Software in development may double cancer diagnosis certainty
In pathology, cells and cell nuclei are usually examined using microscopy to view biomarker expressions in tumors—analysis that can help determine, for example, treatment options for patients who have cancer.
In pathology, cells and cell nuclei are usually examined using microscopy to view biomarker expressions in tumors—analysis that can help determine, for example, treatment options for patients who have cancer. The certainty of the diagnosis depends greatly on the individual pathologist. A study led by Lukas Kenner at the Medical University of Vienna's (MedUni Vienna) Clinical Institute of Pathology, as well as at the Ludwig Boltzmann Institute for Cancer Research (LBI-CR) and the VetMedUni Vienna, all in Austria, has demonstrated that two independent pathologists only agreed on one in three diagnoses. Also part of the study is new computer software that has been developed jointly, which may help to someday double diagnostic certainty.
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In the study, the scientists investigated and analyzed 30 liver cell carcinomas and were able to classify them into categories ranging from "negative" to "strongly positive" using the software developed jointly by the MedUni Vienna and the Vienna-based firm Tissuegnostics.
The study measured the expression of the proteins STAT5AB and JUNB in an aggressive T-cell lymphoma. The software uses certain algorithms and highly sensitive digital photography, enabling it to represent the matrix of cells and the cell nucleus better than under the microscope. STAT5 plays an important role in the development of leukemia and liver cancer. The JUNB gene is involved in the development of tumors in lymph gland tissue.
"The new program of course does not make pathologists redundant; however, it is a supplementary method that considerably increases diagnostic certainty," says Kenner. The MedUni Vienna expert also anticipates that the new technology will contribute to the changes in cancer cells, which are currently classified into four categories, being specified in much more detail in the future. It also may someday be possible to create much more detailed categories, giving clinicians a further tool with which to choose the correct and tailored therapy option.
"Cancer therapies are expensive. This new software will also help us to assess more effectively where expensive therapy is justified, but also which cases do not need it, thereby also sparing the patient," says Kenner.
Full details of the work appear in the journal PLoS One; for more information, please visit http://dx.doi.org/10.1371/journal.pone.0100822.
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