The power of this technology is that the medical images in the databases have corresponding case information. Thus, images that are found to be similar also provide information on patient diagnosis, treatments, outcomes, etc. This is particulary useful in oncology since, in more cases than you’d expect, pathologists disagree on whether a particular image shows cancer or not [1-3]. By comparing pathology images, the technology greatly accelerates the review process and allows a diagnosis to be more objective than what is currently done.

Check out their demo at the conference in the video below. James Gosling (the inventor of Java) was clearly impressed with the significance of the technology. Chris Boone, CEO and president of Visuvi, and Florian Brody, VP Marketing, highlighted and captured a section of an actual prostate cancer biopsy image and searched 90,000 images in 0.3 seconds to find related patient cases.

PathXchange is a not-for-profit professional networking portal for the global pathology community. PathXchange brings the field of pathology into the digital age with Web 2.0 features designed to promote exchange of pathological cases, knowledge and information, combining the elements of a case gallery, community content contribution and professional networking.

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References

1. Farmer et al. Discordance in the histopathologic diagnosis of melanoma and melanocytic nevi between expert pathologists. Hum Pathol. 1996 Jun;27(6):528-31.
   View abstract
2. Lettieri et al. Discordance between general and pulmonary pathologists in the diagnosis of interstitial lung disease. Respir Med. 2005 Nov;99(11):1425-30. Epub 2005 Apr 21.
   View abstract
3. Lodha et al. Discordance in the histopathologic diagnosis of difficult melanocytic neoplasms in the clinical setting. J Cutan Pathol. 2008 Apr;35(4):349-52.
   View abstract

Related articles

• Health 2.0 Highlights: November 1st, 2009
• Survival Rate Influences the Type of Web Communities Used by Cancer Patients

The new study, presented last month at the 2008 annual meeting of the North American Primary Care Research Group [2], evaluated the differences in emotional and informational social support content in online communities for cancers with low and high survival rates.

The researchers analyzed over 3,500 messages from 587 individuals in eight online support communities located within Yahoo!Groups and the Association of Cancer Online Resources (ACOR) websites for four different types of cancer with low or high five-year survival rates. Across all communities, there was a greater amount of emotional support than informational support.

High survival rate communities contained a greater proportion of emotional support than low survival rate communities (65% vs. 55%). In contrast, low survival rate communities contained a greater proportion of informational support than high survival rate communities (33% vs. 25%).

Participants in the study were members of support communities for four different types of cancer: lung cancer, melanoma, pancreatic cancer and thyroid cancer. They participated in eight different online communities and were all reviewed under the same time period.

According to the primary author of the study, Lorraine Buis, Ph.D. [3]:

When primary care providers refer individuals to online communities for support, they should be aware that there might be differing amounts of support based on the survival rate of a particular cancer.

According to the National Cancer Institute’s Surveillance Epidemiology and End Results (SEER) Cancer Statistics Review, which reports the most recent cancer incidence, mortality, survival, prevalence and lifetime risk statistics, from 1975 to 2005 cancer patients with thyroid cancer and melanoma of the skin had high survival rates (96.6% and 91.2% respectively) while lung cancer and pancreatic cancer had low survival rates (12.1% and 5.1% respectively) [4].

In addition to helping patients, online support communities help family and friends cope with the struggles that cancer presents. This is the first study to assess the influence of cancer patient survival rates on social support content in online communities for cancer.

A number of patient social networks are listed in the Highlight HEALTH Web Directory.

References

1. Buis et al. Relationship between cancer survival rate and social support within online communities for cancer. 2008 Annual Meeting of the North American Primary Care Research Group, Rio Grande, Puerto Rico.
2. 2008 Annual Meeting of the North American Primary Care Research Group (NAPCRG) Program. 2008 Nov 15 — 18.
3. Cancer survival rates impact type of Web communities used by patients. University of Michigan Health System press release. 2008 Nov 18.
4. SEER Cancer Statistics Review, 1975-2005, Age-adjusted SEER Incidence and U.S. Death Rates and 5-year Relative Survival Rates, National Cancer Institute. Bethesda, MD, based on November 2007 SEER data submission, posted to the SEER web site, 2008.

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• Digital Pathology and Visuvi Visual Search