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Purpose To investigate the ability of kilovolt-independent (hereafter, kV-independent) and tin filter spectral shaping to accurately quantify the coronary artery calcium score (CACS) and radiation dose reductions compared with the standard 120-kV CT protocol. Materials and Methods This prospective, blinded reader study included 201 participants (mean age, 60 years ± 9.8 [SD]; 119 female, 82 male) who underwent standard 120-kV CT and additional kV-independent and tin filter research CT scans from October 2020 to July 2021. Scans were reconstructed using a Qr36f kernel for standard scans and an Sa36f kernel for research scans simulating artificial 120-kV images. CACS, risk categorization, and radiation doses were compared by analyzing data with analysis of variance, Kruskal-Wallis test, Mann-Whitney test, Bland-Altman analysis, Pearson correlations, and κ analysis for agreement. Results There was no evidence of differences in CACS across standard 120-kV, kV-independent, and tin filter scans, with median CACS values of 1 (IQR, 0-48), 0.6 (IQR, 0-58), and 0 (IQR, 0-51), respectively (P = .85). Compared with standard 120-kV scans, kV-independent and tin filter scans showed excellent correlation in CACS values (r = 0.993 and r = 0.999, respectively), with high agreement in CACS risk categorization (κ = 0.95 and κ = 0.93, respectively). Standard 120-kV scans had a mean radiation dose of 2.09 mSv ± 0.84, while kV-independent and tin filter scans reduced it to 1.21 mSv ± 0.85 and 0.26 mSv ± 0.11, cutting doses by 42% and 87%, respectively (P < .001). Conclusion The kV-independent and tin filter research CT acquisition techniques showed excellent agreement and high accuracy in CACS estimation compared with standard 120-kV scans, with large reductions in radiation dose. Keywords: CT, Cardiac, Coronary Arteries, Radiation Safety, Coronary Artery Calcium Score, Radiation Dose Reduction, Low-Dose CT Scan, Tin Filter, kV-Independent Supplemental material is available for this article. © RSNA, 2024.

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BACKGROUND: The retention of foreign bodies inside the body during ludic/sexual procedures or for traumatism represents one of the causes of visits to accident and emergency departments that often requires surgical removal of the foreign body. However, there are cases where the discovery of such foreign bodies takes place after many years, as in patients that are slightly compromised from a neuro-sociological point of view.
METHODS: A 76-year-old male presented to an outpatient urological examination due to an increase in scrotal volume. At the ultrasound check, an acoustic interference from a solid object was detected, for which computed tomography was requested. The computed tomography scan revealed the presence of an elongated metal body in the perineum. The removal of the foreign body in the operating theatre was then scheduled. A 10 cm long stainless-steel nail located within an abscessed foreign body granuloma was identified and removed via a scrotal access. Four days later, a new surgical toilet was performed due to minimal necrosis of the skin flaps. The patient then performed three more dressings in the operating theatre during the following week. Healing took place by secondary intention until a perfect healing of the surgical wound was obtained.
CONCLUSIONS: Removal of foreign bodies from the perineum in case of infection can be challenging. Careful attention and postoperative dressings are crucial for the success of the case.

OBJECTIVE: To assess the diagnostic efficacy of integrating B-mode and color Doppler capabilities of ultrasound (US) to establish a robust standalone diagnostic tool for the diagnosis of ureteric stones as an alternative to non-contrast-enhanced computed tomography (NCCT).
METHODS: A total of 140 consecutive patients diagnosed with ureteric stones using NCCT were enrolled. On the same day, US in both B-mode and Color Doppler was performed by an experienced radiologist who was blinded to the NCCT scan results. The diagnostic rate of US for stone detection was recorded. Additionally, baseline patient and stone characteristics were analyzed for their association with the accuracy of stone detection using US.
RESULTS: US exhibited a high sensitivity of 91.43%, detecting 128 out of 140 stone foci. Notably, ureteric stones in the proximal and uretero-vesical junction (UVJ) segments were readily identifiable compared to those in the pelvic region (p = 0.0003). Additionally, hydronephrosis enhanced the US\'s ability to detect stones (p < 0.0001). Conversely, abdominal gases and obesity adversely affected US capabilities (p < 0.0001 and p = 0.009, respectively). Stone side, size, and density showed no statistically significant impact (p > 0.05).
CONCLUSIONS: US with its color Doppler capabilities could serve as a reliable and safe alternative imaging modality in the diagnostic work up of patients with ureterolithiasis. Factors including stone location, Hydronephrosis, weight and abdominal gases significantly influenced its accuracy.

UNASSIGNED: SAPIEN3 (S3) is a ubiquitous redo-transcatheter aortic valve (TAV) replacement alternative for degenerated Evolut valves, but S3 sizing for S3-in-Evolut remains unclear. We sought to compare the impact of in vivo computed tomography (CT)-sizing on redo-TAV feasibility for S3-in-Evolut with traditional bench-sizing.
UNASSIGNED: CT scans of 290 patients treated using Evolut R/PRO/PRO+ between July 2015 and December 2021 were analyzed. S3-in-Evolut was simulated using S3 outflow/neoskirt plane (NSP) at node-6, -5, and -4. CT-sizing for S3 was determined by averaging 4 areas of the Evolut stent frame at NSP level and 3 nodes below. Redo-TAV was deemed feasible if the NSP was below the coronaries, or the narrowest valve (virtual S3)-to-aorta distance was >4 mm. Risk of prosthesis-patient mismatch was estimated using predicted indexed-effective orifice area.
UNASSIGNED: Compared with bench-sizing, CT-sizing yielded smaller S3 size in 82% at node-6, 81% at node-5, and 84% at node-4. Factors associated with CT-sizing less than bench-sizing were larger index Evolut size, underexpansion of index Evolut, and shallower implant depth (all P<0.05). CT-sizing increased redo-TAV feasibility by +8% at node-6, +10% at node-5, and +4% at node-4. Redo-TAV feasibility increased with annulus size, sinotubular junction dimensions, coronary heights, index Evolut size, deeper Evolut implant depth, and lower NSP levels (all P<0.05). CT-sizing had a slightly higher estimated risk of severe prosthesis-patient mismatch (9% at node-6, 7% at node-5, and 6% at node-4), which could be mitigated by changing the NSP.
UNASSIGNED: CT-sizing for S3-in-Evolut is associated with higher feasibility of redo-TAV compared with bench-sizing, potentially reducing the risk of excessive oversizing and S3 underexpansion. Further validation using real-world clinical data is necessary.

We report a case of a Morgagni hernia repaired by primary closure with an extra-abdominal suture. Moreover, we reviewed cases of laparoscopically repaired Morgagni hernia, in which the size of the hernia defect was known, to establish a size criterion for mesh utilization. An 87-year-old woman presented to our hospital with right upper abdominal pain and vomiting. She had no history of abdominal surgery or trauma. Chest radiography and computed tomography (CT) revealed a Morgagni hernia, with the stomach and transverse colon herniated into the right chest cavity. Initially, an endoscopic repair was performed for the herniated stomach due to her age, which was successful. However, she had a recurrence 2 days later, prompting us to perform a semi-emergent laparoscopic surgery. Laparoscopic examination revealed a Morgagni defect, with the omentum, transverse colon, and stomach herniated, with the stomach reduced by pneumoperitoneum. Fortunately, the herniated organs could be easily relocated into the abdomen with no adhesions. The hernia defect measured 6 x 3 cm. We performed primary closure with an extra-abdominal suture. No sac resection was performed. The operation lasted 98 min. Oral intake was initiated on postoperative day 1, and the patient was discharged on postoperative day 3 without complications. Chest radiography and CT scans at 1 month postoperatively showed no recurrence, and the patient remained asymptomatic at the 9-month follow-up examination. According to our review findings, primary closure is an efficient method for small hernia defects (rule of thumb: width, <4 cm; length, <7 cm).

UNASSIGNED: To investigate the prediction of pathologic complete response (pCR) in patients with non-small cell lung cancer (NSCLC) undergoing neoadjuvant immunochemotherapy (NAIC) using quantification of intratumoral heterogeneity from pre-treatment CT image.
UNASSIGNED: This retrospective study included 178 patients with NSCLC who underwent NAIC at 4 different centers. The training set comprised 108 patients from center A, while the external validation set consisted of 70 patients from center B, center C, and center D. The traditional radiomics model was contrasted using radiomics features. The radiomics features of each pixel within the tumor region of interest (ROI) were extracted. The optimal division of tumor subregions was determined using the K-means unsupervised clustering method. The internal tumor heterogeneity habitat model was developed using the habitats features from each tumor sub-region. The LR algorithm was employed in this study to construct a machine learning prediction model. The diagnostic performance of the model was evaluated using criteria such as area under the receiver operating characteristic curve (AUC), accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV).
UNASSIGNED: In the training cohort, the traditional radiomics model achieved an AUC of 0.778 [95% confidence interval (CI): 0.688-0.868], while the tumor internal heterogeneity habitat model achieved an AUC of 0.861 (95% CI: 0.789-0.932). The tumor internal heterogeneity habitat model exhibits a higher AUC value. It demonstrates an accuracy of 0.815, surpassing the accuracy of 0.685 achieved by traditional radiomics models. In the external validation cohort, the AUC values of the two models were 0.723 (CI: 0.591-0.855) and 0.781 (95% CI: 0.673-0.889), respectively. The habitat model continues to exhibit higher AUC values. In terms of accuracy evaluation, the tumor heterogeneity habitat model outperforms the traditional radiomics model, achieving a score of 0.743 compared to 0.686.
UNASSIGNED: The quantitative analysis of intratumoral heterogeneity using CT to predict pCR in NSCLC patients undergoing NAIC holds the potential to inform clinical decision-making for resectable NSCLC patients, prevent overtreatment, and enable personalized and precise cancer management.

Automatic detection of pulmonary nodule based on computer tomography (CT) images can significantly improve the diagnosis and treatment of lung cancer. However, there is a lack of effective interactive tools to record the marked results of radiologists in real time and feed them back to the algorithm model for iterative optimization. This paper designed and developed an online interactive review system supporting the assisted diagnosis of lung nodules in CT images. Lung nodules were detected by the preset model and presented to doctors, who marked or corrected the lung nodules detected by the system with their professional knowledge, and then iteratively optimized the AI model with active learning strategy according to the marked results of radiologists to continuously improve the accuracy of the model. The subset 5-9 dataset of the lung nodule analysis 2016(LUNA16) was used for iteration experiments. The precision, F1-score and MioU indexes were steadily improved with the increase of the number of iterations, and the precision increased from 0.213 9 to 0.565 6. The results in this paper show that the system not only uses deep segmentation model to assist radiologists, but also optimizes the model by using radiologists\' feedback information to the maximum extent, iteratively improving the accuracy of the model and better assisting radiologists.
基于电子计算机断层扫描（CT）影像的肺结节自动检测可以有效辅助肺癌诊治，但当前缺乏有效的交互工具将放射科医生的判读结果实时记录并反馈，以优化后台算法模型。本文设计并研发了一个支持CT图像肺结节辅助诊断的在线交互审查系统，通过预置模型检测出肺结节展示给医生，医生利用专业知识对检测的肺结节进行标注，然后根据标注结果采用主动学习策略对内置模型进行迭代优化，以持续提高模型的准确性。本文以开源肺结节数据集——肺结节分析2016（LUNA16）的5～9号子集进行迭代实验，随着迭代次数的增加，模型的准确率、调和分数和交并比指标稳定提升，准确率从0.213 9提高至0.565 6。本文研究结果表明，该系统能在使用深度分割模型辅助医生诊断的同时，最大程度地利用医生的反馈信息来优化模型，迭代提高模型的准确性，从而更好地辅助医生工作。.

The onset of the COVID-19 pandemic allowed physicians to gain experience in lung ultrasound (LUS) during the acute phase of the disease. However, limited data are available on LUS findings during the recovery phase. The aim of this study was to evaluate the utility of LUS to assess lung involvement in patients with post-COVID-19 syndrome. This study prospectively enrolled 72 patients who underwent paired LUS and chest CT scans (112 pairs including follow-up). The most frequent CT findings were ground glass opacities (83.3%), subpleural lines (72.2%), traction bronchiectasis (37.5%), and consolidations (31.9%). LUS revealed irregular pleural lines as a common abnormality initially (56.9%), along with subpleural consolidation >2.5 mm ≤10 mm (26.5%) and B-lines (26.5%). A strong correlation was found between LUS score, calculated by artificial intelligence percentage involvement in ground glass opacities described in CT (r = 0.702, p < 0.05). LUS score was significantly higher in the group with fibrotic changes compared to the non-fibrotic group with a mean value of 19.4 ± 5.7 to 11 ± 6.6, respectively (p < 0.0001). LUS might be considered valuable for examining patients with persistent symptoms after recovering from COVID-19 pneumonia. Abnormalities identified through LUS align with CT scan findings; thus, LUS might potentially reduce the need for frequent chest CT examinations.