Friday, July 18, 2008
I spent most of the time bouncing around between Floors 0, 2, and 4 of the Starr Building this week, and reinforcing what I have learned about cardiology and different kinds of imaging so far in the program. Got to ask the fellows, nurses, and techs in each department tons of questions, as well as getting a lot more interesting references and resources to read. It was also great to see the end of the tunnel for my immersion project, for which I now have a realistic timeline to complete the study and possibly a paper or an abstract.
This week, I'll write a little bit more about the software that's used in my project, the LVMetric Segmentor, which was developed at WCMC to speed up the segmentation process of cardiac images. Image segmentation provides a lot of important information, such as the chamber volume, blood mass, etc. which can be used as an indicator for certain diseases. In the past, doctors spend an awfully long time on each image case to segment myocardium from the chambers, while taking into account the papillary muscle mass, etc. For each patient's image, it can take anywhere from 4 to 10 minutes for an experienced doctor like Jonathan to segment the image profiles at the systolic and diastolic cardiac phases. LVMetric, on the other hand is very efficient, as it automates this segmentation process using some nifty image transforms and segmentation algorithms, and does it for all 25 or so different cardiac phases; in a matter of few seconds!
In addition to speeding up the process for doctors, the software can get data point at almost every cardiac phase; this allows us to study the temporal aspects of the chamber volume, etc. at each moment in the cardiac phase. We've recently added a new function to the program, so that it can output a decent amount of data from different cases that we examine. The remainder of my project starting Monday will be to organize, process, and analyze the volume curve for a number of these cases (Jonathan said it would be ~20 or so).
From this study, we are hoping to identify a quantitative indicator of certain physiological defects by analyzing quantitative data that I will work with. So it will be time to hit my Statistics textbooks hiding somewhere in my room next week (where are they?!). I'm really looking forward to wrapping up my project.
Finally, I got to follow Dr. Frayer on the rounds in the NICU this morning; I really must resonate Shawn and everybody else's earlier comments: man those babies are cute!
Wednesday, July 16, 2008
This is a 44-year-old breast cancer patient coming in with a bright blue scarf wrapped around head, which is undergoing hair loss due to the radiation therapy. I talked with her for a while she was waiting for the scan. Different from some other patients, I found her very cheerful throughout the short chat. Rattling super happily and proudly on her twins, she almost made me forget she was actually a cancer patient. The surprising thing happened at the time when I found out she actaully came to do an abdomen scan rather than a chest scan. Was this for checking the possible metastasis? I thought this way at first. But things just surprised me more when I gradually noticed the technicians paid more attention to some abdominal blood vessels. At last the most elucidating yet surprising thing came when I was told she was actually doing this scan for the susceptabilty test of a breast reconstruction surgery.
I know this is still confusing so let me explain more. Obviously this optimistic lady had not underwent a surgery to take out the breast cancer yet. She was doing the radiation therapy right now to suppress the cancer cells, so that they won't metastasize so easily post surgery. At the same time, she was also worried that she won't look so good after the excision of breast and DIEP Flap Breast Reconstruction technology came at the right time. Her surgeons planned to carry out two surgeries - mastectomy and breast reconstruction - on her at the same time, but before that, they need to make sure that her perforator vessels are still intact so that they are able to function as the internal mammary blood vessels later. She was very happy to learn the good news that day: her perforator vessels look super good even after the incision in C-section many years ago.
For me, this story totally refreshed my idea about the role of surgery in healthcare. In my old memory, surgery is always related with pain, wound and scar; surgery happens when medicine fails. However, this time just imagining nowadays patients can actually choose to combine resection with orthopaedics, I am totally overwhelmed. You can get cure and beauty at the same time - one stone two birds - isn't it fantastic?
Of course I understand that this technology must also be very controversial. Just like people would even argue whether this is worthy and safe to create an artificial beauty through orthopaedics, DIEP Flap Breast Reconstruction on a cancer patient is also risky. Recovery from two surgeries is definitely slower, not to mention the underlying risk to keep some breast tissues near lesions for better reconstruction. The fact is, ethic problems always come with healthcare. Nevertheless, the hope for benefiting more from medical technology never dies. Medical care is not all about elongating one's life. It also helps improving the quality of life, and the way we look at life and ourselves. There is nothing more important than that patients find health care help their lives and be happy about it. And I think the impressing part of this case just lies in that it teaches me the function of healthcare CAN be not only for physical well-being, but also spiritual welfare.
Tuesday, July 15, 2008
The next day I saw three plastic surgeries. These surgeons were sooo much less serious. They played music, joked around, and the head surgeon played peek-a-boo behind the door. In the first two surgeries there was a lot of manipulation of the skin. In one, the skin would be stretched over time, then excess skin would be used to replace scar tissue. In the other surgery, the woman needed a skin graft. I could see all the exposed muscle that they were covering up. She also had the biggest blister on her heel that I had ever seen. It looked like a giant diabetic blister or something.
Today I saw open heart surgery. They are right, it is intense. They bypassed the heart and lungs so that they could treat an aortic valve inefficiency. The blood went to a machine that acted as a heart. The resident said they would take a blood vessel from the leg and use it to replace one of the aortic vessels. It did not see the whole thing because I had other things to do.
I really want to learn as much about stereotactic surgical techniques from my clinician as possible, specifically on dissecting rats. He had me hook up with a woman in his lab who plans on doing stereotactic surgery. She said she had never done stereotactic surgery either. Not too encouraging. On the other hand, Yi stated clearly that this work is not meant to be for our theses.
I continued to work on the research protocol that Dr.Frayer says is junk. I was too lazy to change what I was doing and figured that at least I am learning a lot about neuroanatomy, something that is important to me in pursuing a neural engineering career. Now that I have learned about the neuroanatomy of drug addiction, I think about the reward circuit when I pop in snack foods and go out for a run. I have finished writing about the rationale now, so I don't know what he will have me do next.
Monday, July 14, 2008
So I missed a few days of the Immersion program teaching for a Math Camp in Montreal. For the summer camp, I was preparing a fun talk that discusses some ways that math can help in the clinical settings. While preparing this talk, I figured there was no better way than asking the immersion clinicians for ideas that I can talk about. So here it is:
As engineers, we often use mathematics as a set of tools for solving problems. From fluid dynamic models of blood flow, to certain clinical data analysis, there are numerous ways to use math in clinical settings. One topic that caught my attention, and fascinated me was the problem of how organ transplants are optimized at the local, regional, and national levels. There is an increasing trend of government funding for an efficient network called the Organ Procurement and Transplantation Network (OPTN). I've seen an analogous problem, (about the renal transplant network) last year in a mathematical modeling contest, and thought this would be a great problem to think about and ask around.
The topic of establishing an effective network is a difficult one, because of the many factors that must be incorporated in developing this model. As there are more organs sought after than there are available, there would usually be a significant waiting list for patients who need a new organ. One could try making a population dynamics model (using a system of ordinary differential equations) to get a holistic idea of how the waiting list behaves over the long course, but many indications suggest that we are all moving more towards larger and larger waiting lists in the future for almost all organs. Supply simply does not meet the demand.
One novel approach for resolving this situation was looking at donor-patient pairs. It is often true that exists a donor who is more than willing to donate an organ to a specific patient (which made sense in the case of a kidney), but the donor's kidneys are not compatible with the patient. If this is the case, it would make sense to establish a two-way exchange, so the two donors would trade their kidneys.
As a mathematician, one would like to generalize into establishing an n-way exchange, and finding a mathematically elegant solution that solves this optimization problem. However, from a clinical perspective, there are additional factors that need to be considered before we consider a similar exchange. First, suppose we establish an n-way exchange, but the chain breaks (eg. extraction fails) at some point. If this happens, what are the repercussions of such failure to the whole chain? One patient will not receive a sought after kidney due to the failure, while its donor, whose kidney is somewhat like a bargaining chip for acquiring his or her patient's new kidney, may break off; would this result in the entire chain of surgeries to fall apart? If so, will that mean that the all n transplants must happen simultaneously? Second is the feasibility of such cyclic surgeries; after all, these n-way exchanges require a lot of clinical manpower. Do most facilities have such capabilities? While it may be possible to model these intricacies using mathematics, it still won't address all the questions that clinicians may have.
Through summer immersion, I've learned that to address these problems properly, it would require more than mathematical problem-solvers developing models; a collaboration with clinical experts who work hands-on with these issues is a must. It is interesting to see where these considerations may lead to: NYP-Columbia Hospital was successful in having a 3-way exchange for the renal transplant recently in 2004, and this was a huge step forward.
Sunday, July 13, 2008
After hanging around enough during clinic I get to experience a more personal connection and understanding of each case that is presented. It is all well and good to pop into a surgery because the case is interesting or it is a procedure you haven’t seen before, but I really enjoy taking in the big picture. Going into an OR with a patient whom I have met, talked to, and begun to understand their mindset and choice for undergoing a particular type of surgery brings the experience to a whole new level. It is also incredibly gratifying to visit the patient while they recover in the hospital and then follow them as they come in for subsequent post-op visits. It still amuses me that some patients a day after surgery insist on asking how I am doing when they are the ones bandaged up in a hospital bed. I suppose this whole circle of care is what medicine is truly about and as a biomedical engineer I need to try not to forget to live up to the word medical in my title.
I spent most of my mornings this week rounding in the Pediatric ICU (PICU). It was a very interesting experience, having spent a couple of weeks in the neonatal ICU. In the neonatal ICU, the most common issues were nutrition/growth, respiratory distress, and cardiac problems. The cases in the PICU were a lot more varied and more complex. In one of the cases, a child was admitted for fever with irritability and inconsolable crying. But because the patient had such an extensive medical history (despite being so young), which included a repaired paraesophageal hiatus hernia , Lennox-Gastaut syndrome, and myoclonic seizures, it was difficult to diagnose whether the crying was a result of pain from the surgery or a neurological issues. It took an entire week, and consults from multiple departments and hospitals, to rectify the problem at admission. By the end of the week, the child was dramatically better and was due for discharge. It was really satisfying to experience the entire diagnosis process of a complex case that led to resolution of the problem.
In the past month, I've made some interesting observations regarding medical technologies in the hospital too through my time on the floor, and at various conferences. These are key considerations for any technology to be developed for patient care.
1) Mobility: There are so many patient transfers that go on in the hospital everyday - to and from surgeries/deliveries, across the floors, and between the units. It may seem somewhat trivial but the capability of a critical care device to function during transport is a huge deal. A company was promoting a new warmer for NICU with enhanced features, including procedure lights, motion sensors, hourglass heating, in-built sensors and respiratory aids, etc. The new features were exciting but in the end, it came down to whether the product could function at full capability (without wall power) in the time it takes to bring a baby from the delivery room to the ICU. It turned out that it was not able to do that by itself, and it was significant drawback. You can buy an additional universal power supply box at an exorbitant rate for 15min of offline power, but that may not always be sufficient.
2) Speed: This is where lab-on-a-chip technologies will come in. It is surprising to know how the results a relatively simple genetic test can take several weeks to return. This can be dangerous for a patient that requires immediate treatment based on a positive result of the test. This is a very real issue, and there are already lab-on-a-chip technologies used in the hospital. If you look around, you may notice that the blood gases of the patient are obtained at the bedside.3) Accuracy & Verification: I learnt in a conference that dosing errors are very common in any hospital. Usually, the error is noted before it causes any irreparable damage but sometimes it is not. The source of this error is either from the human (doctor, pharmacist, nurse etc.) or from the machine (dosing and prescription order systems). Fortunately, there are checks that go on at each level to make sure the prescription is right. It would be great if there was a system that could somehow eliminate all the forms of dosing errors.