Influence of CT dose reduction on AI-driven malignancy estimation of incidental pulmonary nodules.

OBJECTIVES: The purpose of this study was to determine the influence of dose reduction on a commercially available lung cancer prediction convolutional neuronal network (LCP-CNN). METHODS: CT scans from a cohort provided by the local lung cancer center (n = 218) with confirmed pulmonary malignancies and their corresponding reduced dose simulations (25% and 5% dose) were subjected to the LCP-CNN. The resulting LCP scores (scale 1-10, increasing malignancy risk) and the proportion of correctly classified nodules were compared. The cohort was divided into a low-, medium-, and high-risk group based on the respective LCP scores; shifts between the groups were studied to evaluate the potential impact on nodule management. Two different malignancy risk score thresholds were analyzed: a higher threshold of ≥ 9 ("rule-in" approach) and a lower threshold of > 4 ("rule-out" approach). RESULTS: In total, 169 patients with 196 nodules could be included (mean age ± SD, 64.5 ± 9.2 year; 49% females). Mean LCP scores for original, 25% and 5% dose levels were 8.5 ± 1.7, 8.4 ± 1.7 (p > 0.05 vs. original dose) and 8.2 ± 1.9 (p < 0.05 vs. original dose), respectively. The proportion of correctly classified nodules with the "rule-in" approach decreased with simulated dose reduction from 58.2 to 56.1% (p = 0.34) and to 52.0% for the respective dose levels (p = 0.01). For the "rule-out" approach the respective values were 95.9%, 96.4%, and 94.4% (p = 0.12). When reducing the original dose to 25%/5%, eight/twenty-two nodules shifted to a lower, five/seven nodules to a higher malignancy risk group. CONCLUSION: CT dose reduction may affect the analyzed LCP-CNN regarding the classification of pulmonary malignancies and potentially alter pulmonary nodule management. CLINICAL RELEVANCE STATEMENT: Utilization of a "rule-out" approach with a lower malignancy risk threshold prevents underestimation of the nodule malignancy risk for the analyzed software, especially in high-risk cohorts. KEY POINTS: • LCP-CNN may be affected by CT image parameters such as noise resulting from low-dose CT acquisitions. • CT dose reduction can alter pulmonary nodule management recommendations by affecting the outcome of the LCP-CNN. • Utilization of a lower malignancy risk threshold prevents underestimation of pulmonary malignancies in high-risk cohorts.

Making CT Dose Monitoring Meaningful: Augmenting Dose with Imaging Quality.

Due to the concerns about radiation dose associated with medical imaging, radiation dose monitoring systems (RDMSs) are now utilized by many radiology providers to collect, process, analyze, and manage radiation dose-related information. Currently, most commercially available RDMSs focus only on radiation dose information and do not track any metrics related to image quality. However, to enable comprehensive patient-based imaging optimization, it is equally important to monitor image quality as well. This article describes how RDMS design can be extended beyond radiation dose to simultaneously monitor image quality. A newly designed interface was evaluated by different groups of radiology professionals (radiologists, technologists, and physicists) on a Likert scale. The results show that the new design is effective in assessing both image quality and safety in clinical practices, with an overall average score of 7.8 out of 10.0 and scores ranging from 5.5 to 10.0. Radiologists rated the interface highest at 8.4 out of 10.0, followed by technologists at 7.6 out of 10.0, and medical physicists at 7.5 out of 10.0. This work demonstrates how the assessment of the radiation dose can be performed in conjunction with the image quality using customizable user interfaces based on the clinical needs associated with different radiology professions.

Phase-Separated Transcriptional Condensates Accelerate Target-Search Process Revealed by Live-Cell Single-Molecule Imaging.

Compartmentalization by liquid-liquid phase separation is implicated in transcription. It remains unclear whether and how transcriptional condensates accelerate the search of transcriptional regulatory factors for their target sites. Furthermore, the molecular mechanisms by which regulatory factors nucleate on chromatin to assemble transcriptional condensates remain incompletely understood. The CBX-PRC1 complexes compartmentalize key developmental regulators for repression through phase-separated condensates driven by the chromobox 2 (CBX2) protein. Here, by using live-cell single-molecule imaging, we show that CBX2 nucleates on chromatin independently of H3K27me3 and CBX-PRC1. The interactions between CBX2 and DNA are essential for nucleating CBX-PRC1 on chromatin to assemble condensates. The assembled condensates shorten 3D diffusion time and reduce trials for finding specific sites through revisiting the same or adjacent sites repetitively, thereby accelerating CBX2 in searching for target sites. Overall, our data suggest a generic mechanism by which transcriptional regulatory factors nucleate to assemble condensates that accelerate their target-search process.