Purpose: To determine the reference site for relative apparent diffusion coefficient (rADC) and to evaluate the benefit of rADC for detecting metastatic lymph nodes in uterine cervical cancer. Materials and Methods:Two observers independently measured ADCs in the spleen, liver, renal cortex, lumbar spine, lumbar spinal cord, and gluteus maximus on diffusion-weighted images (b value, 0 and 1000 mm/sec 2 ) in 50 patients. The reference site for rADC was determined using the intra-and interobserver coefficient of variation (CV) of ADC in these organs. rADC was calculated by ADC lesion / ADC reference site . The benefit of rADC over ADC was validated by comparing the area under the receiver operating curve for identifying metastatic lymph nodes in uterine cervical cancer in 130 patients. Results:The renal cortex was determined to be the reference site for rADC, as its CVs (intraobserver, 5%-7%; interobserver, 5%) were less than those of the other organs (P Ͻ 0.05). The ADC and rADC of metastatic lymph nodes (n ϭ 29, ADC, 0.7483 ϫ 10 Ϫ3 mm 2 /sec; rADC, 0.3832) were less than those of nonmetastatic lymph nodes (n ϭ 229, ADC, 0.9960 ϫ 10 Ϫ3 mm 2 /sec; rADC, 0.5383) (P Ͻ 0.05). The area under the receiver operating characteristics curve for differentiating metastatic from nonmetastatic lymph nodes was greater for rADC (0.914; 95% confidence interval [CI], 0.872-0.945) than for ADC (0.872; 95% CI, 0.825-0.910) (P ϭ 0.007). Conclusion:The renal cortex is an appropriate reference site for rADC and rADC may improve the accuracy for diagnosing metastatic lymph nodes in uterine cervical cancer.

Bone involvement is an unusual manifestation of secondary syphilis, but little information is available in the English-language literature. We carried out a systematic review of the English-language literature from 1964 to 2013, describing cases of secondary syphilis with bone involvement. We also describe a case of secondary syphilis with multiple osteolytic lesions, mimicking metastatic cancer or myeloma, which was included in an analysis of 37 eligible cases of secondary syphilis with bone involvement. Of these 37 patients, 28 (76%) patients were male, and the median age was 32 years (range, 12-64 years). Eleven (30%) patients had human immunodeficiency virus (HIV) infection with a median CD4 lymphocyte count of 343 cells/mm (range, 130-689 cells/mm). The diagnosis of early syphilis was suspected based on mucocutaneous findings in 28 (76%) cases. In the remaining 9 (24%) cases, high titers of nontreponemal serologic tests were the only evidence of early syphilis. The median venereal disease research laboratory (VDRL) titer was 1:64 (range, 1:8-1:320), and median rapid plasma reagin (RPR) titer was 1:64 (range, 1:16-1:512). The bones most often affected were long bones of the limbs (n = 22) and skull (n = 21). The bone lesions were multifocal in 27 (73%) cases and osteolytic in 19 (51%) cases. The treatment of syphilitic bone lesions was medical only in most patients, and prognosis was favorable with high-dose penicillin therapy. Clinical features and outcome between HIV-uninfected and HIV-infected patients were not different. Knowledge of this rare entity may lead to early diagnosis and appropriate management.

ObjectiveThis study was designed to develop an automated system for quantification of various regional disease patterns of diffuse lung diseases as depicted on high-resolution computed tomography (HRCT) and to compare the performance of the automated system with human readers.Materials and MethodsA total of 600 circular regions-of-interest (ROIs), 10 pixels in diameter, were utilized. The 600 ROIs comprised 100 ROIs that represented six typical regional patterns (normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation). The ROIs were used to train the automated classification system based on the use of a Support Vector Machine classifier and 37 features of texture and shape. The performance of the classification system was tested with a 5-fold cross-validation method. An automated quantification system was developed with a moving ROI in the lung area, which helped classify each pixel into six categories. A total of 92 HRCT images obtained from patients with different diseases were used to validate the quantification system. Two radiologists independently classified lung areas of the same CT images into six patterns using the manual drawing function of dedicated software. Agreement between the automated system and the readers and between the two individual readers was assessed.ResultsThe overall accuracy of the system to classify each disease pattern based on the typical ROIs was 89%. When the quantification results were examined, the average agreement between the system and each radiologist was 52% and 49%, respectively. The agreement between the two radiologists was 67%.ConclusionAn automated quantification system for various regional patterns of diffuse interstitial lung diseases can be used for objective and reproducible assessment of disease severity.