Effectiveness of computer-aided diagnosis (CADx) of breast pathology using immunohistochemistry results of core needle biopsy samples for synaptophysin, oestrogen receptor and CK14/p63 for classification of epithelial proliferative lesions of the breast

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Abstract

Aims

The aim of this study was to develop a computer-aided diagnosis (CADx) system for identifying breast pathology.

Methods

Two sets of 100 consecutive core needle biopsy (CNB) specimens were collected for test and validation studies. All 200 CNB specimens were stained with antibodies targeting oestrogen receptor (ER), synaptophysin and CK14/p63. All stained slides were scanned in a whole-slide imaging system and photographed. The photographs were analysed using software to identify the proportions of tumour cells that were positive and negative for each marker. In the test study, the cut-off values for synaptophysin (negative and positive) and CK14/p63 (negative and positive) were decided using receiver operating characteristic (ROC) analysis. For ER analysis, samples were divided into groups with <10% positive or >10% positive cells and decided using receiver operating characteristic (ROC) analysis. Finally, these two groups categorised as ER-low, ER-intermediate (non-low and non-high) and ER-high groups. In the validation study, the second set of immunohistochemical slides were analysed using these cut-off values.

Results

The cut-off values for synaptophysin, <10% ER positive, >10% ER positive and CK14/p63 were 0.14%, 2.17%, 77.93% and 18.66%, respectively. The positive predictive value for malignancy (PPV) was 100% for synaptophysin-positive/ER-high/(CK14/p63)-any or synaptophysin-positive/ER-low/(CK14/p63)-any. The PPV was 25% for synaptophysin-positive/ER-intermediate/(CK14/p63)-positive. For synaptophysin-negative/(CK14/p63)-negative, the PPVs for ER-low, ER-intermediate and ER-high were 100%, 80.0% and 95.8%, respectively. The PPV was 4.5% for synaptophysin-negative/ER-intermediate/(CK14/p63)-positive.

Conclusion

The CADx system was able to analyse sufficient data for all types of epithelial proliferative lesions of the breast including invasive breast cancer. This system may be useful for pathological diagnosis of breast CNB in routine investigations.

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