I'm a Healthy Young Woman: Here's Why I Would Get Tested for Alzheimer's Now
Editor's Note: A team of researchers in Italy recently used artificial intelligence and machine learning to diagnose Alzheimer's disease on a brain scan an entire decade before symptoms show up in the patient. While some people argue that early detection is critical, others believe the knowledge would do more harm than good. LeapsMag invited contributors with opposite opinions to share their perspectives.
Alzheimer's doesn't run in my family. When my father was diagnosed at the age of 58, we looked at his familial history. Both his parents lived into their late 80's. All of their surviving siblings were similarly long-lived and none had had Alzheimer's or any related dementias. My dad had spent 20 years working for the United Nations in the 60's and 70's in Africa. He was convinced that the Alzheimer's had come from his time spent in dodgy mines where he was exposed without the proper protections to all kinds of chemical processes.
Maybe that was true. Maybe it wasn't. The theory that metals, particularly aluminum, is an environmental factor leading to Alzheimer's has been around for a while. It's mostly been debunked, but clearly something is causing this epidemic as the vast majority of the cases in the world today are age-related. But no one knows what the trigger is, nor are we close to knowing.
If my father had had the Alzheimer's gene, I would go get myself checked for it. If some new MRI were commercially available to scan my brain and let me know if I was developing Alzheimer's, I would also take that test. There are four reasons why.
First, studies have shown that lifestyle has a major impact on the disease. I already run three miles a day. I eat relatively healthily. But like anyone, I don't live strictly on boiled chicken and broccoli. And I definitely enjoy a glass of wine or two. If I knew I had a propensity for the disease, or was developing it, I would be more diligent. I would eat my broccoli and cut out my wine. Life would be less fun, but I'd get more life and that's what's important.
The last picture taken of the author with her father before his death, in 2015.
Secondly, I would also have time to create an end-of-life plan the way my father did not. He told me repeatedly early on in his diagnosis that he did not want to live when he no longer knew me, when he became a burden, when he couldn't feed or bathe himself. I did my best in his final years to help him die quicker: I know that was what he wanted. But, given U.S. laws, all that meant was taking him off his heart and stroke medications and letting him eat anything he wanted, no matter how unhealthy. Knowing what's to come, having seen him go through it, I might consider moving to Belgium, which has begun to allow assisted suicide of those living with Alzheimer's and dementia if they can clearly state their intentions early on in the disease when they still have clarity of mind.
Next, I could help. Right now, there are dozens of Alzheimer's and dementia studies in the works. They are short thousands of willing test subjects. One of the top barriers to learning what's triggering the disease, and finding a cure, is populating these studies. So, knowing would make me a stronger candidate and would potentially help others down the road.
Finally, it would change my priorities. My father died the longest death possible: he succumbed last year more than 15 years after his diagnosis. My mother died the quickest possible way: she had a stress-related brain aneurysm 10 years after my father's diagnosis. Caring for him was too much for her and aneurysms ran in her family; her mother died of one as well. I already get a scan once every five years to see if I'm developing a brain aneurysm. If I am, odds are only 66% that they can operate on it—some aneurysms develop much too deep in the brain to operate, like my mother's.
Would she have wanted to know? Even though the aneurysm in her case was inoperable? I'm not sure. But I imagine if she had known, she would've lived her final years differently. She might have taken that trip to Alaska that she debated but thought was too expensive. She might have gotten organized earlier to make out a will so I wasn't left with chaos in the wake of her death; we'd planned for my father's death, knowing he was ill, but not my mother's. And she might have finally gotten around to dictating her story to me, as she'd always promised me she would when she found the time.
Telling my father's story at the end of his life helped his care.
With my startup MemoryWell, I spend my life now collecting senior stories before they are lost, in part because telling my father's story at the end of his life helped his care. But it's also in part for the story I lost with my mother.
If I knew that my time was limited, I'd not worry so much about saving for retirement. I'd make progress on my bucket list: hike Machu Picchu, scuba dive the Maldives, or raft the Grand Canyon. I'd tell my loved ones as much as I can in my time remaining how much they mean to me. And I would spend more time writing my own story to pass it down—finally finishing the book I've been working on. Maybe it's the writer in me, or maybe it's that I don't have kids of my own yet to carry on a legacy, but I'd want my story to be known, to have others learn from my experiences. And that's the biggest gift knowing would give me.
Editor's Note: Consider the other side of the argument here.
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.