ABSTRACT
BACKGROUND: Small echogenic renal masses are usually angiomyolipomas (AMLs), but some renal cell carcinomas (RCCs) can be echogenic and confused with an AML. OBJECTIVES: This is a study to evaluate any distinguishing demographic and sonographic features of small (<3 cm) peripheral AMLs versus peripheral RCCs. METHODS: This is a HIPAA-compliant retrospective review of the demographics and ultrasound features of peripheral renal AMLs compared with a group of peripheral RCCs. All AMLs had confirmation of macroscopic fat as noted on thin-cut CT or fat-saturation MRI sequence images. All RCCs were pathologically proven. Statistical analysis was used to compare findings in the two groups. RESULTS: There were a total of 52 patients with 56 AMLs, compared with 42 patients with 42 RCCs. There were 42 females in the AML group versus 10 females in the RCC group (P < .0001). The AML diameters (15.7 mm × 12.0 mm) were statistically significantly smaller (Plargest = .0085, Psmallest < .001) than the diameters of the RCCs (19.9 mm × 18.5 mm). Ultrasound features found to be statistically different between the two groups were the ratio of the largest dimension to the smallest dimension (P < .001), a lobulated versus smooth margin of the AML (26 vs 30) compared with the RCC group (3 vs 39) (P = .0012), and an "unusual" versus a round shape (P < .001) of the AML group (45 vs 11) compared with the RCC group (9 vs 33). In the multivariable model, the patient sex, margin, and mass shape were predictive of AML, with an area under the receiver operating characteristic curve of 0.92. CONCLUSION: For a small (<3 cm) peripheral echogenic mass in a female patient, a lobulated lesion with an unusual shape is highly predictive of being an AML.
Subject(s)
Angiomyolipoma , Carcinoma, Renal Cell , Kidney Neoplasms , Leukemia, Myeloid, Acute , Humans , Female , Carcinoma, Renal Cell/diagnostic imaging , Kidney Neoplasms/diagnostic imaging , Angiomyolipoma/diagnostic imaging , Angiomyolipoma/pathology , Sensitivity and Specificity , Diagnosis, Differential , Retrospective StudiesABSTRACT
Complex anatomy and a wide spectrum of diseases in the head and neck predispose interpretation of neck imaging to cognitive pitfalls and perceptual errors. Extra attention to common blind spots in the neck and familiarity with common interpretive challenges could aid radiologists in preventing these diagnostic errors.
Subject(s)
Head , Neck , Diagnostic Errors , Diagnostic Imaging , Humans , Neck/diagnostic imaging , RadiologistsABSTRACT
The objective of this study was to examine predictors of postdisaster major depression in two separate datasets of survivors of various disasters. Postdisaster major depression was examined in two disaster databases using consistent research methodology, permitting combination of databases into a combined dataset including 1181 survivors of 11 disasters representing all major disaster typologies with full diagnostic assessment using structured diagnostic interviews from two databases. The first database includes 808 directly-exposed survivors of 10 disasters. The second includes 373 survivors of the September 11, 2001 attacks on New York City's World Trade Center, recruited from employees of eight organizations affected by the disaster. This rich dataset permitted comparison of predictors of postdisaster major depression between databases and across survivors of different disasters. Identical models applied to both databases found postdisaster major depression to be independently associated with pre-existing major depression, indirect exposure to disaster trauma through family/friends, and disaster-related PTSD. In a final model limited to directly-exposed disaster across both databases, postdisaster major depression was independently associated with terrorism in addition to the 3 variables that predicted postdisaster major depression in the two separate databases. Replication of findings from one model to the next across different types of disasters and populations in this study suggests that these three variables could potentially provide a powerful tool for estimating likelihood of postdisaster major depression.