded an overall low percentage of robust features (range: 0.00 %-1.19 %). A subgroup analysis revealed the reconstructed field of view and the X-ray tube current as determinants of feature robustness (significant differences in subgroups for all organs, p < 0.001) as well as the size of the region of interest (no significant difference for the pancreatic head with p = 0.135, significant difference with p < 0.001 for all other organs). CONCLUSION: Radiomic feature robustness obtained from cancer-free subjects with repeated examinations using a consistent protocol and CT scanner was limited, with first order features yielding the highest proportion of robust features.

Protocol optimization for abdominal imaging using photon-counting CT: a consensus of two academic institutions.

PURPOSE: Photon-counting detector CT (PCD CT) is a promising technology for abdominal imaging due to its ability to provide high spatial and contrast resolution images with reduced patient radiation exposure. However, there is currently no consensus regarding the optimal imaging protocols for PCD CT. This article aims to present the PCD CT abdominal imaging protocols used by two tertiary care academic centers in the United States. METHODS: A review of PCD CT abdominal imaging protocols was conducted by two abdominal radiologists at different academic institutions. Protocols were compared in terms of acquisition parameters and reconstruction settings. Both imaging centers independently selected similar protocols for PCD CT abdominal imaging, using QuantumPlus mode. RESULTS: There were some differences in the use of reconstruction kernels and iterative reconstruction levels, however the individual combination at each site resulted in similar image impressions. Overall, the imaging protocols used by both centers provide high-quality images with low radiation exposure. CONCLUSION: These findings provide valuable insights into the development of standardized protocols for PCD CT abdominal imaging, which can help to ensure consistent as well as high-quality imaging across different institutions and allow for future multicenter research collaborations.

Introducing fitting models for estimating age-specific dose and effective dose in paediatric patients undergoing head, chest and abdomen-pelvis imaging protocols: a patient study.

INTRODUCTION: Concerns regarding the adverse consequences of radiation have increased due to the expanded application of computed tomography (CT) in medical practice. Certain studies have indicated that the radiation dosage depends on the anatomical region, the imaging technique employed and patient-specific variables. The aim of this study is to present fitting models for the estimation of age-specific dose estimates (ASDE), in the same direction of size-specific dose estimates, and effective doses based on patient age, gender and the type of CT examination used in paediatric head, chest and abdomen-pelvis imaging. METHODS: A total of 583 paediatric patients were included in the study. Radiometric data were gathered from DICOM files. The patients were categorised into five distinct groups (under 15 years of age), and the effective dose, organ dose and ASDE were computed for the CT examinations involving the head, chest and abdomen-pelvis. Finally, the best fitting models were presented for estimation of ASDE and effective doses based on patient age, gender and the type of examination. RESULTS: The ASDE in head, chest, and abdomen-pelvis CT examinations increases with increasing age. As age increases, the effective dose in head and abdomen-pelvis CT scans decreased. However, for chest scans, the effective dose initially showed a decreasing trend until the first year of life; after that, it increases in correlation with age. CONCLUSIONS: Based on the presented fitting model for the ASDE, these CT scan quantities depend on factors such as patient age and the type of CT examination. For the effective dose, the gender was also included in the fitting model. By utilising the information about the scan type, region and age, it becomes feasible to estimate the ASDE and effective dose using the models provided in this study.

A Novel Integrated Clinical-Biochemical-Radiological and Sonographic Classification of Necrotizing Enterocolitis.

OBJECTIVE: To evaluate the sensitivity and specificity of clinical, laboratory, and radiological markers and the neonatologist-performed intestinal ultrasound (NP-IUS) for treatment interventions in preterm neonates who developed necrotizing enterocolitis (NEC). STUDY DESIGN: This was a case-control study of preterm neonates < 35 weeks with a diagnostic workup for NEC. The diagnostic workup included NP-IUS performed by trained neonatologists using a standard protocol, abdominal roentgenogram (AXR), and laboratory investigations. Intestinal ultrasound (IUS) performed by two neonatologists was standardized to detect 11 injury markers. AXRs were read independently by experienced pediatric radiologists. The investigators who retrospectively interpreted the IUS were blinded to the clinical and treatment outcomes. RESULTS: A total of 111 neonates were assessed. Fifty-four did not require intervention and formed the control group. Twenty cases were treated medically, 21 cases were treated with late surgery for stricture or adhesions, and 16 were treated with early surgery. The integrated model of cumulative severity of ultrasound markers, respiratory and hemodynamic instability, abdominal wall cellulitis, and C- reactive protein > 16 mg/L had an area under the curve (AUC) of 0.89 (95% confidence interval [CI]: 0.83-0.94%, p < 0.0001) for diagnosing NEC requiring surgical intervention. We also investigated the utility of Bell's classification to diagnose either the need for surgery or death, and it had an AUC of 0.74 (95% CI: 0.65-0.83%, p < 0.0001). CONCLUSION: In this cohort, a combination of specific IUS markers and clinical signs of instability, abdominal wall cellulitis, plus laboratory markers were diagnostic of NEC requiring interventions. KEY POINTS: · The diagnosis of necrotizing enterocolitis requires a combination of markers.. · The combination of specific ultrasound markers, clinical signs, and laboratory markers were diagnostic of NEC requiring intervention.. · The intestinal ultrasound performed by a trained neonatologist was the most sensitive diagnostic marker of NEC requiring surgical intervention..

Comparative study of abdominal CT enhancement in overweight and obese patients based on different scanning modes combined with different contrast medium concentrations.

PURPOSE: To compare image quality, iodine intake, and radiation dose in overweight and obese patients undergoing abdominal computed tomography (CT) enhancement using different scanning modes and contrast medium. METHODS: Ninety overweight and obese patients (25 kg/m2≤body mass index (BMI)< 30 kg/m2 and BMI≥30 kg/m2) who underwent abdominal CT-enhanced examinations were randomized into three groups (A, B, and C) of 30 each and scanned using gemstone spectral imaging (GSI) +320 mgI/ml, 100 kVp + 370 mgI/ml, and 120 kVp + 370 mgI/ml, respectively. Reconstruct monochromatic energy images of group A at 50-70 keV (5 keV interval). The iodine intake and radiation dose of each group were recorded and calculated. The CT values, contrast-to-noise ratios (CNRs), and subjective scores of each subgroup image in group A versus images in groups B and C were by using one-way analysis of variance or Kruskal-Wallis H test, and the optimal keV of group A was selected. RESULTS: The dual-phase CT values and CNRs of each part in group A were higher than or similar to those in groups B and C at 50-60 keV, and similar to or lower than those in groups B and C at 65 keV and 70 keV. The subjective scores of the dual-phase images in group A were lower than those of groups B and C at 50 keV and 55 keV, whereas no significant difference was seen at 60-70 keV. Compared to groups B and C, the iodine intake in group A decreased by 12.5% and 13.3%, respectively. The effective doses in groups A and B were 24.7% and 25.8% lower than those in group C, respectively. CONCLUSION: GSI +320 mgI/ml for abdominal CT-enhanced in overweight patients satisfies image quality while reducing iodine intake and radiation dose, and the optimal keV was 60 keV.

Yield of abdominal radiographs in children with suspected intussusception; rate of pneumoperitoneum and other abdominal pathology.

OBJECTIVES: Ultrasound is the criterion standard imaging modality for the diagnosis of intussusception. However, to our knowledge the utility of abdominal radiographs to concurrently screen for pneumoperitoneum or other abdominal pathology that could have a similar presentation has not been studied. Our institutional protocol requires the performance of AP supine and left lateral decubitus views of the abdomen prior to ultrasound evaluation for intussusception, providing an opportunity to examine the yield of abdominal radiographs in this setting. Our primary objective was to determine the rate of pneumoperitoneum on screening abdominal radiographs in children undergoing evaluation for intussusception. Our secondary objective was to determine the rate that other clinically significant pathology is found on these screening abdominal radiographs. METHODS: We performed a retrospective chart review of all patients under 6 years of age who had any imaging ordered in our large urban pediatric emergency department to evaluate for suspected intussusception during the calendar years 2018-2020. RESULTS: 1115 patient encounters met our inclusion criteria. Among 1090 who had screening abdominal radiographs, 82 (8%) had findings concerning for intussusception. Of those not concerning for intussusception, 635 (58%) were read as normal, 263 (24%) showed moderate to large stool burden, 107 (10%) showed generalized bowel distention, and 22 (2%) showed abnormal gastric distention. Individually the remainder of all other findings compromised <1% of encounters and included radiopaque foreign body (8), intraabdominal calcification (4), pneumonia/effusion (3), pneumatosis intestinalis, abdominal mass (2), diaphragmatic hernia (1), rib fracture (1), appendicolith (1), feeding tube malposition (1), and bowel wall thickening (1). In one encounter the patient had a bowel perforation with pneumoperitoneum present secondary to ingestion of multiple magnets. CONCLUSIONS: Our study indicates that radiograph-detected pneumoperitoneum is rare in children with suspected intussusception. Constipation is the most common abnormal finding on screening radiographs. Other findings occur in approximately 15% of total cases, some of which require further workup.

Pretreatment Interstitial Lung Abnormalities Detected on Abdominal Computed Tomography Scans in Prostate Cancer Patients.

OBJECTIVE: Prostate cancer and interstitial lung abnormality (ILA) share similar risk factor, which is men and older age. The purpose of this study was to investigate the prevalence of pretreatment ILA among prostate cancer patients who underwent abdominal computed tomography (CT) within 1 year at their first visit to the urology department. In addition, we aimed to assess the association between pretreatment ILA and long-term survival in prostate cancer patients. METHODS: This study was conducted in patients who had a first visit for prostate cancer at urology department between 2005 and 2016 and underwent an abdominal CT within 1 year. A thoracic radiologist evaluated the presence of ILA through inspecting the lung base scanned on an abdominal CT. The association between pretreatment ILA and survival was assessed using Kaplan-Meier analysis with log-rank test. Specific survival rates at 12, 36, and 60 months according to the presence of ILA were evaluated using z -test. Cox regression analysis was used to assess the risk factors of mortality. RESULTS: A total of 173 patients were included (mean age, 70.23 ± 7.98 years). Pretreatment ILA was observed in 10.4% of patients. Patients with ILA were more likely to be older and current smokers. Pretreatment ILA was associated with poor survival ( P < 0.001). Age ≥70 years (hazards ratio [HR], 1.98; 95% confidence interval [CI], 1.24-3.16; P = 0.004), metastatic stage (HR, 2.26; 95% CI, 1.36-3.74; P = 0.002), and ILA (HR, 1.96; 95% CI, 1.06-3.60; P = 0.031) were the independent risk factors of mortality. An ILA (HR, 3.94; 95% CI, 1.78-8.72; P = 0.001) was the only independent risk factor of mortality in localized stage prostate cancer patients. CONCLUSIONS: This study provides important insights into the unexplored effect of pretreatment ILA in prostate cancer patients. Pretreatment ILAs were observed considerably in the lung bases scanned on the abdominal CT scans among prostate cancer patients. Furthermore, pretreatment ILAs were the risk factor of mortality. Therefore, lung bases should be routinely inspected in the abdominal CT scans of prostate cancer patients. This result may help clinicians in establishing personalized management strategy of prostate cancer patients.

Plain film of the abdomen remains a low sensitivity test in A&E.

BACKGROUND: Plain film abdomens (PFA) are frequently used in the emergency department to help guide the management of patients presenting with abdominal symptoms. A plain film abdomen contributes minimally to clinical scenarios due to low sensitivity and specificity. Is a PFA useful in the emergency setting or does it serve to further complicate decision making? AIM: We hypothesise that PFAs in the emergency department are over utilised to falsely reassure clinicians and patients alike. METHODS: A search of the National Integrated Medical Imaging System (NIMIS) database in an Irish tertiary referral hospital was conducted. All plain film abdominal radiographs requested by the emergency department between 01/01/2022 and 31/08/2022 were identified. Requests where there was suspicion of foreign body were excluded. A retrospective search of the NIMIS database identified subjects who underwent subsequent imaging. RESULTS: A total of 619 abdominal films were deemed suitable for inclusion. These comprised of 338 male and 282 female subjects. Subjects had an average age of 64 years. Fifty-seven per cent of PFAs detected no abnormality. Forty-two per cent of subjects had subsequent imaging. The plain film findings correlated with further imaging in only 15% of cases. One case of ruptured aortic aneurysm and 11 perforations were detected on computerised tomography, none of these cases were evident on abdominal X-ray. CONCLUSION: Plain film abdomen requests are over utilised in the emergency department. PFAs are not sensitive for detecting acute pathology and should not be used to decide if a patient requires further imaging or a full clinical assessment.

Diagnostic Yield of Abdominal Radiographs in the Pediatric Emergency Department.

BACKGROUND AND OBJECTIVES: Abdominal radiographs (ARs) are commonly used in the pediatric emergency department (PED). Their low diagnostic accuracy leads to overuse, excess radiation exposure, and increased resource usage. This study aims to assess the diagnostic yield of ARs in the evaluation of intraabdominal pathology in the PED. METHODS: Retrospective, cross-sectional study of patients aged 0 to 18 years with an AR who visited the PED between 2017 and 2019. Diagnostic yield was analyzed with sensitivity, specificity, positive predictive value, negative predictive value (NPV), and likelihood ratio. RESULTS: A total of 4288 ARs were identified, with a rate of 6%. The overall abnormal AR rate was 31%. The incidences of an abnormal AR in abdominal pain, vomiting, and constipation were 26%, 37%, and 50%, respectively. There was a 13% rate of clinically significant diagnoses. The AR diagnostic yield showed 44% sensitivity, 70% specificity, 17% positive predictive value, and 90% NPV ( P < 0.05). Unadjusted odds ratio analysis of positive AR and abdominal pain, vomiting, and constipation revealed an odds ratio of 0.68 (95% confidence interval [CI], 0.63-0.75), 1.22 (95% CI, 1.06-1.39), and 1.72 (95% CI, 1.54-1.91), respectively. CONCLUSIONS: There is a low rate of intraabdominal pathologic processes that an AR can identify. A normal AR does not change patient management, nor does it reduce the need for further radiologic imaging. Despite a good NPV, the AR is not a useful diagnostic tool in the PED because of its limited ability to rule in or rule out clinically significant diagnoses.

Short-term psychosocial outcomes of adding a non-contrast abdominal computed tomography (CT) scan to the thoracic CT within lung cancer screening.

OBJECTIVES: To evaluate psychological, social, and financial outcomes amongst individuals undergoing a non-contrast abdominal computed tomography (CT) scan to screen for kidney cancer and other abdominal malignancies alongside the thoracic CT within lung cancer screening. SUBJECTS AND METHODS: The Yorkshire Kidney Screening Trial (YKST) is a feasibility study of adding a non-contrast abdominal CT scan to the thoracic CT within lung cancer screening. A total of 500 participants within the YKST, comprising all who had an abnormal CT scan and a random sample of one-third of those with a normal scan between 14/03/2022 and 24/08/2022 were sent a questionnaire at 3 and 6 months. Outcomes included the Psychological Consequences Questionnaire (PCQ), the short-form of the Spielberger State-Trait Anxiety Inventory, and the EuroQoL five Dimensions five Levels scale (EQ-5D-5L). Data were analysed using regression adjusting for participant age, sex, socioeconomic status, education, baseline quality of life (EQ-5D-5L), and ethnicity. RESULTS: A total of 380 (76%) participants returned questionnaires at 3 months and 328 (66%) at 6 months. There was no difference in any outcomes between participants with a normal scan and those with abnormal scans requiring no further action. Individuals requiring initial further investigations or referral had higher scores on the negative PCQ than those with normal scans at 3 months (standardised mean difference 0.28 sd, 95% confidence interval 0.01-0.54; P = 0.044). The difference was greater in those with anxiety or depression at baseline. No differences were seen at 6 months. CONCLUSION: Screening for kidney cancer and other abdominal malignancies using abdominal CT alongside the thoracic CT within lung cancer screening is unlikely to cause significant lasting psychosocial or financial harm to participants with incidental findings.

Development and clinical feasibility of a reduced-dose radiograph in children for feeding tube placement.

BACKGROUND: Temporary feeding tubes are commonly used but may lead to complications if malpositioned. Radiographs are the gold standard for assessing tube position, but clinician concern over radiation risks may curtail their use. OBJECTIVE: We describe development and use of a reduced dose feeding tube radiograph (RDFTR) targeted for evaluation of feeding tube position. MATERIALS AND METHODS: Age-based abdominal radiograph was adapted to use the lowest mAs setting of 0.32 mAs with field of view between carina and iliac crests. The protocol was tested in DIGI-13 line-pair plates and anthropomorphic phantoms. Retrospective review of initial clinical use compared dose area product (DAP) for RDFTR and routine abdomen, chest, or infant chest and abdomen. Review of RDFTR reports assessed tube visibility, malpositioning, and incidental critical findings. RESULTS: Testing through a line-pair phantom showed loss of spatial resolution from 2.2 line pairs to 0.6 line pairs but preserved visibility of feeding tube tip in RDFTR protocol. DAP comparisons across 23,789 exams showed RDFTR reduced median DAP 72-93% compared to abdomen, 55-78% compared to chest, and 76-79% compared to infant chest and abdomen (p<0.001). Review of 3286 reports showed tube was visible in 3256 (99.1%), malpositioned in airway 8 times (0.2%) and in the esophagus 74 times (2.3%). The tip was not visualized in 30 (0.9%). Pneumothorax or pneumoperitoneum was noted seven times (0.2%) but was expected or spurious in five of these cases. CONCLUSION: RDFTR significantly reduces radiation dose in children with temporary feeding tubes while maintaining visibility of tube tip.