In our last article, we took a look at the amazing Zstack technology that is allowing microscopic images obtained using confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). If you missed out on that article, you can read it HERE. However, this is such an important step for augmented reality to take that we couldn’t cover all of it in just one article, so we needed a second post to analyze the present and future implications of this tech in healthcare.
The possibilities are endless for clinical research and practice, and we’ll talk about those later, but we at ARinMED obviously want to talk about the applications for it in medicine. We think that medical education can stand to benefit the most. Can you picture a whole classroom examining microscopic dissections using the power of AR? New teaching methods could be developed around it, where the students could interact with the cell group during class and even ask questions and make comments to their professor in real time, pinpointing exactly what needs clarification. Obviously, having an entire classroom using head mounted devices is an expensive proposal, but that’s not the only way to do it–a mixed reality projection system might not be too far off on the horizon.
Education is surely a place where this technology could be useful, but the possibilities don’t end there. Clinical practice could use it, too. One problem that patients and doctors face today is false negative results from main core biopsies. There are no definitive numbers for all main core biopsies, but in one study of breast cancer, over 2% of all the 998 biopsies presented false negatives, and for others, it can be much higher–up to 8.9% when certain methods of core biopsy are used. These numbers might not sound too high, but false negative results often delay treatment for patients, allowing metastasis of the cancer, especially in more aggressive forms. The Zstack technology could be the key to earlier diagnosis of cancers, if it’s applied to clinical histology, by allowing the physician to navigate through the 100% of the biopsy sample, establish new protocols and signs to determine malignancy, like they already do for mammography assessment.
This is obviously a massive task, and could take a long time. However, by incorporating a system that could help us detect the parameters of the most common malignancies through computer algorithms, we could have a much faster and safer diagnostic method available for patients. As for medical research, currently histological cuts need to be compared in order to determine a diagnosis or group of diagnoses, and and the Zstack system could do that automatically, allowing a much quicker analysis with better results for patients.
The research itself points out several more uses for the Zstack, including neurosurgical planning for microsurgery, which has our full attention. Certainly it must be applied to many more microscopic cuts in order to determine its feasibility for human use, but we at ARinMED are going to be following this system closely, because we believe it’s going to do great things in the future!
What do you think of the Zstack? Could it open doors for research and clinical practice? Let us know your thoughts in the comments section!