PubMed · 6079307
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E Samuel. Mammography.. https://pubmed.ncbi.nlm.nih.gov/6079307/
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This study was undertaken to determine the discriminating cytological features between nonhigh-grade duct carcinoma in situ (NHGDCIS) and benign breast lesions and to determine any histological characteristics which would influence the cytological categorization. Smears of 12 each of histologically confirmed NHGDCIS and benign breast lesions were reviewed with regard to cellularity, cell discohesion, nuclear atypia, crowding of cells, tubule formation, necrosis, and presence of bare atypical nuclei and regular bare bipolar nuclei, and statistically analyzed. Architectural pattern, presence of necrosis, and the size of the lesion assessed at histological examination were compared with the initial cytological categorization. NHGDCIS lesions showed more cell discohesion (P = 0.04), bare atypical nuclei (P = 0.05), necrosis (P = 0.03), and sparse bare bipolar nuclei (P = 0.02) than benign lesions. These differences were statistically significant. Cellularity (P = 0.8), nuclear atypia (P = 0.06), crowding of cells (P = 0.1), and tubule formation did not show a significant difference. Six (out of six lesions) with a solid architectural pattern and six (of seven) with necrosis could be cytologically categorized as suspicious or malignant. Size of the lesion did not influence this. We conclude that cell discohesion, bare atypical and bare bipolar nuclei, and necrosis are discriminating features between NHGDCIS and benign breast lesions and NHGDCIS lesions with a solid architectural pattern and necrosis are more likely to be satisfactorily categorized cytologically.
Dynamic contrast-enhanced breast MR imaging was performed on 14 patients (five cancerous lesions, nine benign) with slice-selective spoiled gradient-recalled echo (2D SPGR) imaging. Adiabatic saturation recovery T(1) measurements were performed before (T(1pre)) and after (T(1post)) 2D SPGR imaging. These two "bookend" T(1) measurements were used to calibrate the equations which were employed to convert the time course of the 2D SPGR signal strength to T(1)-vs.-time, which in turn was used to compute the gadolinium concentration-vs.-time ([C](t)) in the lesion. The extraction-flow product (EF) was computed for each lesion by pharmacokinetic modeling of [C](t). For this study, EF provided a sensitivity and specificity for cancer of 100% and 78%, respectively. When only T(1pre) was used to estimate [C](t) (which assumes a priori knowledge of the shape and amplitude of the slice profile), the sensitivity and specificity fell to 80% and 56%, respectively. This is presumably due to unexpected variations in the shape and/or amplitude of the slice profile, which could be caused by factors such as patient-to-patient variations in breast geometry or inconsistently set transmit gains. Therefore, both T(1pre) and T(1post) measurements are necessary for optimum sensitivity and specificity using pharmacokinetic analysis.
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