Impact of Different Artificial Intelligence User Interfaces on Lung Nodule and Mass Detection on Chest Radiographs.

Purpose: To explore the impact of different user interfaces (UIs) for artificial intelligence (AI) outputs on radiologist performance and user preference in detecting lung nodules and masses on chest radiographs. Materials and Methods: A retrospective paired-reader study with a 4-week washout period was used to evaluate three different AI UIs compared with no AI output. Ten radiologists (eight radiology attending physicians and two trainees) evaluated 140 chest radiographs (81 with histologically confirmed nodules and 59 confirmed as normal with CT), with either no AI or one of three UI outputs: (a) text-only, (b) combined AI confidence score and text, or (c) combined text, AI confidence score, and image overlay. Areas under the receiver operating characteristic curve were calculated to compare radiologist diagnostic performance with each UI with their diagnostic performance without AI. Radiologists reported their UI preference. Results: The area under the receiver operating characteristic curve improved when radiologists used the text-only output compared with no AI (0.87 vs 0.82; P < .001). There was no difference in performance for the combined text and AI confidence score output compared with no AI (0.77 vs 0.82; P = .46) and for the combined text, AI confidence score, and image overlay output compared with no AI (0.80 vs 0.82; P = .66). Eight of the 10 radiologists (80%) preferred the combined text, AI confidence score, and image overlay output over the other two interfaces. Conclusion: Text-only UI output significantly improved radiologist performance compared with no AI in the detection of lung nodules and masses on chest radiographs, but user preference did not correspond with user performance.Keywords: Artificial Intelligence, Chest Radiograph, Conventional Radiography, Lung Nodule, Mass Detection© RSNA, 2023.

Three Zone Scanning Protocol For Lung Ultrasound: An Anatomical Basis.

Lung ultrasound is rapidly gaining popularity based on point of care ease of use, diagnostic fidelity and lack of ionising radiation. This was particularly notable at the beginning of the COVID-19 pandemic, where concerns of contamination of the x-ray department led to a reluctance to order frequent chest x-rays. Early COVID-19 lung involvement is of a bronchopneumonia, and patches of consolidation adjacent to the chest wall were easily detectable by ultrasound. A large number of proposed scanning protocols were advocated and are often complex and largely based on traditional stethoscope examination or access points on the chest wall rather than the underlying lung anatomy. A surgical understanding of lung anatomy and related surface anatomy has led us to develop a simplified three zone scanning protocol in 2013. The anterior zone corresponds to the upper lobe, and the posterior zone is divided between upper lobe and lower lobe. The relationship between lung lobes and the surface of the chest wall provides the anatomical basis for a simple three scanning zone lung ultrasound protocol.

CLiP, catheter and line position dataset.

Correct catheter position is crucial to ensuring appropriate function of the catheter and avoid complications. This paper describes a dataset consisting of 50,612 image level and 17,999 manually labelled annotations from 30,083 chest radiographs from the publicly available NIH ChestXRay14 dataset with manually annotated and segmented endotracheal tubes (ETT), nasoenteric tubes (NET) and central venous catheters (CVCs).

Adult diffuse leptomeningeal glioneuronal tumour with limited leptomeningeal involvement, lack of 1p deletion and BRAF V600E mutation.

Diffuse leptomeningeal glioneuronal tumours (DLGNT) are rare primary CNS tumours, traditionally characterised by leptomeningeal growth and usually affecting children. A recent large study defined DLGNT on a molecular basis, of which all demonstrated 1p deletions. The vast majority also demonstrated MAPK/ERK pathway activations, however BRAF V600E mutation has not been previously documented in adult cases. In this case report, we describe an unusual cerebral DLGNT, with limited leptomeningeal spread, intact 1p status and a BRAF V600E mutation.

Phenotypes of AKT3 deletion: a case report and literature review.

AKT3 (v-akt murine thymoma viral oncogene homolog 3) is located at chromosome 1q44 and encodes a 479 amino acid protein, a member of the protein kinase B (PKB) family. This gene is frequently involved in 1q44 deletion syndrome in patients with microcephaly, intellectual disability, and dysmorphic features. Phenotype and genotype studies of patients with 1q44 deletion syndrome have suggested that deletion of the AKT3 gene is responsible for the microcephaly in these patients. However, the phenotype of pure AKT3 deletion has not been studied. We report on a 1q44 deletion involving only AKT3 in a boy and his father. The boy has microcephaly, hypotonia, feeding difficulties, developmental delay, and minor dysmorphic features. His father does not have microcephaly and is of normal intelligence. We also analyzed the available information on the phenotypes of 13 individuals carrying a pure AKT3 gene deletion identified through literature review and database search. To our knowledge, this is the first report of a paternally inherited pure AKT3 deletion with full clinical description. This is also the first report to suggest that (1) AKT3 deletion is associated with microcephaly and intellectual disability with incomplete penetrance; (2) a pure AKT3 deletion is likely to be inherited in contrast to the larger 1q44 deletions, which are mostly de novo and (3) there seems to be no consistent or characteristic dysmorphism associated with pure AKT3 deletion.