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Wilbur, David

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Wilbur

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David

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Wilbur, David

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Now showing 1 - 7 of 7
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    HPV Reflex Testing in Menopausal Women
    (Hindawi Limited, 2011) Ko, Emily M.; Tambouret, Rosemary; Wilbur, David; Goodman, Annekathryn; ko, emily
    Objective. To determine the frequency of high risk (HR) HPV and intraepithelial neoplasia following ASCUS pap cytology screens in menopausal women. Study Design. Following IRB approval, we performed a retrospective review of all cases of ASCUS pap tests, HPV results, and relevant clinical-pathologic data in women age 50 or over from November 2005 to January 2007 within a tertiary care center. Statistical analyses were performed in EXCEL. Results. 344 patients were analyzed for a total of 367 screening pap tests. 25.29% (87/344) patients were HR HPV positive, with greater percentages of HR HPV cases occurring in women age 65–74. Within HR HPV cases, 79.3% (69/87) underwent colposcopy. 27.5% (19/69) biopsy proven lesions were discovered, including cervical, vulvar or vaginal (intraepithelial neoplasia). Within the negative HR HPV group 3.1% (8/257) patients were diagnosed with dysplasia or carcinoma. Within both HR HPV positive and negative groups, patients with no prior history of lower genital tract lesions or cancer were identified. Conclusion. Reflex HPV testing plays an important role in ASCUS triage in menopausal women. Pap test screening and HPV testing should not be limited to women of reproductive age as they may aid in the diagnosis of intraepithelial neoplasia in women of older age.
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    Case 10-2009: A 23-Year-Old Woman With an Abnormal Papanicolaou Smear
    (Massachusetts Medical Society, 2009-03-26) Goldstein, Mark; Goodman, Annekathryn; del Carmen, Marcela; Wilbur, David
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    Whole-Slide Imaging Digital Pathology as a Platform for Teleconsultation: A Pilot Study Using Paired Subspecialist Correlations
    (College of American Pathologists, 2009) Lauwers, Gregory Y.; Wilbur, David; Madi, Kalil; Colvin, Robert; Duncan, Lyn; Faquin, William; Ferry, Judith; Frosch, Matthew; Houser, Stuart L.; Kradin, Richard; Louis, David; Mark, Eugene; Mino-Kenudson, Mari; Misdraji, Joseph; Nielsen, Gunnlauger P.; Pitman, Martha; Rosenberg, Andrew Eric; Smith, R. Neal; Sohani, Aliyah; Stone, James; Tambouret, Rosemary; Wu, Chin-Lee; Young, Robert; Zembowicz, Artur; Wlietmann, Wolfgang
    Context.—Whole-slide imaging technology offers promise for rapid, Internet-based telepathology consultations between institutions. Before implementation, technical issues, pathologist adaptability, and morphologic pitfalls must be well characterized. Objective.—To determine whether interpretation of whole-slide images differed from glass-slide interpretation in difficult surgical pathology cases. Design.—Diagnostically challenging pathology slides from a variety of anatomic sites from an outside laboratory were scanned into whole digital format. Digital and glass slides were independently diagnosed by 2 subspecialty pathologists. Reference, digital, and glass-slide interpretations were compared. Operator comments on technical issues were gathered. Results.—Fifty-three case pairs were analyzed. There was agreement among digital, glass, and reference diagnoses in 45 cases (85%) and between digital and glass diagnoses in 48 (91%) cases. There were 5 digital cases (9%) discordant with both reference and glass diagnoses. Further review of each of these cases indicated an incorrect digital whole-slide interpretation. Neoplastic cases showed better correlation (93%) than did cases of nonneoplastic disease (88%). Comments on discordant cases related to digital whole technology focused on issues such as fine resolution and navigating ability at high magnification. Conclusions.—Overall concordance between digital whole-slide and standard glass-slide interpretations was good at 91%. Adjustments in technology, case selection, and technology familiarization should improve performance, making digital whole-slide review feasible for broader telepathology subspecialty consultation applications.
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    Computational Pathology to Discriminate Benign from Malignant Intraductal Proliferations of the Breast
    (Public Library of Science, 2014) Dong, Fei; Irshad, Humayun; Oh, Eun-Yeong; Lerwill, Melinda F.; Brachtel, Elena; Jones, Nicholas C.; Knoblauch, Nicholas W.; Montaser-Kouhsari, Laleh; Johnson, Nicole B.; Rao, Luigi K. F.; Faulkner-Jones, Beverly; Wilbur, David; Schnitt, Stuart; Beck, Andrew
    The categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools to aid pathologists in the characterization of these lesions would have great diagnostic and clinical value. As a first step to address this issue, we evaluated the ability of computational image analysis to accurately classify DCIS and UDH and to stratify nuclear grade within DCIS. Using 116 breast biopsies diagnosed as DCIS or UDH from the Massachusetts General Hospital (MGH), we developed a computational method to extract 392 features corresponding to the mean and standard deviation in nuclear size and shape, intensity, and texture across 8 color channels. We used L1-regularized logistic regression to build classification models to discriminate DCIS from UDH. The top-performing model contained 22 active features and achieved an AUC of 0.95 in cross-validation on the MGH data-set. We applied this model to an external validation set of 51 breast biopsies diagnosed as DCIS or UDH from the Beth Israel Deaconess Medical Center, and the model achieved an AUC of 0.86. The top-performing model contained active features from all color-spaces and from the three classes of features (morphology, intensity, and texture), suggesting the value of each for prediction. We built models to stratify grade within DCIS and obtained strong performance for stratifying low nuclear grade vs. high nuclear grade DCIS (AUC = 0.98 in cross-validation) with only moderate performance for discriminating low nuclear grade vs. intermediate nuclear grade and intermediate nuclear grade vs. high nuclear grade DCIS (AUC = 0.83 and 0.69, respectively). These data show that computational pathology models can robustly discriminate benign from malignant intraductal proliferative lesions of the breast and may aid pathologists in the diagnosis and classification of these lesions.
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    Whole Slide Imaging Based Digital Pathology Network between Pakistan and USA
    (Hindawi Publishing Corporation, 2014) Absar, Syeda Fatima; Tahir, Mohammad; Yagi, Yukako; Wilbur, David
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    MGH Whole Slide Imaging Teleconsultation Practice in Dermatopathology
    (Hindawi Publishing Corporation, 2014) Jones, Nicholas C.; Nazarian, Rosalynn; Duncan, Lyn; Wilbur, David
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    Case 32-2003 — a 37-Year-Old Woman With Atypical Squamous Cells on a Papanicolaou Smear
    (Massachusetts Medical Society, 2003-10-16) Goodman, Annekathryn; Wilbur, David
    Presentation of Case: A 37-year-old woman was referred to the colposcopy clinic because of two Papanicolaou smears showing atypical squamous cells of undetermined significance (ASC-US). One and two years previously, the patient had had Papanicolaou smears that were reported to be normal. Six months before referral, a routine pelvic examination revealed no abnormalities. A Papanicolaou smear at that time was interpreted as revealing ASC-US. The patient was reexamined three months later, and another Papanicolaou smear was again interpreted as showing ASC-US. The patient (gravida 5, para 4) had had one spontaneous first-trimester abortion.