We aimed to evaluate and compare the growth patterns among pathological types of indeterminate subsolid nodules in patients without a history of cancer as observed on computed tomography (CT). METHODSThis retrospective study included 77 consecutive patients with 80 indeterminate subsolid nodules on unenhanced thin-section CT. Subsolid nodules were classified into 2 growth pattern groups based on volume: growth (n = 35) and non-growth (n = 42). According to the pathological diagnosis, subsolid nodules were further subdivided into 3 groups: adenocarcinoma in situ (growth, n = 8 vs. non-growth, n = 22), minimally invasive adenocarcinoma (n = 14 vs. n = 15), and invasive adenocarcinoma (n = 13 vs. n = 5). Kaplan-Meier and Cox proportional hazards regression analyses were performed to identify the risk factors for subsolid nodules growth. The CT findings of the 35 subsolid nodules in the growth group were compared among the 3 pathological groups. RESULTSIn the growth group, the overall mean volume doubling time and mass doubling time (MDT) were 811.5 days and 616.5 days, respectively. Patient's age (odds ratio = 1.041, P = .045) and CT subtype of non-solid nodule and part-solid nodule (odds ratio = 3.430, P = .002) could predict subsolid nodule growth. The baseline volume, mass, and mean CT value were larger in the invasive adenocarcinoma group than in the adenocarcinoma in situ group (all P < .01). The shortest volume doubling time was observed in the invasive adenocarcinoma group, followed by the minimally invasive adenocarcinoma group and the adenocarcinoma in situ group. A shorter mass doubling time was observed in the minimally invasive adenocarcinoma group than in the adenocarcinoma in situ group (all P < .02). CONCLUSIONAs age increases, the risk of pulmonary subsolid nodule growth increases by 4% each year, and part-solid nodules have a 3 times higher risk of growth compared to non-solid nodules in patients with no history of cancer. Subsolid nodules with more aggressive pathological characteristics grow at a faster rate. I ncidentally detected pulmonary subsolid nodules (SSNs) can commonly present as indeterminate nodules on chest computed tomography (CT) in routine workflows. Pulmonary SSNs can be divided into non-solid nodules (NSNs) and part-solid nodules (PSNs) according to the absence or presence of internal solid components on thin-section CT, respectively. 1,2 Subsolid nodules can be benign or malignant; most benign SSNs can be radiologically diagnosed based on whether the lesion resolves on follow-up CT scans, while a few persistent SSNs must be surgically confirmed as focal organizing pneumonia and non-specific interstitial fibrosis. 3 Pulmonary SSNs that persist after a follow-up period of 3-6 months have a high likelihood of being premalignant or malignant lesions, and many authors consider persistent SSNs to represent early-stage adenocarcinoma or its precursor. [3][4][5] However, it is still important to determine the following: (1) the growth patterns of radiologically malignant SSNs, (2) what g...
Purpose To evaluate the accuracy of pulmonary nodule (PN) detection in overweight or obese adult patients using ultralow‐dose computed tomography (ULDCT) with tin filtration at 100 kV and advanced model‐based iterative reconstruction (ADMIRE). Methods Eighty‐one patients with body mass indices of ≥25 kg/m2 were enrolled. All patients underwent low‐dose chest CT (LDCT), followed by ULDCT. Two radiologists experienced in LDCT established the standard of reference (SOR) for PNs. The number, type, size, and location of PNs were identified in the SOR. Effective dose, objective image quality (IQ), and subjective IQ based on two radiologists’ scores were compared between ULDCT and LDCT. The detection performances of radiologists based on ULDCT were calculated according to the nodule analyses. Logistic regression was used to test for independent predictors of PN detection sensitivity. Results Both the effective dose and objective IQ were lower for ULDCT than for LDCT (both p < 0.001). Both radiologists rated the subjective IQ of the overall IQ on ULDCT to be diagnostically sufficient. In total, 234 nodules (mean diameter, 3.4 ± 1.9 mm) were classified into 32 subsolid, 149 solid, and 53 calcified nodules according to the SOR. The overall sensitivity of ULDCT for nodule detection was 93.6%. Based on multivariate analyses, the nodule types (p = 0.015) and sizes (p = 0.013) were independent predictors of nodule detection. Conclusions Compared with LDCT, ULDCT with tin filtration at 100 kV and ADMIRE could significantly reduce the radiation dose in overweight or obese patients while maintaining good sensitivity for nodule detection.
BACKGROUND We present a rare case of plasma cell type of Castleman’s disease (CD) involving only the right renal sinus in a 65-year-old woman with a duplex collecting system (DCS). CASE SUMMARY The patient presented with a right renal sinus lesion after renal ultrasonography. Subsequent abdominal enhanced computed tomography (CT) and magnetic resonance imaging (MRI) of the kidneys showed DCS and a soft tissue mass with mild enhancement at the lower right renal sinus. The lesion was suspected to be a malignant renal pelvic carcinoma. Hence, the patient underwent a right radical nephrectomy. Histological examination revealed hyperplastic lymphoid follicles in the renal sinus. A detailed review of the patient’s CT and MRI images and a literature review suggested that the lesion was hypointense on T2-weighted images and hyperintense on diffusion-weighted image manifestations, and showed mild enhancement, which distinguished the plasma cell type of CD from many other renal sinus lesions. Furthermore, peripelvic soft tissue masses with a smooth internal surface of the renal pelvis were on imaging findings, which suggests that the urinary tract epithelial system is invulnerable and can be used to differentiate the plasma cell type of CD from malignant lymphoma with a focally growth pattern to some extent. CONCLUSION Preoperative diagnosis is often difficult in such cases, as plasma cell type of CD involving only the right kidney is exceedingly rare. However, heightened awareness of this disease entity and its radiographic presentations may alert one to consider this diagnosis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.