Fleischner Society: Glossary of Terms for Thoracic Imaging.

Members of the Fleischner Society have compiled a glossary of terms for thoracic imaging that replaces previous glossaries published in 1984, 1996, and 2008, respectively. The impetus to update the previous version arose from multiple considerations. These include an awareness that new terms and concepts have emerged, others have become obsolete, and the usage of some terms has either changed or become inconsistent to a degree that warranted a new definition. This latest glossary is focused on terms of clinical importance and on those whose meaning may be perceived as vague or ambiguous. As with previous versions, the aim of the present glossary is to establish standardization of terminology for thoracic radiology and, thereby, to facilitate communications between radiologists and clinicians. Moreover, the present glossary aims to contribute to a more stringent use of terminology, increasingly required for structured reporting and accurate searches in large databases. Compared with the previous version, the number of images (chest radiography and CT) in the current version has substantially increased. The authors hope that this will enhance its educational and practical value. All definitions and images are hyperlinked throughout the text. Click on each figure callout to view corresponding image. © RSNA, 2024 Supplemental material is available for this article. See also the editorials by Bhalla and Powell in this issue.

Pictorial Review of Pleural Disease: Multimodality Imaging and Differential Diagnosis.

The pleura is a thin, smooth, soft-tissue structure that lines the pleural cavity and separates the lungs from the chest wall, consisting of the visceral and parietal pleurae and physiologic pleural fluid. There is a broad spectrum of normal variations and abnormalities in the pleura, including pneumothorax, pleural effusion, and pleural thickening. Pneumothorax is associated with pulmonary diseases and is caused by iatrogenic or traumatic factors. Chest radiography and US help detect pneumothorax with various signs, and CT can also help assess the causes. Pleural effusion occurs in a wide spectrum of diseases, such as heart failure, cirrhosis, asbestos-related diseases, infections, chylothorax, and malignancies. Chest US allows detection of a small pleural effusion and evaluation of echogenicity or septa in pleural effusion. Pleural thickening may manifest as unilateral or bilateral and as focal, multifocal, or diffuse. Various diseases can demonstrate pleural thickening, such as asbestos-related diseases, neoplasms, and systemic diseases. CT, MRI, and fluorodeoxyglucose (FDG) PET/CT can help differentiate between benign and malignant lesions. Knowledge of these features can aid radiologists in suggesting diagnoses and recommending further examinations with other imaging modalities. The authors provide a comprehensive review of the clinical and multimodality imaging findings of pleural diseases and their differential diagnoses. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

The Tumor Growth Inhibitory Effect of a Standardized Extract of Cultured Lentinula edodes Mycelia Using Patient Derived Xenograft Model.

Patient derived xenograft (PDX) is a powerful tool to confirm pharmacological efficacy in non-clinical studies for the development of various drugs including anti-cancer agents and therapeutic research. A standardized extract of cultured Lentinula edodes mycelia, a product name AHCC® is produced by Amino Up Co., Ltd. (Sapporo, Japan). In this study, we investigated the inhibitory effect of AHCC® on the growth of tumor PDX in Super SCID (severe combined immunodeficiency) mice. Effects of AHCC® and BCG administration on the growth of renal cancer PDX implanted in Super SCID mice were evaluated by PDX growth curve. Tendency for the effects on the growth of renal cancer PDX in Super SCID by administration of AHCC® and BCG before implanting the PDX were demonstrated. The effects of the oral administration of AHCC® on the growth of renal, invasive and non-invasive breast cancer PDX in Super SCID mice were studied. In Super SCID mice transplanted with renal cancer PDX, AHCC® significantly suppressed tumor proliferation from the day 48 to 83 after transplantation. In two types of breast cancer PDX, tendency of the growth inhibitory effects of AHCC® were shown by PDX growth curve. Significant inhibitory effect was found at only one time point for during proliferation in each PDX. Super SCID-PDX model has the potential to be a useful tool to investigate for the effect of functional foods.

Investigation of abdominal artery delineation by photon-counting detector CT.

OBJECTIVES: To evaluate the ability of 50-keV virtual monoenergetic images (VMI) to depict abdominal arteries in abdominal CT angiography (CTA) compared with 70-keV VMI with photon-counting detector CT (PCD-CT). METHODS: Fifty consecutive patients who underwent multiphase abdominal scans between March and April 2023 were included. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were quantitatively assessed for the abdominal aorta (AA), celiac artery (CeA), superior mesenteric artery (SMA), renal artery (RA), and right hepatic artery (RHA) at both 50- and 70-keV VMI. In addition, 3D images from CTA were analyzed to measure arterial lengths and evaluate the visualization of distal branches. RESULTS: Significantly higher SNR and CNR were observed at 50-keV compared to 70-keV VMI for all arteries: AA (36.54 and 48.28 vs. 25.70 and 28.46), CeA (22.39 and 48.38 vs. 19.09 and 29.15), SMA (23.34 and 49.34 vs. 19.67 and 29.71), RA (22.88 and 48.84 vs. 20.15 and 29.41), and RHA (14.38 and 44.41 vs. 13.45 and 27.18), all p < 0.05. Arterial lengths were also significantly longer at 50-keV: RHA (192.6 vs. 180.3 mm), SMA (230.9 vs. 216.5 mm), and RA (95.9 vs. 92.0 mm), all p < 0.001. CONCLUSION: In abdominal CTA with PCD-CT, 50-keV VMI demonstrated superior quantitative image quality compared to 70-keV VMI. In addition, 50-keV VMI 3D CTA allowed better visualization of abdominal artery branches, highlighting its potential clinical advantage for improved imaging and detailed assessment of abdominal arteries.

Preclinical Evaluation of Biodistribution and Toxicity of [211At]PSMA-5 in Mice and Primates for the Targeted Alpha Therapy against Prostate Cancer.

Astatine (211At) is a cyclotron-produced alpha emitter with a physical half-life of 7.2 h. In our previous study, the 211At-labeled prostate-specific membrane antigen (PSMA) compound ([211At]PSMA-5) exhibited excellent tumor growth suppression in a xenograft model. We conducted preclinical biodistribution and toxicity studies for the first-in-human clinical trial. [211At]PSMA-5 was administered to both normal male ICR mice (n = 85) and cynomolgus monkeys (n = 2). The mice were divided into four groups for the toxicity study: 5 MBq/kg, 12 MBq/kg, 35 MBq/kg, and vehicle control, with follow-ups at 1 day (n = 10 per group) and 14 days (n = 5 per group). Monkeys were observed 24 h post-administration of [211At]PSMA-5 (9 MBq/kg). Blood tests and histopathological examinations were performed at the end of the observation period. Blood tests in mice indicated no significant myelosuppression or renal dysfunction. However, the monkeys displayed mild leukopenia 24 h post-administration. Despite the high accumulation in the kidneys and thyroid, histological analysis revealed no abnormalities. On day 1, dose-dependent single-cell necrosis/apoptosis was observed in the salivary glands of mice and intestinal tracts of both mice and monkeys. Additionally, tingible body macrophages in the spleen and lymph nodes indicated phagocytosis of apoptotic B lymphocytes. Cortical lymphopenia (2/10) in the thymus and a decrease in the bone marrow cells (9/10) were observed in the 35 MBq/kg group in mice. These changes were transient, with no irreversible toxicity observed in mice 14 days post-administration. This study identified no severe toxicities associated with [211At]PSMA-5, highlighting its potential as a next-generation targeted alpha therapy for prostate cancer. The sustainable production of 211At using a cyclotron supports its applicability for clinical use.

Novel Strategy for the Management of Cervical Multicystic Diseases.

PURPOSE: To investigate the clinical practices of diagnosing multicystic cervical lesions as a means to develop a more appropriate diagnostic algorithm for gastric-type adenocarcinoma (GAS) and its precursors. METHODS: Clinical information for 159 surgically treated patients for multicystic disease of the uterine cervix was collected from 15 hospitals. We performed a central review of the MRI and pathological findings. The MRI findings were categorized into four types including two newly proposed imaging features based on the morphology and distribution of cysts, and the diagnosis accuracy was assessed. Among the four MRI types, types 1 and 2 were categorized as benign lesions that included LEGH; type 3 were precancerous lesions (with an assumption of atypical LEGH); and type 4 were malignant lesions. RESULTS: The central pathological review identified 56 cases of LEGH, seven with GAS, four with another form of carcinoma, and 92 with benign disease. In clinical practice, over-diagnosis of malignancy (suspicion of MDA) occurred for 12/19 cases (63.2%) and under-diagnosis of malignancy occurred for 4/11 (36%). Among the 118 patients who had a preoperative MRI and underwent a hysterectomy, type 3 or 4 MRI findings in conjunction with abnormal cytology were positively indicative of premalignancy or malignancy, with a sensitivity and specificity of 61.1% and 96.7%, respectively. CONCLUSIONS: Although the correct preoperative diagnosis of cervical cancer with a multicystic lesion is challenging, the combination of cytology and MRI findings creates a more appropriate diagnostic algorithm that significantly improves the diagnostic accuracy for differentiating benign disease from premalignancy and malignancy.

Targeted α-therapy using astatine (211At)-labeled PSMA1, 5, and 6: a preclinical evaluation as a novel compound.

PURPOSE: Targeted α-therapy (TAT) for prostate-specific membrane antigen (PSMA) is a promising treatment for metastatic castration-resistant prostate cancer (CRPC). Astatine is an α-emitter (half-life=7.2 h) that can be produced by a 30-MeV cyclotron. This study evaluated the treatment effect of 211At-labeled PSMA compounds in mouse xenograft models. METHODS: Tumor xenograft models were established by subcutaneous transplantation of human prostate cancer cells (LNCaP) in NOD/SCID mouse. [211At]PSMA1, [211At]PSMA5, or [211At]PSMA6 was administered to LNCaP xenograft mice to evaluate biodistribution at 3 and 24 h. The treatment effect was evaluated by administering [211At]PSMA1 (0.40 ± 0.07 MBq), [211At]PSMA5 (0.39 ± 0.03 MBq), or saline. Histopathological evaluation was performed for the at-risk organs at 3 and 6 weeks after administration. RESULTS: [211At]PSMA5 resulted in higher tumor retention compared to [211At]PSMA1 and [211At]PSMA6 (30.6 ± 17.8, 12.4 ± 4.8, and 19.1 ± 4.5 %ID/g at 3 h versus 40.7 ± 2.6, 8.7 ± 3.5, and 18.1 ± 2.2%ID/g at 24 h, respectively), whereas kidney excretion was superior in [211At]PSMA1 compared to [211At]PSMA5 and [211At]PSMA6. An excellent treatment effect on tumor growth was observed after [211At]PSMA5 administration. [211At]PSMA1 also showed a substantial treatment effect; however, the tumor size was relatively larger compared to that with [211At]PSMA5. In the histopathological evaluation, regenerated tubules were detected in the kidneys at 3 and 6 weeks after the administration of [211At]PSMA5. CONCLUSION: TAT using [211At]PSMA5 resulted in excellent tumor growth suppression with minimal side effects in the normal organs. [211At]PSMA5 should be considered a new possible TAT for metastatic CRPC, and translational prospective trials are warranted.

Radiologists with and without deep learning-based computer-aided diagnosis: comparison of performance and interobserver agreement for characterizing and diagnosing pulmonary nodules/masses.

OBJECTIVES: To compare the performance of radiologists in characterizing and diagnosing pulmonary nodules/masses with and without deep learning (DL)-based computer-aided diagnosis (CAD). METHODS: We studied a total of 101 nodules/masses detected on CT performed between January and March 2018 at Osaka University Hospital (malignancy: 55 cases). SYNAPSE SAI Viewer V1.4 was used to analyze the nodules/masses. In total, 15 independent radiologists were grouped (n = 5 each) according to their experience: L (< 3 years), M (3-5 years), and H (> 5 years). The likelihoods of 15 characteristics, such as cavitation and calcification, and the diagnosis (malignancy) were evaluated by each radiologist with and without CAD, and the assessment time was recorded. The AUCs compared with the reference standard set by two board-certified chest radiologists were analyzed following the multi-reader multi-case method. Furthermore, interobserver agreement was compared using intraclass correlation coefficients (ICCs). RESULTS: The AUCs for ill-defined boundary, irregular margin, irregular shape, calcification, pleural contact, and malignancy in all 15 radiologists, irregular margin and irregular shape in L and ill-defined boundary and irregular margin in M improved significantly (p < 0.05); no significant improvements were found in H. L showed the greatest increase in the AUC for malignancy (not significant). The ICCs improved in all groups and for nearly all items. The median assessment time was not prolonged by CAD. CONCLUSIONS: DL-based CAD helps radiologists, particularly those with < 5 years of experience, to accurately characterize and diagnose pulmonary nodules/masses, and improves the reproducibility of findings among radiologists. KEY POINTS: • Deep learning-based computer-aided diagnosis improves the accuracy of characterizing nodules/masses and diagnosing malignancy, particularly by radiologists with < 5 years of experience. • Computer-aided diagnosis increases not only the accuracy but also the reproducibility of the findings across radiologists.

Risk Factors Associated with Clinical Failure of Uterine Artery Embolization for Postpartum Hemorrhage.

PURPOSE: To identify risk factors for clinical failure of uterine artery embolization (UAE) for postpartum hemorrhage (PPH), with particular attention to the uterine artery diameter. MATERIALS AND METHODS: This retrospective study included 47 patients who underwent UAE for PPH between January 1, 2010, and January 31, 2021. Technical success was defined as the completion of embolization of the arteries thought to be the cause of the bleeding. Clinical success was defined as no recurrent bleeding or need for additional therapeutic interventions. Univariate and multivariate analyses were performed to examine the risk factors associated with clinical failure of UAE. RESULTS: Of the 47 patients, 6 had recurrent bleeding. Of the 6 patients, 4 underwent hysterectomy, and 2 underwent repeat embolization. The clinical success rate was 87.2% (41/47), with no major adverse events such as uterine infarction or death. In univariate analysis, there were slight differences in multiparity (P = .115) and placental abruption (P = .128) and a significant difference in the findings of a narrow uterine artery on digital subtraction angiography (DSA) (P = .005). In multivariate analysis, only a narrow uterine artery on DSA was a significant factor (odds ratio, 18.5; 95% confidence interval, 2.5-134.8; P = .004). CONCLUSIONS: A narrow uterine artery on DSA was a risk factor for clinically unsuccessful UAE for PPH. It may be prudent to conclude the procedure only after it is ensured that vasospasm has been relieved.

Image Quality and Lesion Detectability of Pancreatic Phase Thin-Slice Computed Tomography Images With a Deep Learning-Based Reconstruction Algorithm.

OBJECTIVE: To evaluate the image quality and lesion detectability of pancreatic phase thin-slice computed tomography (CT) images reconstructed with a deep learning-based reconstruction (DLR) algorithm compared with filtered-back projection (FBP) and hybrid iterative reconstruction (IR) algorithms. METHODS: Fifty-three patients who underwent dynamic contrast-enhanced CT including pancreatic phase were enrolled in this retrospective study. Pancreatic phase thin-slice (0.625 mm) images were reconstructed with each FBP, hybrid IR, and DLR. Objective image quality and signal-to-noise ratio of the pancreatic parenchyma, and contrast-to-noise ratio of pancreatic lesions were compared between the 3 reconstruction algorithms. Two radiologists independently assessed the image quality of all images. The diagnostic performance for the detection of pancreatic lesions was compared among the reconstruction algorithms using jackknife alternative free-response receiver operating characteristic analysis. RESULTS: Deep learning-based reconstruction resulted in significantly lower image noise and higher signal-to-noise ratio and contrast-to-noise ratio than hybrid IR and FBP ( P < 0.001). Deep learning-based reconstruction also yielded significantly higher visual scores than hybrid IR and FBP ( P < 0.01). The diagnostic performance of DLR for detecting pancreatic lesions was highest for both readers, although a significant difference was found only between DLR and FBP in one reader ( P = 0.02). CONCLUSIONS: Deep learning-based reconstruction showed improved objective and subjective image quality of pancreatic phase thin-slice CT relative to other reconstruction algorithms and has potential for improving lesion detectability.

Ultrafast lumbar spine MRI protocol using deep learning-based reconstruction: diagnostic equivalence to a conventional protocol.

OBJECTIVE: To evaluate the diagnostic equivalency between an ultrafast (1 min 53 s) lumbar MRI protocol using deep learning-based reconstruction and a conventional lumbar MRI protocol (12 min 31 s). MATERIALS AND METHODS: This study included 58 patients who underwent lumbar MRI using both conventional and ultrafast protocols, including sagittal T1-weighted, T2-weighted, short-TI inversion recovery, and axial T2-weighted sequences. Compared with the conventional protocol, the ultrafast protocol shortened the acquisition time to approximately one-sixth. To compensate for the decreased signal-to-noise ratio caused by the acceleration, deep learning-based reconstruction was applied. Three neuroradiologists graded degenerative changes and analyzed for presence of other pathologies. For the grading of degenerative changes, interprotocol intrareader agreement was assessed using kappa statics. Interchangeability between the two protocols was also tested by calculating the individual equivalence index between the intraprotocol interreader agreement and interprotocol interreader agreement. For the detection of other pathologies, interprotocol intrareader agreement was assessed. RESULTS: For the grading of degenerative changes, the kappa values for interprotocol intrareader agreement of all three readers ranged from 0.707 to 0.804, indicating substantial to almost perfect agreement. Except for foraminal stenosis and disc contour on axial images, the 95% confidence interval of the individual equivalence index was < 5%, indicating the two protocols were interchangeable. For the detection of other pathologies, the interprotocol intrareader agreement rates were > 98% for each individual pathology. CONCLUSIONS: Our proposed ultrafast lumbar spine MRI protocol provided almost equivalent diagnostic results to that of the conventional protocol, except for some degenerative changes.

Simultaneous spatial and temporal regularization in low-dose dynamic contrast-enhanced CT cerebral perfusion studies.

PURPOSE: To apply total generalized variation (TGV) and its combination with low-rank and sparse decomposition (LRSD) (LTGV) to cerebral perfusion studies using low-dose dynamic contrast-enhanced (DCE) CT and to quantitatively evaluate their performances through comparisons with those without any regularizers and those of total variation (TV) and its combination with LRSD (LTV) using simulation and clinical data. METHODS: The simulation study used a realistic digital brain phantom. Low-dose DCE-CT images were reconstructed using the regularizers and primal-dual algorithm. Subsequently, cerebral perfusion parameter (CPP) images were generated from them. Thereafter, their quality was evaluated based on the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). Further, the accuracy of CPP estimation was evaluated through a linear regression analysis between the CPP values obtained by the above regularizers and those obtained from the noise-free DCE-CT images. In addition, the mean and standard deviation of the CPP were calculated (region analysis). In the clinical study, low-dose DCE-CT images were generated using normal-dose images acquired from a patient, and CPP images were generated from them similar to that in the simulation study. RESULTS: When using LTV and LTGV, both PSNR and SSIM were higher than those of the other methods with increasing regularization parameter values. The results of the linear regression and region analyses demonstrated that TGV generally exhibited the best performance, followed by LTGV, and finally that of TV was significantly different from those of the other regularizers. Despite an overall consistency between the simulation and clinical results, certain inconsistencies appeared owing to the difference in generating low-dose DCE-CT images. CONCLUSIONS: The results implied that TGV and LTGV were useful in improving the accuracy of CPP estimation using low-dose DCE-CT. This study provides an improved understanding of the performance of regularizers and is expected to aid in the selection of a suitable regularizer for low-dose DCE-CT perfusion studies.

Use of artificial intelligence to identify data elements for The Japanese Orthopaedic Association National Registry from operative records.

BACKGROUND: The Japanese Orthopaedic Association National Registry (JOANR) was recently launched in Japan and is expected to improve the quality of medical care. However, surgeons must register ten detailed features for total hip arthroplasty, which is labor intensive. One possible solution is to use a system that automatically extracts information about the surgeries. Although it is not easy to extract features from an operative record consisting of free-text data, natural language processing has been used to extract features from operative records. This study aimed to evaluate the best natural language processing method for building a system that automatically detects some elements in the JOANR from the operative records of total hip arthroplasty. METHODS: We obtained operative records of total hip arthroplasty (n = 2574) in three hospitals and targeted two items: surgical approach and fixation technique. We compared the accuracy of three natural language processing methods: rule-based algorithms, machine learning, and bidirectional encoder representations from transformers (BERT). RESULTS: In the surgical approach task, the accuracy of BERT was superior to that of the rule-based algorithm (99.6% vs. 93.6%, p < 0.001), comparable to machine learning. In the fixation technique task, the accuracy of BERT was superior to the rule-based algorithm and machine learning (96% vs. 74%, p < 0.0001 and 94%, p = 0.0004). CONCLUSIONS: BERT is the most appropriate method for building a system that automatically detects the surgical approach and fixation technique.

Diagnostic accuracy of MRI for evaluating myometrial invasion in endometrial cancer: a comparison of MUSE-DWI, rFOV-DWI, and DCE-MRI.

OBJECTIVES: To compare the image quality of high-resolution diffusion-weighted imaging (DWI) using multiplexed sensitivity encoding (MUSE) versus reduced field-of-view (rFOV) techniques in endometrial cancer (EC) and to compare the diagnostic performance of these techniques with that of dynamic contrast-enhanced (DCE) MRI for assessing myometrial invasion of EC. METHODS: MUSE-DWI and rFOV-DWI were obtained preoperatively in 58 women with EC. Three radiologists assessed the image quality of MUSE-DWI and rFOV-DWI. For 55 women who underwent DCE-MRI, the same radiologists assessed the superficial and deep myometrial invasion using MUSE-DWI, rFOV-DWI, and DCE-MRI. Qualitative scores were compared using the Wilcoxon signed-rank test. Receiver operating characteristic analysis was performed to compare the diagnostic performance. RESULTS: Artifacts, sharpness, lesion conspicuity, and overall quality were significantly better with MUSE-DWI than with rFOV-DWI (p < 0.05). The area under the curve (AUC) of MUSE-DWI, rFOV-DWI, and DCE-MRI for the assessment of myometrial invasion were not significantly different except for significantly higher AUC of MUSE-DWI than that of DCE-MRI for superficial myometrial invasion (0.76 for MUSE-DWI and 0.64 for DCE-MRI, p = 0.049) and for deep myometrial invasion (0.92 for MUSE-DWI and 0.80 for DCE-MRI, p = 0.022) in one observer, and that of rFOV-DWI for deep myometrial invasion in another observer (0.96 for MUSE-DWI and 0.89 for rFOV-MRI, p = 0.048). CONCLUSION: MUSE-DWI exhibits better image quality than rFOV-DWI. MUSE-DWI and rFOV-DWI shows almost equivalent diagnostic performance compared to DCE-MRI for assessing superficial and deep myometrial invasion in EC although MUSE-DWI may be helpful for some radiologists.

Impact of MRI on the post-therapeutic diagnosis of T4 esophageal cancer.

BACKGROUND: Opportunities for T4b esophageal cancer patients to receive curative surgery are increasing with the development of multidisciplinary treatments. However, the best modality to accurately diagnose infiltration to the organs surrounding T4b esophageal cancer is still unknown. The aim of this study was to determine the performance of CT and MRI in diagnosing T stage in T4b esophageal cancer, with reference to the pathological diagnosis. METHODS: A retrospective medical records review of patients with T4b esophageal cancer patients from January 2017 to December 2021 was conducted. Among 125 patients who were treated for cT4b esophageal cancer in Osaka University Hospital, 30 patients were diagnosed with cT4b esophageal cancer by CT, ycT staging with CT (contrast-enhanced images) and MRI (T2-FSE images), and curative R0 resection was performed. Preoperative MRI staging was independently performed by two experienced radiologists. The diagnostic performance of CT and MRI were examined using McNemar's test. RESULTS: Nineteen and 12 patients were diagnosed with ycT4b by CT and MRI, respectively. Combined T4b organ resection was performed in 15 patients. A pathological diagnosis of ypT4b was made in 11 cases. In comparison to CT, MRI showed a higher diagnostic performance, specificity (47% vs. 89%, p = 0.013), and accuracy (60% vs. 90%, p = 0.015) for CT vs. MRI. CONCLUSIONS: Our results-with reference to the pathological diagnosis-revealed that MRI had a superior diagnostic performance to CT for diagnosing T4b esophageal cancer invading the surrounding organs. An accurate diagnosis of T4b esophageal cancer may facilitate the implementation of appropriate treatment strategies.

Traction Bronchiectasis/Bronchiolectasis on CT Scans in Relationship to Clinical Outcomes and Mortality: The COPDGene Study.

Background The clinical impact of interstitial lung abnormalities (ILAs) on poor prognosis has been reported in many studies, but risk stratification in ILA will contribute to clinical practice. Purpose To investigate the association of traction bronchiectasis/bronchiolectasis index (TBI) with mortality and clinical outcomes in individuals with ILA by using the COPDGene cohort. Materials and Methods This study was a secondary analysis of prospectively collected data. Chest CT scans of participants with ILA for traction bronchiectasis/bronchiolectasis were evaluated and outcomes were compared with participants without ILA from the COPDGene study (January 2008 to June 2011). TBI was classified as follows: TBI-0, ILA without traction bronchiectasis/bronchiolectasis; TBI-1, ILA with bronchiolectasis but without bronchiectasis or architectural distortion; TBI-2, ILA with mild to moderate traction bronchiectasis; and TBI-3, ILA with severe traction bronchiectasis and/or honeycombing. Clinical outcomes and overall survival were compared among the TBI groups and the non-ILA group by using multivariable linear regression model and Cox proportional hazards model, respectively. Results Overall, 5295 participants (median age, 59 years; IQR, 52-66 years; 2779 men) were included, and 582 participants with ILA and 4713 participants without ILA were identified. TBI groups were associated with poorer clinical outcomes such as quality of life scores in the multivariable linear regression model (TBI-0: coefficient, 3.2 [95% CI: 0.6, 5.7; P = .01]; TBI-1: coefficient, 3.3 [95% CI: 1.1, 5.6; P = .003]; TBI-2: coefficient, 7.6 [95% CI: 4.0, 11; P < .001]; TBI-3: coefficient, 32 [95% CI: 17, 48; P < .001]). The multivariable Cox model demonstrated that ILA without traction bronchiectasis (TBI-0-1) and with traction bronchiectasis (TBI-2-3) were associated with shorter overall survival (TBI-0-1: hazard ratio [HR], 1.4 [95% CI: 1.0, 1.9; P = .049]; TBI-2-3: HR, 3.8 [95% CI: 2.6, 5.6; P < .001]). Conclusion Traction bronchiectasis/bronchiolectasis was associated with poorer clinical outcomes compared with the group without interstitial lung abnormalities; TBI-2 and 3 were associated with shorter survival. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee and Im in this issue.

Identification of biomarkers of chronic kidney disease among kidney-derived proteins.

BACKGROUND: Chronic kidney disease (CKD) has few objective symptoms, and it is difficult to make an early diagnosis by using existing methods. Therefore, new biomarkers enabling diagnosis of renal dysfunction at an early stage need to be developed. Here, we searched for new biomarkers of CKD by focusing on kidney-derived proteins that could sensitively reflect that organ's disease state. METHODS: To identify candidate marker proteins, we performed a proteomics analysis on renal influx and efflux blood collected from the same individual. RESULTS: Proteomics analysis revealed 662 proteins in influx blood and 809 in efflux. From these identified proteins, we selected complement C1q as a candidate; the plasma C1q level was significantly elevated in the renal efflux of donors. Moreover, the plasma concentration of C1q in a mouse model of diabetic nephropathy was significantly increased, in association with increases in blood glucose concentration and urinary protein content. Importantly, we demonstrated that the tendency of C1q to increase in the plasma of CKD patients was correlated with a decrease in their estimated glomerular filtration rate. CONCLUSION: Overall, our results indicate that our approach of focusing on kidney-derived proteins is useful for identifying new CKD biomarkers and that C1q has potential as a biomarker of renal function.

MRI of Borderline Epithelial Ovarian Tumors: Pathologic Correlation and Diagnostic Challenges.

Borderline epithelial ovarian tumors are a distinct pathologic entity characterized by increased epithelial proliferation and nuclear atypia, but without frank stromal invasion. Borderline tumor (BT) is now considered to represent an intermediate phase in the stepwise progression from benign to malignant ovarian epithelial tumor. Since BTs commonly manifest at early stages in women of reproductive age and are associated with a good prognosis, making the correct diagnosis is important in determining whether a patient is a candidate for fertility-sparing surgery. There are six histologic BT subtypes (serous, mucinous, seromucinous, endometrioid, clear cell, and Brenner), and each has different MRI features, reflecting their unique histologic architectures. Radiologists should be aware of the MRI features that can suggest BTs. These features include a hyperintense papillary architecture with hypointense internal branching, which can be observed with serous and seromucinous BTs on T2-weighted images; aggregates of microcysts that have hypointensity on T2-weighted images and reticular enhancement on contrast-enhanced T2-weighted images, which can be seen with mucinous BTs; and moderately high signal intensity on diffusion-weighted images along with relatively high apparent diffusion coefficient values, which can be observed regardless of the histologic subtype. Nevertheless, because the imaging features of BTs overlap with those of many benign lesions (eg, cystadenoma and cystadenofibroma, decidualized endometriosis, and polypoid endometriosis) and malignant tumors (ovarian cancers and metastases), histologic confirmation is required for the final diagnosis. Special emphasis is placed on the MRI features of BTs, pathologic correlation, and the challenges related to diagnosis. ©RSNA, 2022.

Interstitial Lung Abnormalities at CT: Subtypes, Clinical Significance, and Associations with Lung Cancer.

Interstitial lung abnormality (ILA) is defined as an interstitial change detected incidentally on CT images. It is seen in 4%-9% of smokers and 2%-7% of nonsmokers. ILA has a tendency to progress with time and is associated with respiratory symptoms, decreased exercise capability, reduced pulmonary function, and increased mortality. ILAs can be classified into three subcategories: nonsubpleural, subpleural nonfibrotic, and subpleural fibrotic. In cases of ILA, clinically significant interstitial lung disease should be identified and requires clinically driven management by a pulmonologist. Risk factors for the progression of ILA include clinical elements (ie, inhalation exposures, medication use, radiation therapy, thoracic surgery, physiologic findings, and gas exchange findings) and radiologic elements (ie, basal and peripheral predominance and fibrotic findings). It is recommended that individuals with one or more clinical or radiologic risk factors for progression of ILA be actively monitored with pulmonary function testing and CT. To avoid overcalling ILA at CT, radiologists must recognize the imaging pitfalls, including centrilobular nodularity, dependent abnormality, suboptimal inspiration, osteophyte-related lesions, apical cap and pleuroparenchymal fibroelastosis-like lesions, aspiration, and infection. There is a close association between ILA and lung cancer, and many studies have reported an increased incidence of lung cancer, worse prognoses, and/or increased pulmonary complications in relation to cancer treatment in patients with ILA. ILA is considered to be an important comorbidity in patients with lung cancer. Accordingly, all radiologists involved with body CT must have sound knowledge of ILAs owing to the high prevalence and potential clinical significance of these anomalies. An overview of ILAs, including a literature review of the associations between ILAs and lung cancer, is presented. ©RSNA, 2022.

Spindle Cell Carcinoma of the Breast: Investigation of Magnetic Resonance Imaging Features of 26 Cases.

OBJECTIVE: The aim of the study was to retrospectively investigate the fat-saturated T2-weighted sequences (FST2WI) and 3-dimensional dynamic contrast-enhanced sequence (DCE) of magnetic resonance imaging (MRI) findings of breast spindle cell carcinoma (SpCC). METHODS: Twenty-six women with surgically confirmed breast SpCC, who underwent breast MRI in 2 institutions, were enrolled in this study (mean age, 54 years; range, 27-81 years). Two breast radiologists determined the MRI findings by consensus after independent interpretations. Each MRI finding was analyzed. RESULTS: Most lesions of SpCC showed a solitary mass (92.2%). Most masses were round/oval (76.0%), had an irregular margin (88.0%), rim enhancement (72.0%), washout kinetic analysis (96.0%), hyperintensity on FST2WI (84%), hyperintensity on FST2WI and fast enhancing component on DCE (56%), and hypointense rim on FST2WI (72.0%). CONCLUSIONS: Most breast SpCC showed a solitary mass, round/oval shape, irregular margin, rim enhancement, washout kinetics, and intratumoral hyperintensity on FST2WI; a hypointense rim on FST2WI; and hyperintensity on FST2WI and fast enhancing component on DCE.