There is increasing recognition of heterogeneity within tumors of many different tissues,
16 including heterogeneity within DCIS of the breast.
16,17 This study extends the previous observations on intratumoral heterogeneity of DCIS by documenting that quantitative differences can exist even between ducts that appear to have the same nuclear grade.
We compared image features for nuclei in ducts with the same nuclear grade within the same patient and found statistically significant differences. Also, differences were detected between ducts of the same nuclear grade in different patients, in which one patient had a single grade and the other patient had more than one grade. Image analysis of digital images of biopsy specimens was able to extract quantitative subvisual information about nuclei that was found to be statistically different.
The high replicability of repeated measurements of nuclear features by image analysis implies that the statistically significant differences reported in this study are unlikely to be due to measurement error, but rather represent real differences between nuclei.
Nuclear grade has been found to be associated with both risk of DCIS recurrence,
3,19,20 and progression to invasive carcinoma.
19,21 Based on such results, nuclear grade is a required component of the pathologic evaluation and reporting of DCIS.
1,22 Traditional nuclear grading depends on visual inspection and subjective judgement. Image cytometry can detect additional subvisual information and the extracted data is amenable to objective statistical analysis. This additional information has been used in the assessment of biopsy specimens of many tissues, including
in situ and invasive carcinoma of the breast.
21,23–31 In previous studies, we showed that image cytometric features were significantly associated with risk of DCIS recurrence,
11 and development of invasive cancer.
12Here we show that image cytometry can characterize interductal heterogeneity, the difference between ducts with the same nuclear grade. Since nuclear grade is one of the factors considered in the management of DCIS,
32–34 not accounting for interductal heterogeneity may have clinical implications. This may explain the lack of association between nuclear grade and patient outcome in a previous report.
4Interductal heterogeneity also has implications for studies of DCIS at the molecular and cellular levels. Some of these studies are based on analysis of a single patient sample, either a mixture of cells from a “representative” region, or a small number of selected cells from a region obtained by laser capture microdissection. Several studies have compared DCIS to normal tissue, to invasive carcinoma, or to metastatic carcinoma from the same patient by gene expression,
35–39 protein expression,
40 microsatellite markers,
40,41 loss of heterozygosity,
43,44 gene amplification or deletion (CGH),
45,46 and nuclear image features.
29 Many of these studies included paired samples of DCIS and other lesions from the same patient; however, it is often not clear how many samples of DCIS were assessed and therefore whether the sampling method would account for the kind of interductal heterogeneity reported here. Without characterizing multiple samples from different ducts from the same patient, it is not clear if the differences found between the single DCIS sample and the other invasive or metastatic lesion of the same patient would also have been found between multiple samples of DCIS of the same patient.
Interductal heterogeneity can also be a concern in analysis of samples in tissue microarrays. Tissue microarrays often include multiple samples from the same patient. The reproducibility of measurements of pairs of samples has been demonstrated.
47,48 However, if the samples analyzed in tissue microarrays come from the same region of tissue, these samples may not reflect the heterogeneity existing in the patient’s tumor.
49Our results suggest that studies of DCIS at the molecular and cellular levels should incorporate analysis of multiple samples from different areas of tissue demonstrating DCIS in order to account for the range of molecular and cellular diversity that may exist between the different ducts within each patient.
In summary, digital image analysis, previously used to quantitatively characterize premalignant and malignant specimens, may reveal subvisual information useful for diagnosis and prognosis of breast and other tumors. In this communication, we used image analysis to reveal heterogeneity between ducts of breast DCIS of the same nuclear grade.