Sparganosis Presenting as a Mammographic Abnormality

2013 ◽  
Vol 20 (1) ◽  
pp. 92-94 ◽  
Author(s):  
Rondell P.D. Graham ◽  
Bobbi S. Pritt ◽  
Katrina N Glazebrook ◽  
Sejal Shah
2011 ◽  
Vol 197 (3) ◽  
pp. 764-764 ◽  
Author(s):  
Ferris M. Hall ◽  
Tejas S. Mehta ◽  
David Magaram

1993 ◽  
Vol 79 (6) ◽  
pp. 422-426 ◽  
Author(s):  
Angelo Paradiso ◽  
Annita Mangia ◽  
Anna Barletta ◽  
Francesco Marzullo ◽  
Vincenzo Ventrella ◽  
...  

Aims A comparative analysis was performed to verify a possible correlation between mammographic features and morphobiologic characteristics of the tumor in a series of 176 invasive primary breast cancer patients. Methods Breast cancers were grouped according to mammographic features as follows: tumor mass with spiculated borders; tumor mass with well-circumscribed borders; tumor with density alteration of parenchyma with no clear borders; a cluster of micro-calcifications as the only sign of tumor presence; tumor without mammographic abnormality. The tumor tissue biologic characteristics investigated were: hormone receptor content, tumor proliferative activity, DNA content and cytohlstologic tumor-grade differentiation. Results Spiculated tumors showed a significantly higher percentage of estrogen-receptorpositive cases with respect to circumscribed tumors, independently of the patient's menopausal status. Tumors with only microcalcifications were all from premenopausal patients and showed a significantly higher percentage of progesterone-receptor-positive cases (83 %). Tumor proliferative activity did not significantly differ in the 5 mammographic breast cancer groups; aneuploidy was less frequent in tumors with spiculated borders than in mammographic types (39 % vs 57 %; p = 0.05); percentages of G1-G2-G3 tumors did not differ significantly among the mammographic groups considered. Conclusions Certain relationships between mammographic features and biologic characteristics could be of potential clinical interest and stimulate more detailed studies on this issue.


1999 ◽  
Vol 86 (7) ◽  
pp. 851-852 ◽  
Author(s):  
M. J. Kerin ◽  
J. R. T. Monson

2000 ◽  
Vol 87 (3) ◽  
pp. 374-374
Author(s):  
C. Zammit ◽  
C. Yiangou ◽  
H. D. Sinnett

2016 ◽  
Vol 27 (2) ◽  
pp. 553-561
Author(s):  
Rob van Bommel ◽  
Adri C. Voogd ◽  
Marieke W. Louwman ◽  
Luc J. Strobbe ◽  
Dick Venderink ◽  
...  

1996 ◽  
Vol 167 (1) ◽  
pp. 17-19 ◽  
Author(s):  
R J Brenner ◽  
L Berlin

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15533-e15533
Author(s):  
Virginia A. Espina ◽  
Ngoc Vuong ◽  
Alessandra Luchini ◽  
Claudius Mueller ◽  
Denitra S Mack ◽  
...  

e15533 Background: Biomarker identification for early breast cancer diagnosis is confounded by comparing healthy control patients to patients undergoing surgical procedures and stress of a potential cancer diagnosis. We implemented a clinical research protocol that combines biomarker harvesting and identification with Breast Imaging-Reporting and Data System (BIRADS) results, within a cohort of women with a suspicious mammogram who donated samples prior to biopsy. The primary goals were to discover candidate novel plasma markers for stage I breast cancer versus benign lesions, and validate the markers by mass spectrometry and immunohistochemistry. Methods: 150 women found on screening mammography to have a BIRADS IV or V mammographic abnormality were enrolled in the IRB approved study, with one year follow-up. After informed consent, serum, plasma, and saliva specimens were obtained and frozen. The patient underwent image guided biopsy of the mammographic abnormality. Hydrogel nanoparticles were used to harvest and concentrate low abundance protein biomarkers from plasma. Proteins were identified by mass spectrometry. The BIRADS score and biopsy outcome were blinded to the laboratory researchers. Results: 37/150 women (median age 64, 73% ER+, 70% PR+) were diagnosed with biopsy-proven breast cancer. 15/37 had a family history of breast cancer. Within the context of stress of an abnormal mammogram and invasive biopsy, we identified 5478 plasma peptides. A model to predict endpoints that discriminate cancer vs no cancer was developed using cross-validation and lasso shrinkage method. The best fit multi-analyte ROC/AUC model of peptide spectral matches revealed 10 candidate peptides, including PLAA, TRAPPC9, PROS1, DDX41, ANKRD63, EGFLAM (AUC = 0.81), that discriminated cancer versus no cancer. The functional mechanisms of these proteins are calcium metabolism, GPI anchor biosynthesis, neural-immune crosstalk, DNA repair, and ubiquitin-mediated protein trafficking. Conclusions: Molecular profiling of blood can potentially complement imaging to improve diagnostic specificity in the setting of a suspicious mammogram. This unique trial design, enhanced by nanotechnology protein harvesting, identified potential novel cancer biomarkers in the presence of a suspicious mammogram. A confirmation trial is underway.


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