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The validation of the accuracy of the quantification software in computed tomography (CT) images is very challenging. Therefore, we proposed a CT imaging phantom that accurately represents patient-specific anatomical structures and randomly integrates various lesions including disease-like patterns and lesions of various shapes and sizes using silicone casting and three-dimensional (3D) printing. Six nodules of various shapes and sizes were randomly added to the patient's modeled lungs to evaluate the accuracy of the quantification software. By using silicone materials, CT intensities suitable for the lesions and lung parenchyma were realized, and their Hounsfield unit (HU) values were evaluated on a CT scan of the phantom. As a result, based on the CT scan of the imaging phantom model, the measured HU values for the normal lung parenchyma, each nodule, fibrosis, and emphysematous lesions were within the target value. The measurement error between the stereolithography model and 3D-printing phantoms was 0.2 ± 0.18 mm. In conclusion, the use of 3D printing and silicone casting allowed the application and evaluation of the proposed CT imaging phantom for the validation of the accuracy of the quantification software in CT images, which could be applied to CT-based quantification and development of imaging biomarkers. [ABSTRACT FROM AUTHOR]

Recently, the development of 3D printing (3DP) technology and its application in various fields have improved our quality of life. However, hazardous materials that affect the human body, such as formaldehyde and particulate matter (PM), are emitted into the air during 3DP. This study measured the formaldehyde, PM10, and PM2.5 emitted by 3DP with the ventilation operation using six materials in material extrusion (ME) and vat photopolymerization (VP) and compared them between the 3DP workspace and the control setting with test–retest validation by two researchers. The experiments were divided into four stages based on the 3DP and ventilation operation. A linear mixed model was used to analyze the mean differences and tendencies between the 3DP workspace and the control setting. The change as ventilation was switched from off to on was evaluated by calculating the area. The differences and tendencies were shown in the statistically significant differences from a post-hoc test (α = 0.0125) except for some cases. There was a significant difference in formaldehyde depending on the ventilation operation; however, only a minor difference in PM10, and PM2.5 was confirmed. The amount of formaldehyde exceeding the standard was measured in all materials during 3DP without ventilation. Therefore, it is recommended to operate ventilation systems. [ABSTRACT FROM AUTHOR]

In thoracoabdominal aortic aneurysm repair, repairing the visceral and segmental arteries is challenging. Although there is a pre-hand-sewn and multi-branched graft based on the conventional image-based technique, it has shortcomings in precisely positioning and directing the visceral and segmental arteries. Here, we introduce two new reconstruction techniques using patient-specific 3D-printed graft reconstruction guides: (1) model-based technique that presents the projected aortic graft, visualizing the main aortic body and its major branches and (2) guide-based technique in which the branching vessels in the visualization model are replaced by marking points identifiable by tactile sense. We demonstrate the effectiveness by evaluating conventional and new techniques based on accuracy, marking time requirement, reproducibility, and results of survey to surgeons on the perceived efficiency and efficacy. The graft reconstruction guides cover the segmentation, design, fabrication, post-processing, and clinical application of open surgical repair of thoracoabdominal aneurysm, and proved to be efficient for accurately reconstructing customized grafts. [ABSTRACT FROM AUTHOR]

Herein, realistic and reusable phantoms for simulation of pediatric lung video-assisted thoracoscopic surgery (VATS) were proposed and evaluated. 3D-printed phantoms for VATS were designed based on chest computed tomography (CT) data of a pediatric patient with esophageal atresia and tracheoesophageal fistula. Models reflecting the patient-specific structure were fabricated based on the CT images. Appropriate reusable design, realistic mechanical properties with various material types, and 3D printers (fused deposition modeling (FDM) and PolyJet printers) were used to represent the realistic anatomical structures. As a result, the phantom printed by PolyJet reflected closer mechanical properties than those of the FDM phantom. Accuracies (mean difference ± 95 confidence interval) of phantoms by FDM and PolyJet were 0.53 ± 0.46 and 0.98 ± 0.55 mm, respectively. Phantoms were used by surgeons for VATS training, which is considered more reflective of the clinical situation than the conventional simulation phantom. In conclusion, the patient-specific, realistic, and reusable VATS phantom provides a better understanding the complex anatomical structure of a patient and could be used as an educational phantom for esophageal structure replacement in VATS. [ABSTRACT FROM AUTHOR]

We quantitatively evaluated breast tumor movement and volume changes between magnetic resonance imaging (MRI) scans in prone and supine positions. Twenty-seven breast tumor patients who received neoadjuvant systemic therapy (NST) for breast-conserving surgery were studied. Before and after NST, MRI scans in prone and supine positions were performed immediately. Tumor segmentation, volume, and position of tumors were evaluated in both positions. Average tumor volumes in prone and supine positions did not significantly differ (p = 0.877). Tumor movement from prone to supine positions from the origin of the bottom center of the sternum was strongly correlated with the distance from the tumor center to the chest wall (r = 0.669; p < 0.05). Tumor changes from prone to supine positions measured from the origin of the nipple depended on the location of the tumor in the breast. The prone-to-supine movement of all tumors from the origin of the bottom center of the sternum tended to move outward from the sagittal centerline of the body on the coronal plane, to the inside of the body on the sagittal plane, and outward and downward close to the body on the axial plane, which might help in planning operations using prone MRI in supine-position breast cancer surgery. [ABSTRACT FROM AUTHOR]

Segmentation is fundamental to medical image analysis. Recent advances in fully convolutional networks has enabled automatic segmentation; however, high labeling efforts and difficulty in acquiring sufficient and high-quality training data is still a challenge. In this study, a cascaded 3D U-Net with active learning to increase training efficiency with exceedingly limited data and reduce labeling efforts is proposed. Abdominal computed tomography images of 50 kidneys were used for training. In stage I, 20 kidneys with renal cell carcinoma and four substructures were used for training by manually labelling ground truths. In stage II, 20 kidneys from the previous stage and 20 newly added kidneys were used with convolutional neural net (CNN)-corrected labelling for the newly added data. Similarly, in stage III, 50 kidneys were used. The Dice similarity coefficient was increased with the completion of each stage, and shows superior performance when compared with a recent segmentation network based on 3D U-Net. The labeling time for CNN-corrected segmentation was reduced by more than half compared to that in manual segmentation. Active learning was therefore concluded to be capable of reducing labeling efforts through CNN-corrected segmentation and increase training efficiency by iterative learning with limited data. [ABSTRACT FROM AUTHOR]

These authors contributed equally: Taehun Kim, Kyung Hwa Lee and Sungwon Ham Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-019-57242-9, published online 15 January 2020 The original version of this Article contained an error in the spelling of the author Kyung Hwa Lee which was incorrectly given as Kyunghwa Lee. The original Article has been corrected. [Extracted from the article]