Early Detection Opportunities Resulting from Low-Dose CT
Thursday, September 19, 2024 | New York Academy of Medicine (NYAM)
1216 5th Ave, New York, NY 10029
During the third panel discussion on the first day of the conference, experts highlighted the role of advanced imaging and AI in early disease detection, particularly for metabolic and immunometabolic disorders. They discussed the significance of incidental findings from routine scans and the need for standardized reporting. They also addressed the socioeconomic barriers to implementing these preventive measures and the importance of insurance coverage for such interventions.
The panel discussion was moderated by Dr. Jim Mulshine, MD, and Dr. Morteza Naghavi, MD, and featured the following panelists: Dr. Andrea D. Branch, PhD, Dr. Mingqian Huang, MD, Dr. Jeffrey Mechanick, MD, and Dr. Susan K. Fried, PhD.
Watch The Panel Discussion Below:
See Slides and Images from "Session 3: Early Detection Opportunities Resulting from Low-Dose CT" Panel Discussions Below:
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[Jim Mulshine] [0.56s] So I wanna thank all the presenters for some very important and, complex and new and emerging information.
[Jim Mulshine] [9.68s] And, you know, and as much as this is within the context of screening, it would be important to kind of tailor the conversation in that we seem to have a lot more emerging information to some of the other presentations we've had.
[Jim Mulshine] [32.41s] Could you help us in understanding what's the biggest opportunity for integration of analysis of these types of dynamics in prospective screening activities?
[Jim Mulshine] [45.86s] Does anybody wanna take that on?
[Jim Mulshine] [47.14s] Is there some particular
[Morteza Naghavi] [48.41s] the timing for it.
[Jim Mulshine] [49.77s] Yeah.
[Andrea Branch] [55.05s] The mark of metabolic dysfunction that can be treated now.
[Andrea Branch] [58.98s] So, like, go for it.
[Andrea Branch] [61.15s] And as I mentioned, AGA already has an algorithm for working of steatosis as an incidental finding.
[Andrea Branch] [68.59s] And basically, working through the algorithm, what the first step is trying to evaluate for liver fibrosis, because it's really liver fibrosis that's going to indicate a person is on the path toward progressive liver disease.
[Andrea Branch] [83.97s] So I I I think in that case, it's really just it's just really right there.
[Andrea Branch] [91.24s] I mean, there are algorithms to detect it that work effectively, and it's very easy to link your radiology report to lead hepatologists.
[Andrea Branch] [102.22s] Like, we you know?
[Andrea Branch] [104.38s] So so that's kind of, I would say, the lowest hanging.
[Andrea Branch] [108.61s] The a question I have is where are we in terms of image analysis to get information about these various fat depot sizes and and how to do that because I would love to have information about subcutaneous fat and visceral fat and liver fat and pancreas fat and kidney fat, but I don't know enough to know what are we there?
[Andrea Branch] [135.46s] Do we have the software to do that, or does that require more development?
[Jim Mulshine] [140.42s] So so one thing that that I might suggest is that as opposed to calling it incidental findings, I think this is some kind of immunometabolic consequence.
[Andrea Branch] [151.99s] Yes.
[Andrea Branch] [152.95s] That's what I'm trying to convey.
[Jim Mulshine] [155.11s] Okay.
[Jim Mulshine] [155.43s] So if you if it's tobacco related immunomodulation, whatever whatever, metabolic modulation, it would appear that studying these diseases within the context of what we've heard where there's augmentative impact of the fat dynamics on top of the progression of of some of the other more established diseases.
[Jim Mulshine] [181.10s] And and we've heard about how interconnected all these things are.
[Jim Mulshine] [185.50s] If we stop kind of pulling these things out into different, polarized bodies of science and try to study the integration and how they kinda come together So bad.
[Jim Mulshine] [198.86s] Relative to improving and
[Andrea Branch] [201.48s] No.
[Andrea Branch] [201.76s] I was talking to to Jeff before.
[Andrea Branch] [204.80s] And let's see.
[Andrea Branch] [205.52s] I he I can't remember what term he used.
[Andrea Branch] [207.84s] Back engineering, I think.
[Andrea Branch] [209.28s] Reverse engineering.
[Andrea Branch] [210.48s] I suggested that what we do is we find the diseases that improve when you treat with GLP 1 receptor agonist, and then you use that as a way to figure out what metabolic syndrome really is because we don't really know.
[Morteza Naghavi] [227.04s] I think your the answer to your question is absolutely yes, doctor Branch.
[Morteza Naghavi] [231.08s] There are so many AI tools available that can measure quantitatively report, fat, fat distribution, the abnormal adiposity, sarcopenia combined sarcopenia and fat.
[Morteza Naghavi] [247.66s] So the the technology is there.
[Morteza Naghavi] [249.81s] It's this kind of meeting, the awareness, the guideline, and bring it to patient care with FDA approval.
[Morteza Naghavi] [257.28s] I don't think there are FDA approved products to my knowledge in this.
[Morteza Naghavi] [261.20s] And I I I'm I'm just gonna bet, once we get this out, people may you know, the general public may love that part a lot more than coronary calcium and long nodule because they're looking at you know, most people like to see their fat go down.
[Morteza Naghavi] [277.71s] If you tell them that you have this much of visceral fat or fat around your heart, it gets their attention.
[Morteza Naghavi] [284.81s] So that's the kind of discussions that we needed to have for this meeting.
[Andrea Branch] [288.57s] Some of these drugs, they just drive the fat out of the liver.
[Andrea Branch] [292.17s] Like, if you see serial MRIs, I mean, it it's shocking to see the decrease in steatosis on these drugs.
[Jim Mulshine] [300.06s] Well, well, developmentally, much of the field of immunology, which was very confusing even more confusing 10, 20 years ago, was kinda directed towards things like c reactive protein.
[Andrea Branch] [314.14s] Yes.
[Jim Mulshine] [314.90s] What is c reactive protein?
[Andrea Branch] [316.90s] It is c reactive protein.
[Jim Mulshine] [318.02s] So that really you know, the short answer, I think, is that it's a surrogate of inflammation activity.
[Jim Mulshine] [325.14s] Instead of calling stuff fat, your fat really equals some kind of metabolic immunometabolic perturbation.
[Andrea Branch] [334.10s] I see.
[Andrea Branch] [334.50s] It's some kind of disorder.
[Andrea Branch] [336.10s] So can identify it with these drugs.
[Andrea Branch] [339.06s] As I say, I think Jeff's idea of reverse engineering, the definition is quite a clever one.
[Jim Mulshine] [344.51s] Well, if you can map it back to specific, you know, metabolic pathways and stuff like that, it might allow us to move it forward more rationally and and with less objection because people are just confused by this fat, that fat, you know, leave with other fat.
[Jim Mulshine] [364.32s] If it if it could be you know, I think with a lot of things, we're getting back to fundamental biology.
[Jim Mulshine] [371.46s] And if we and it clearly is driven by fundamental biology.
[Jim Mulshine] [374.90s] And if we could relate it to that, it could cross over between cardiovascular disease, pulmonary disease, cancer in a much more, I think, adaptive way.
[Andrea Branch] [384.36s] Yeah.
[Andrea Branch] [384.80s] I think these drugs are going to be very good anti inflammatory drugs.
[Andrea Branch] [389.63s] I think that's really what's
[Morteza Naghavi] [391.00s] Yeah.
[Morteza Naghavi] [391.24s] GLP one, definitely.
[Morteza Naghavi] [392.60s] I I was telling folks that to to cardiology, it's the best next, drug after statin, and it's proving even more than that.
[Morteza Naghavi] [403.42s] Susan, you go ahead.
[Susan Fried] [408.30s] So everything that you discussed is ongoing.
[Susan Fried] [411.98s] There are molecules.
[Susan Fried] [415.31s] Adipose tissue is the largest endocrine organ in the body.
[Susan Fried] [419.00s] It secretes more than a 100, factors, some protein, some transport protein, some endocrine factors, including diponectin, which has been put, you know, is probably our best candidate for a marker, but it's complicated because of its multiple molecular forms.
[Susan Fried] [439.05s] So it's not easy to measure, but it can be done in it, and and that can be done as well.
[Susan Fried] [445.98s] In terms of, prediction and finding not just there's good fat and bad fat.
[Susan Fried] [453.01s] We cannot tell from the mess.
[Susan Fried] [454.94s] We have to look at it more carefully.
[Susan Fried] [456.94s] When I get fat samples in my study and we look at them and the whole world looks at them, Everybody gets this finding that dysfunctional fat from people with the worst metabolic syndrome is, fibrotic.
[Susan Fried] [470.78s] It's filled with, more and more macrophages.
[Susan Fried] [473.50s] Those macrophages are more toxic and that they are secreting inflammatory cytokines.
[Susan Fried] [480.37s] This instigates the fat to release, very high concentrations of fatty acids and the way that can be toxic to the other tissues and are deposited there.
[Susan Fried] [492.28s] There are clear mechanisms, but at the physiological and at the molecular level, which controls the its adipose cell is only 50% of the cells.
[Susan Fried] [501.32s] And the fact there are multiple mechanisms like any other endocrine cell to control how much is made, how much is degraded, and how much is released.
[Jim Mulshine] [510.25s] So from a functional perspective, could you and your colleagues kinda come together and create an a, logic tree about in routine lung cancer screening, what would you want a radiologist to characterize for you in in probably a research directed report at this point in time?
[Jim Mulshine] [532.55s] Is that something, Dechomechanic, is that something that would be useful, or is there something else that could be done?
[Jim Mulshine] [537.43s] That's what we're doing.
[Jeffrey Mechanick] [539.36s] Right.
[Jeffrey Mechanick] [539.75s] So let me just repackage this question a little bit.
[Jeffrey Mechanick] [547.97s] It seems to me that the real question is about early detection.
[Jeffrey Mechanick] [552.77s] And the reason I'm focusing on that is what's actually the problem in health care now?
[Jeffrey Mechanick] [559.68s] And the problem in health care is that we have so many chronic diseases.
[Jeffrey Mechanick] [566.16s] We have a multi morbidity model.
[Jeffrey Mechanick] [568.64s] And despite all of the information that we have in the growing and emerging technology, if you look at the prevalence rate rates, they're they're getting worse.
[Jeffrey Mechanick] [579.01s] Now you can you can parse them out into different subpopulations, but we're actually not doing a good job.
[Jeffrey Mechanick] [586.21s] And we need to be able to leverage primordial and primary prevention better.
[Jeffrey Mechanick] [593.40s] Doctor Fuster will be speaking on primordial prevention, in 2 in 2 days, I I guess.
[Jeffrey Mechanick] [601.16s] But is this actionable?
[Jeffrey Mechanick] [604.10s] So what so what if we detect these things earlier?
[Jeffrey Mechanick] [609.46s] You gotta have an action.
[Jeffrey Mechanick] [611.22s] And in order to have an action, you need a model that can direct it.
[Jeffrey Mechanick] [615.06s] Right now, our models are that there are 3 primary drivers for these chronic diseases, genetics or molecular, environment, and behavior.
[Jeffrey Mechanick] [626.00s] So we have tons of data where people the CARA, paper, New England Journal, December 2016, where patients were at high genetic risk for cardiovascular disease.
[Jeffrey Mechanick] [638.32s] But when they adopt a healthy lifestyle, and this is information from the electronic health records, they had a risk reduction of about 48%, which is huge.
[Jeffrey Mechanick] [648.62s] And that's the environment and the behavior.
[Jeffrey Mechanick] [651.82s] We need to have structured lifestyle.
[Jeffrey Mechanick] [653.98s] But in order for that to happen, and again, you reverse engineer it back, what would make this system work?
[Jeffrey Mechanick] [660.70s] It would be early detection.
[Jeffrey Mechanick] [662.53s] That's the problem.
[Jeffrey Mechanick] [664.25s] Now we get to your point.
[Jeffrey Mechanick] [666.81s] There are so many images that are done that there's a waste of information.
[Jeffrey Mechanick] [673.13s] And now embarking on an age of, Internet of things and artificial intelligence.
[Jeffrey Mechanick] [679.80s] We just published a couple papers on digital twin technology with complete remissions of diabetes in a multi center study in India.
[Jeffrey Mechanick] [688.68s] When you have all of this information at hand, particularly with AI enabled technology, now you get this information.
[Jeffrey Mechanick] [697.61s] And you don't have to have the the humans ask those individual questions.
[Jeffrey Mechanick] [703.53s] The information's there.
[Jeffrey Mechanick] [704.65s] It's curated, and and you have actionable, directives, basically.
[Jeffrey Mechanick] [709.86s] I think that's where we're heading.
[Jeffrey Mechanick] [712.10s] I think that's the future.
[Jeffrey Mechanick] [713.38s] It's a future that we're not gonna be able to avoid.
[Jeffrey Mechanick] [716.34s] And I think that conferences like this, which position the technology for early detection are gonna be valuable.
[Jeffrey Mechanick] [725.45s] So Can you elaborate
[Morteza Naghavi] [727.37s] in digital twin?
[Jeffrey Mechanick] [729.05s] Sure.
[Jeffrey Mechanick] [730.25s] Sure.
[Jeffrey Mechanick] [730.57s] So the we we have two papers out.
[Jeffrey Mechanick] [732.73s] The first paper is in endocrine practice actually looking at, NAFLD, but MASL.
[Jeffrey Mechanick] [739.25s] And, the second paper was in Jack Advances on hypertension.
[Jeffrey Mechanick] [742.68s] Digital twin technology did not originate with health care.
[Jeffrey Mechanick] [746.52s] It originated with aerospace science and NASA.
[Jeffrey Mechanick] [750.22s] It's basically a way to virtually represent something in the natural world.
[Jeffrey Mechanick] [755.02s] But for humans in health care, what we did in this particular study is patients, and and full disclosure because I consult for Twin Health, but it was on my slide.
[Jeffrey Mechanick] [767.05s] But humans wear a continuous glucose monitor.
[Jeffrey Mechanick] [770.74s] They wear an accelerometer.
[Jeffrey Mechanick] [772.65s] They have an electronic scale, and they have electronic chemodynamic monitoring devices.
[Jeffrey Mechanick] [778.40s] The information goes into an Internet of things construct to proprietary artificial intelligence.
[Jeffrey Mechanick] [786.00s] And then with 247 bot coaching, patients are now able to change their behaviors in what they eat.
[Jeffrey Mechanick] [797.79s] And they change their foods based on postprandial glucose levels.
[Jeffrey Mechanick] [803.95s] Their weight comes down.
[Jeffrey Mechanick] [805.79s] We had a 78.7% complete remission in diabetes defined as 3 months off all medicine, normal numbers in a multicenter trial in India, and the Cleveland Clinic paper is just ready to be submitted now.
[Morteza Naghavi] [823.88s] 3 months?
[Jeffrey Mechanick] [824.87s] 3 months?
[Jeffrey Mechanick] [826.19s] 3 months.
[Jeffrey Mechanick] [827.07s] And so that's the current definition of a complete remission.
[Jeffrey Mechanick] [831.49s] So at some point during 1 year, 78.7% of patients enjoyed a 3 month period where they got off all their diabetes medicines and had normal a one c's, continuous glucose monitoring, fasting blood sugars, etcetera based on digital twin.
[Jeffrey Mechanick] [848.35s] That's off all medicines, and they were on a lot of medicines, including, including insulin.
[Jeffrey Mechanick] [854.82s] And bearing in mind that the, Asian Indian population, the diabetes phenotype described by Vimalahan and Chennai is very different than in Caucasians.
[Jeffrey Mechanick] [865.38s] Right?
[Jeffrey Mechanick] [865.70s] You have a beta cell hit.
[Jeffrey Mechanick] [867.80s] You have diabetes at lower BMIs.
[Jeffrey Mechanick] [870.12s] Even though there's insulin resistance, you can get get fibrocalcinosis of the pancreas.
[Jeffrey Mechanick] [875.48s] You can have decreased beta cell reserve.
[Jeffrey Mechanick] [877.96s] So you there's more of a postprandial hyperglycemia hit than there is an insulin resistant hit.
[Jeffrey Mechanick] [884.86s] So everything I just said, if you're thinking, you can you can realize you can detect this with imaging.
[Jeffrey Mechanick] [891.58s] And what you're gonna hear when doctor Fuster speaks is he's gonna be a proponent.
[Jeffrey Mechanick] [896.44s] He's gonna talk about his PASA stuff, and I wanna steal his thunder.
[Jeffrey Mechanick] [900.60s] But he's gonna talk about how imaging is gonna facilitate a lot of this.
[Jeffrey Mechanick] [906.20s] Imagine if you had a patient with completely normal numbers and completely normal anthropometrics, and you had imaging, information that already showed pathologic, however you define it as a statistical based classifier, pathologic ectopic fat, pericardial, whether it's mastoid, whether it's in the pancreas, you're now going to initialize some action.
[Jeffrey Mechanick] [934.05s] The action doesn't have to be pharmaceutical.
[Andrea Branch] [937.41s] I agree.
[Jeffrey Mechanick] [937.97s] It doesn't have to be pharmaceutical.
[Jeffrey Mechanick] [940.10s] So it's gonna be cost effective.
[Jeffrey Mechanick] [942.17s] So we need our infrastructure socioeconomics improved so that we can get people into a medical gym, have them see a sleep hygiene person, see a dietitian, get them to the right consultants.
[Jeffrey Mechanick] [956.47s] And in fact, if you think about the socioeconomic piece, by bundling all the economics here, you're using and I hate to say the word incidentally, but incidentally, you're using that information which would have been thrown in the garbage, all that extra information about bones and about sarcopenia that you would have had on those images.
[Jeffrey Mechanick] [976.48s] Now you can use it and you can profile a patient and restratify them at an early age.
[Jeffrey Mechanick] [982.68s] And when I say early, I mean, you're talking about teenagers, twenties, maybe even school children.
[Jeffrey Mechanick] [989.08s] And in fact, to I don't know if you saw my my last slide.
[Jeffrey Mechanick] [993.16s] Sci the problem with science fiction is it underestimates the future.
[Jeffrey Mechanick] [997.70s] Then that really what's gonna happen is this is gonna be maternal health and transgenerational medicine.
[Jeffrey Mechanick] [1004.89s] Okay.
[Jeffrey Mechanick] [1005.38s] Those are even starting
[Jim Mulshine] [1007.05s] So I think this is phenomenal, but we gotta get there.
[Jim Mulshine] [1010.10s] And right now, this year, there's gonna be a few 1,000,000 thoracic CTs done.
[Jim Mulshine] [1015.53s] And the only thing I know about this is that there is no standard reporting of fat in a CT study.
[Jim Mulshine] [1022.57s] And my question as a simple type of person when we hear about all the primary care and all these other challenges is, how do we get experts to help us say, here's what would be the snapshot because this is all gonna be longitudinal screening over year over year after year.
[Jim Mulshine] [1039.38s] How do we get something done now that will potentially help us deconstruct all these dynamics to allow what you just outlined to happen?
[Morteza Naghavi] [1049.58s] David, Jim, I'm gonna weigh in here.
[Morteza Naghavi] [1053.58s] We take actions.
[Morteza Naghavi] [1054.62s] As you know, 3 years ago, I started Claudia and David.
[Morteza Naghavi] [1057.93s] Now we have an FDA cleared auto bone density AI that's applicable and it's being installed in Mount Sinai, and we'll give a report without you doing anything.
[Morteza Naghavi] [1069.86s] It's just Yeah.
[Mingqian Huang] [1073.98s] Some other house information.
[Mingqian Huang] [1075.74s] We don't report, and we have a tremendous clinical burdens.
[Mingqian Huang] [1080.70s] Literally, we are only afford a couple minutes on each study.
[Morteza Naghavi] [1084.56s] Yep.
[Mingqian Huang] [1084.80s] So this kind of help is what we needed.
[Mingqian Huang] [1087.91s] And we are very aware of of all these problems.
[Mingqian Huang] [1091.12s] If you I would just come back from our International Scalital Society meeting, and there are so many talks, visceral fats and, muscle fat.
[Mingqian Huang] [1100.26s] And, also, there was a study proposed.
[Mingqian Huang] [1102.50s] It was interesting.
[Mingqian Huang] [1103.30s] I didn't know.
[Mingqian Huang] [1104.02s] They were looking at all these, AC joint or near the heart soft tissue calcifications that were wrongfully, attributed to hard calculations and how to use AI to increase the sensitivity of that.
[Mingqian Huang] [1119.48s] So we are all very well aware of that.
[Mingqian Huang] [1121.96s] But all this work are done in the research arena.
[Mingqian Huang] [1125.04s] Yeah.
[Mingqian Huang] [1125.28s] There was study that done with AI.
[Mingqian Huang] [1128.00s] They can adequately diagnose or pick out patient who are risk developing, metabolic syndrome very accurately from that group from University of Wisconsin.
[Mingqian Huang] [1138.52s] It's all there, but we need a tool that'd be fast and practice.
[Mingqian Huang] [1143.88s] Exact So,
[Jim Mulshine] [1145.56s] what I just heard you say is you guys are volunteering to be in a subcommittee to urgently map Yes.
[Jim Mulshine] [1153.13s] A profile of of immuno, metabolic factors that should be routinely recorded on a thoracic CT.
[Morteza Naghavi] [1162.33s] We will be actually circulating after this this was, as I said, draft that we would need your help in in weighing on and forming it and shaping it to a, a writing group white paper of some sort that would actually put in, you know, in front of policymaker.
[Jim Mulshine] [1181.42s] Would that be worthwhile?
[Jim Mulshine] [1182.94s] You're you're the experts.
[Mingqian Huang] [1184.30s] Our radiology report is going is our standardized reporting, and you can just add a category with all the numbers and stuff there.
[Mingqian Huang] [1192.14s] That's where the direction going.
[Andrea Branch] [1194.13s] Also, I don't know if it would fit in this white paper, but it kinda picks up on something that doctor Mckinic was talking about.
[Andrea Branch] [1200.68s] Certainly, there are alternatives to pharmacology, but I've gotta say, as far as our patient population of liver has been concerned, like, we've been advocating for weight loss and more exercise for decades, and the impact on disease has been not what we would hope for.
[Andrea Branch] [1216.81s] So I think one thing that would be really helpful is if people thought about how things are paid for other than pharmaceuticals.
[Andrea Branch] [1224.07s] And I don't know if you could work this into the white paper, but I think a huge hurdle is that you we need physicians to be able to write prescriptions for gym memberships and for interventions with personal trainers.
[Andrea Branch] [1239.52s] And I think that if we got that kind of cost flow going to support non pharmaceutical interventions, we find that they were a lot more effective.
[Andrea Branch] [1250.48s] Whereas we're stuck currently with this situation in medicine where you can write a prescription for a drug and it's gonna get insurance coverage.
[Andrea Branch] [1258.38s] You wanna write a prescription for somebody to go to a personal trainer.
[Andrea Branch] [1262.21s] That's a hurdle that we we really haven't addressed.
[Andrea Branch] [1264.86s] So how we can get that insurance piece to cover the kinds of interventions, I you know, I think that is really a critical part of solving this problem.
[Jim Mulshine] [1274.42s] So I I that's a very important point.
[Jim Mulshine] [1276.58s] And what I would point out is in the in the commentary that was published with the revision of the US Preventive Services Task Force Assessment of COPD as a screening tool, the the the the editorialist basically said that exercise and these other interventions in COPD is very important, but there's not a single trial of quality in the literature that gives us an inkling of whether it's works or not.
[Jim Mulshine] [1309.20s] So I think the the the impetus to take these ongoing cohorts and to start to pilot some of these things to get support for what you just said, it serves seems like an urgent first step.
[Jim Mulshine] [1320.01s] Yeah.
[Andrea Branch] [1320.16s] I really think it is.
[Andrea Branch] [1321.82s] We're working out a pay line for these lifestyle interventions, especially as they relate to physical activity, I think, is really critical.
[Morteza Naghavi] [1333.58s] One last question.
[Speaker 7] [1335.98s] It's it's very nice if we can quantify, for example, body composition, but that's only one step.
[Speaker 7] [1342.30s] For example, body composition, you have, for example, total segmentator and all those.
[Speaker 7] [1346.30s] You got many, many measurements, but we don't have standardization of what measurement we should be using.
[Speaker 7] [1352.21s] Because before, for example, we had T4 levels where we had just an area of muscles and stuff like that.
[Speaker 7] [1358.77s] So we can do a lot more, but we need to know what should we measure?
[Speaker 7] [1362.05s] What are the reference values, what is abnormal, and what should be then the management recommendations.
[Speaker 7] [1368.38s] And as for example, we have that l one level versus l three.
[Speaker 7] [1372.71s] It might, I we check that in our, screening population and 30% doesn't add L1, because we are pretty, pretty good with our dose, yeah, limits.
[Speaker 7] [1385.81s] So we really try to just stick to the entire lung only.
[Speaker 7] [1389.65s] So I think we need to work together to work, to get reference values and and, standardization of levels where we should be measuring on a thoracic level.
[Morteza Naghavi] [1398.18s] Excellent point.
[Morteza Naghavi] [1398.90s] I think we are working on that at thoracic level.
[Morteza Naghavi] [1402.03s] Hopefully, next year, we'll have solid, information to share.
[Morteza Naghavi] [1406.43s] But what you just said is applicable to everything else, to bone density reporting, to muscle reporting, body fat, liver fat.
[Morteza Naghavi] [1414.19s] You know, one of the question I wanted to ask you, Andrea, is if somebody goes on a fasting, like, 3 day fasting, what would happen to their body liver picture?
[Morteza Naghavi] [1424.52s] Would that go down?
[Morteza Naghavi] [1425.57s] Oh, it absolutely Yes.
[Morteza Naghavi] [1426.85s] So that's steed.
[Andrea Branch] [1428.37s] But it's really interesting that in studies that have been done where people are not told to fast, where people are just coming in for scans, when patients are followed longitudinally, it's a remarkable stability in in the value.
[Andrea Branch] [1444.75s] So in theory, yes, it could fly all over the place.
[Andrea Branch] [1447.87s] It could make a difference if you had a burger or shake that moment.
[Andrea Branch] [1450.92s] Yes.
[Andrea Branch] [1451.48s] Morning.
[Andrea Branch] [1452.13s] But in practicality, when I've seen the CT data over a longitudinal measurement, it's been remarkably stable.
[Andrea Branch] [1464.13s] But that's really something that I want to look into because one of the secrets about liver fat is there's a theory that when liver disease progresses, the liver loses its ability to store fat.
[Andrea Branch] [1477.25s] And whether that you could actually document longitudinally and what happens to cardiovascular risk and what happens to markers of cardiovascular risk, I've never been able to find information about it.
[Andrea Branch] [1493.93s] And it would be a great
[Morteza Naghavi] [1495.29s] Yeah.
[Morteza Naghavi] [1495.53s] That's that that a hot topic.
[Morteza Naghavi] [1497.53s] The same thing for osteoporosis.
[Morteza Naghavi] [1499.93s] We found those people who have higher osteoporosis, lower bone mass, have higher coronary calcium independent of the traditional risk factor.
[Morteza Naghavi] [1510.31s] An interplay between bone metabolism, calcium metabolism, phosphates, and what happens in coronaries.
[Jim Mulshine] [1516.88s] Yeah.
[Jim Mulshine] [1517.12s] But I'd like to come back to that because Rosemary suggested we need to have some, you know, reference for various things in various populations.
[Jim Mulshine] [1528.80s] Doctor, Yankiewicz has brought this up a number of times, and it's an equity issue.
[Jim Mulshine] [1534.89s] Because when you say you wanna have reference information and it's gonna be on a population health, you know, for a tool to be disseminated, it it means that you have all the vulnerable populations, all the diversity of age and and gender and and and sex and, so that this is why we need to step back and start approaching population screening in a much more rigorous fashion so that we have a way to acquire that data.
[Andrea Branch] [1569.62s] Yeah.
[Andrea Branch] [1570.17s] Absolutely.
[Jim Mulshine] [1570.97s] Because the technology is gonna change.
[Jim Mulshine] [1572.89s] Absolutely.
[Jim Mulshine] [1573.29s] There and so this is a key factor that has been underappreciated.
[Jim Mulshine] [1578.57s] It's not it's not a one off thing, and it's not in a population cohort of 10,000.
[Jim Mulshine] [1583.45s] It's it's in the whole population.
[Jim Mulshine] [1585.55s] So how are we doing on time?
[Jim Mulshine] [1588.83s] I think we have 4 minutes.
[Jim Mulshine] [1590.18s] We will finish 4 minutes early or something like that.
[Speaker 8] [1593.55s] K.
[Morteza Naghavi] [1594.83s] Shall we?
[Jim Mulshine] [1595.55s] We'll keep it under 4 minutes.
[Speaker 8] [1597.47s] Yeah.
[Speaker 8] [1598.33s] I just I just you know, when you are going to put it in the report, all these wonderful findings of a new chronic disease that you see, and I'm as the treating physician asking the question, what do you want me to do with this?
[Speaker 8] [1614.62s] So this is very important because now we are in the first stage of of of detecting the disease.
[Speaker 8] [1624.54s] And then we'll have to learn the natural history of the disease and how we can change it.
[Speaker 8] [1632.37s] It mean to say the treatment.
[Speaker 8] [1634.45s] I think that the coronary calcium is the model, and it took 30 years to to answer all these question and to give the the the the physician that get the answer, and he knows what to do with it.
[Speaker 8] [1651.52s] So, it's it's it's really wonderful.
[Speaker 8] [1655.20s] Things are you see that these things, but how how do you think about specific treatment?
[Morteza Naghavi] [1662.19s] All of
[Speaker 8] [1662.51s] them are sure a healthy lifestyle and changing the the diet.
[Speaker 8] [1667.55s] It's it's things that are normally and act.
[Speaker 8] [1670.73s] But when you are going to report on, on on some kind of what kind of obesity I have, what to do with this?
[Speaker 8] [1679.85s] What's the differences?
[Speaker 8] [1681.13s] How to treat the patient?
[Speaker 8] [1682.89s] I think we're it should be very, very careful when you are going to to send the the physician all these findings in the moment that he doesn't know what to do with it.
[Jim Mulshine] [1694.01s] Your point's very well taken, and I think we have to conclude here.
[Jim Mulshine] [1697.29s] But that's exactly the the task in front of us.
[Jim Mulshine] [1700.41s] And I think there's
[Morteza Naghavi] [1701.86s] And we will be working on that.
[Morteza Naghavi] [1703.62s] And I think, hopefully, role calcium will not be calcium score will not be the role model.
[Morteza Naghavi] [1709.38s] It took 30 years.
[Morteza Naghavi] [1711.05s] We have more evidence.
[Morteza Naghavi] [1712.81s] These guys' endocrinologists and, you know, GLP GLP one, you know, saga has created a lot of positive signs, but you're absolutely right.
[Morteza Naghavi] [1725.02s] No diagnostics tests or, examination saves lives.
[Morteza Naghavi] [1729.73s] It's the intervention after that.
[Morteza Naghavi] [1731.65s] What to do with it in care pathway will be part of the working group that will need your help and everybody else.
[Morteza Naghavi] [1738.15s] Thank you so much.
[Jim Mulshine] [1739.59s] Thank you for the panelists, and thank you for the participation.
The presentations were hosted by I-ELCAP – The International Early Lung Cancer Action Program.
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