Acute Disease ; Adolescent ; Adult ; Child ; Humans ; Leukemia ; diagnosis ; drug therapy ; Neoplasm, Residual ; Remission Induction

Blood Cells ; cytology ; Bone Marrow Cells ; cytology ; China ; Hematologic Tests ; standards ; Humans

China ; Clinical Laboratory Techniques ; Humans ; Myelodysplastic Syndromes ; diagnosis

Humans ; Leukemia, Large Granular Lymphocytic

Child ; Humans ; Myelodysplastic Syndromes ; classification ; diagnosis ; Pediatrics ; World Health Organization

Fibroblast Growth Factors ; metabolism ; Humans ; Phosphorus ; metabolism

Integrative Medicine ; Professional Competence

Objective To investigate radionuclide imaging and routine CT in diagnosing hepatic focal nodular hyperplasia (FNH) and the combined diagnostic value of the two modalities. Methods Thirty-two patients with hepatic FNH were retrospectively studied. All patients underwent routine CT scan. Twenty-four patients were examined by 99Tcm-sulfur colloid (SC) hepatic planar scintigraphy and SPECT/CT imaging, and then patients who had abnormal foci underwent 99Tcm-diethyl iminodiacetic acid (EHIDA) triple-phase hepatobiliary imaging. x2 -test of four-table or Fisher exact probabilities in 2 × 2 table was applied for statistical analysis. Results Of all 32 patients pathologically diagnosed as FNH with single solitary nodule, 25 were classified as classic type and the rest 7 as non-classic type. Although routine CT found all hepatic lesions, only 15 cases were diagnosed pathologically as FNH classic type but the rest were either misdiagnosed or left as indeterminate. On radionuclide imaging (hepatic colloid scintigraphy plus triple-phase hepatobiliary images), 11 patients with big foci (with maximal diameter ＞3 cm) out of 24 patients were correctly diagnosed as FNH, with 7 diagnosed as classic type FNH and 4 as non-classic. Other 13 patients were either misdiagnosed or simply missed. The diagnosing rates of routine CT and radionuclide imaging were60.0% (15/25) and 38.9% (7/18) for FNH classic type, 0/7 and 4/6 for non-classic type,50.0% (10/20) and 73.3% (11/15) for big foci, 41.7% (5/12) and 0/9 forsmall foci (with maximal diameter≤3 cm), respectively. The total diagnosing rate of radionuclide imaging combined with routine CT was significantly higher than that of routine CT or radionuclide imaging alone ( x2 = 4. 48, P ＜ 0. 05;x2 =4.27, P ＜0.05 ). Conclusion Radionuclide imaging in combination with routine CT may improve the diagnostic accuracy for hepatic FNH patients.

AIM: To detect the serum proteomic patterns in patients of breast cancer by the method of SELDI-TOF-MS and CM10 ProteinChip, and to screen the biomarker candidates, build and validate the diagnostic models, and evaluate its clinical value in surveillance and follow-up after operation. METHODS: The SELDI-TOF-MS technology and CM10 ProteinChip were used to detect the proteomic patterns of serum from 63 breast cancer patients and 40 healthy women. The biomarker candidates were screened and the diagnostic models were constructed by ZJU-PDAS software. Meanwhile, the model was blind-validated in another 23 patients and 20 healthy women. At the same time, 16 serum samples were detected to evaluate its value in surveillance and follow-up after operation. RESULTS: The best model was composed by two protein peaks (BC1/3.9 kD and BC2/5.6 kD) with its sensitivity and specificity of 87.30% (55/63) and 95.00% (38/40), respectively. The sensitivity and specificity in the blind-validation of new cases were 95.65% (22/23) and 85.00% (17/20), respectively. The diagnostic efficacies were the same to the patients of different stages (P>0.05). The expression of BC1 increased while BC2 decreased after operation. The expression of BC2 in the patients with recurrence or metastasis was higher than that in the tumor-free survivors (P<0.05). CONCLUSION: This method shows its potential in detection, surveillance and follow-up after operation. The method is also useful for screening the novel and better biomarkers in breast cancer.

Cardiovascular Diseases ; enzymology ; metabolism ; Humans ; Poly(ADP-ribose) Polymerases