Development of deep learning-assisted overscan decision algorithm in low-dose chest CT: Application to lung cancer screening in Korean National CT accreditation program.

We propose a deep learning-assisted overscan decision algorithm in chest low-dose computed tomography (LDCT) applicable to the lung cancer screening. The algorithm reflects the radiologists' subjective evaluation criteria according to the Korea institute for accreditation of medical imaging (KIAMI) guidelines, where it judges whether a scan range is beyond landmarks' criterion. The algorithm consists of three stages: deep learning-based landmark segmentation, rule-based logical operations, and overscan determination. A total of 210 cases from a single institution (internal data) and 50 cases from 47 institutions (external data) were utilized for performance evaluation. Area under the receiver operating characteristic (AUROC), accuracy, sensitivity, specificity, and Cohen's kappa were used as evaluation metrics. Fisher's exact test was performed to present statistical significance for the overscan detectability, and univariate logistic regression analyses were performed for validation. Furthermore, an excessive effective dose was estimated by employing the amount of overscan and the absorbed dose to effective dose conversion factor. The algorithm presented AUROC values of 0.976 (95% confidence interval [CI]: 0.925-0.987) and 0.997 (95% CI: 0.800-0.999) for internal and external dataset, respectively. All metrics showed average performance scores greater than 90% in each evaluation dataset. The AI-assisted overscan decision and the radiologist's manual evaluation showed a statistically significance showing a p-value less than 0.001 in Fisher's exact test. In the logistic regression analysis, demographics (age and sex), data source, CT vendor, and slice thickness showed no statistical significance on the algorithm (each p-value > 0.05). Furthermore, the estimated excessive effective doses were 0.02 ± 0.01 mSv and 0.03 ± 0.05 mSv for each dataset, not a concern within slight deviations from an acceptable scan range. We hope that our proposed overscan decision algorithm enables the retrospective scan range monitoring in LDCT for lung cancer screening program, and follows an as low as reasonably achievable (ALARA) principle.

Fully automated image quality evaluation on patient CT: Multi-vendor and multi-reconstruction study.

While the recent advancements of computed tomography (CT) technology have contributed in reducing radiation dose and image noise, an objective evaluation of image quality in patient scans has not yet been established. In this study, we present a patient-specific CT image quality evaluation method that includes fully automated measurements of noise level, structure sharpness, and alteration of structure. This study used the CT images of 120 patients from four different CT scanners reconstructed with three types of algorithm: filtered back projection (FBP), vendor-specific iterative reconstruction (IR), and a vendor-agnostic deep learning model (DLM, ClariCT.AI, ClariPi Inc.). The structure coherence feature (SCF) was used to divide an image into the homogeneous (RH) and structure edge (RS) regions, which in turn were used to localize the regions of interests (ROIs) for subsequent analysis of image quality indices. The noise level was calculated by averaging the standard deviations from five randomly selected ROIs on RH, and the mean SCFs on RS was used to estimate the structure sharpness. The structure alteration was defined by the standard deviation ratio between RS and RH on the subtraction image between FBP and IR or DLM, in which lower structure alterations indicate successful noise reduction without degradation of structure details. The estimated structure sharpness showed a high correlation of 0.793 with manually measured edge slopes. Compared to FBP, IR and DLM showed 34.38% and 51.30% noise reduction, 2.87% and 0.59% lower structure sharpness, and 2.20% and -12.03% structure alteration, respectively, on an average. DLM showed statistically superior performance to IR in all three image quality metrics. This study is expected to contribute to enhance the CT protocol optimization process by allowing a high throughput and quantitative image quality evaluation during the introduction or adjustment of lower-dose CT protocol into routine practice.

Unique ethnic features of DDX41 mutations in patients with idiopathic cytopenia of undetermined significance, myelodysplastic syndrome, or acute myeloid leukemia.

DDX41 mutations are associated with hematologic malignancies including myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), but the incidence in idiopathic cytopenia of undetermined significance (ICUS) is unknown. We investigated the incidence, genetic characteristics, and clinical features of DDX41 mutations in Korean patients with ICUS, MDS, or AML. We performed targeted deep sequencing of 61 genes including DDX41 in 457 patients with ICUS (n=75), MDS (n=210), or AML (n=172). Germline DDX41 mutations with causality were identified in 28 (6.1%) patients, of whom 27 (96.4%) had somatic mutations in the other position of DDX41. Germline origins of the DDX41 mutations were confirmed in all of the 11 patients in whom germline-based testing was performed. Of the germline DDX41 mutations, p.V152G (n=10) was most common, followed by p.Y259C (n=8), p.A500fs (n=6), and p.E7* (n=3). Compared with non-mutated patients, patients with a DDX41 mutation were more frequently male, older, had a normal karyotype, low leukocyte count, and hypocellular marrow at diagnosis. Three of the four ICUS patients with germline DDX41 mutations progressed to MDS. The incidence of DDX41 mutations in Korean patients was high and there was a distinct mutation pattern, in that p.V152G was a unique germline variant. ICUS harboring germline DDX41 mutations may be regarded as a hereditary myeloid neoplasm. Germline DDX41 mutations are not uncommon and should be explored when treating patients with myeloid malignancies.

Hetero-integration enables fast switching time-of-flight sensors for light detection and ranging.

The time-of-flight (ToF) principle is a method used to measure distance and construct three-dimensional (3D) images by detecting the time or the phase difference between emitted and back-reflected optical flux. The ToF principle has been employed for various applications including light ranging and detection (LiDAR), machine vision and biomedical engineering; however, bulky system size and slow switching speed have hindered the widespread application of ToF technology. To alleviate these issues, a demonstration of hetero-integration of GaN-based high electron mobility transistors (HEMTs) and GaAs-based vertical cavity surface emitting lasers (VCSELs) on a single platform via a cold-welding method was performed. The hetero-integrated ToF sensors show superior switching performance when compared to silicon-transistor-based systems, miniaturizing size and exhibiting stable ranging and high-resolution depth-imaging. This hetero-integrated system of dissimilar material-based high-performance devices suggests a new pathway towards enabling high-resolution 3D imaging and inspires broader range application of heterogeneously integrated electronics and optoelectronics.

Modeling of the capillary wicking of flax fibers by considering the effects of fiber swelling and liquid absorption.

We propose a new model for the capillary rise of liquid in flax fibers whose diameter is changed by liquid absorption. Liquid absorption into the flax fibers is taken into account in a new modified Washburn equation by considering the mass of the liquid absorbed inside the fibers as well as that imbibed between the fibers. The change of permeability and hydraulic radius of pores in a fibrous medium due to the fiber swelling is modeled by a statistical approach considering a non-uniform distribution of flax fiber diameter. By comparisons between capillary rise test results and modeling results, we prove the validity of the proposed modified Washburn model to take into account the effects from fiber swelling and liquid absorption on the decrease of capillary rise velocity. The experimental observation of long-term capillary rise tests show that the swelling behavior of the fibers highly packed in a closed volume and its influence on the capillary wicking are different from those of an individual single fiber in a free space. The current approach was useful to characterize the swelling of fibers highly packed in a closed volume and its influence of the long-term behavior of capillary wicking.