\n| Stenosis \u226550%<\/td>\n | 1.22<\/td>\n | 0.89\u20131.69<\/td>\n | Fully adjusted<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Table 1.<\/strong> Association of CCTA findings with first coronary events in SCAPIS.\u00b9 All values are from the fully adjusted model. Note that once plaque extent is accounted for, obstructive stenosis (\u226550%) is not<\/strong> independently associated with first events in this primary-prevention cohort \u2014 the confidence interval crosses 1.0. Unadjusted and partially adjusted models give larger stenosis estimates and should not be quoted as if they were adjusted results.<\/p>\nAdding the CCTA variables to a model containing PCE and CACS improved discrimination modestly: the C-statistic rose from 0.764 to 0.779<\/strong> (P<\/em> = .004).\u00b9 Reclassification improved as well, with a net reclassification improvement of 0.133<\/strong> (95% CI, 0.031\u20130.165). Among participants who went on to have an event, 14.2%<\/strong> were correctly moved into a higher risk category; among those who did not have an event, 1.6%<\/strong> were incorrectly moved upward.\u00b9 Because the overall event rate was low, most of this reclassification occurred among people the PCE had labeled low risk (<5%) \u2014 which is precisely the group in which a missed diagnosis is most consequential, and also the group in which unnecessary treatment is hardest to justify.<\/p>\nThe investigators themselves characterize the gain as modest<\/em>.\u00b9 That word is worth keeping. SCAPIS shows that direct imaging of plaque adds real, statistically robust information beyond risk factors and calcium scoring in a middle-aged primary-prevention population. It does not show that imaging transforms individual risk prediction, and it was not designed to show that acting on the imaging improves outcomes.<\/p>\nTwo Different Questions: Detecting Stenosis vs Predicting Events<\/h3>\nMuch of the confusion in the popular coverage of AI-assisted CCTA comes from treating two very different performance metrics as interchangeable. They are not, and conflating them inflates the apparent capability of the technology.<\/p>\n \n- Diagnostic accuracy<\/strong> asks: how well does the test agree with a reference standard \u2014 typically invasive quantitative coronary angiography (QCA) \u2014 about whether a stenosis is present right now<\/em>?<\/li>\n
- Prognostic discrimination<\/strong> asks: how well does the test rank people by their likelihood of having a cardiovascular event in the future<\/em>?<\/li>\n<\/ul>\n
An area under the curve (AUC) of 0.91 for the first question is not evidence of an AUC of 0.91 for the second. Diagnostic AUCs against an anatomic reference standard are systematically higher than event-prediction AUCs, because future events depend on plaque biology, hemodynamics, thrombotic propensity, treatment, and chance \u2014 not only on anatomy. The two tables below are therefore presented separately and should not be merged into a single ranking.<\/p>\n Diagnostic accuracy: agreement with invasive angiography<\/h4>\nIn a post hoc analysis of the PACIFIC-1 cohort (208 patients with new-onset stable chest pain, all of whom underwent both CCTA and invasive QCA), AI-guided quantitative CT (AI-QCT) was compared directly with human readers of differing experience for the detection of \u226550% stenosis on a per-patient basis.\u00b3<\/p>\n \n\n\nReader<\/strong><\/td>\nAUC (95% CI)<\/strong><\/td>\nTask<\/strong><\/td>\n<\/tr>\n<\/thead>\n\n\n| AI-QCT<\/td>\n | 0.91 (0.87\u20130.95)<\/td>\n | \u226550% stenosis vs QCA<\/td>\n<\/tr>\n | \n| Level-3 expert reader<\/td>\n | 0.77 (0.70\u20130.83)<\/td>\n | \u226550% stenosis vs QCA<\/td>\n<\/tr>\n | \n| Level-2 reader A<\/td>\n | 0.79<\/td>\n | \u226550% stenosis vs QCA<\/td>\n<\/tr>\n | \n| Level-2 reader B<\/td>\n | 0.76<\/td>\n | \u226550% stenosis vs QCA<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Table 2.<\/strong> Per-patient diagnostic accuracy for obstructive stenosis, PACIFIC-1 post hoc analysis, invasive QCA as reference standard.\u00b3 These are diagnostic<\/strong> AUCs. They describe agreement with invasive angiography about present anatomy. They do not describe prediction of myocardial infarction.<\/p>\nThe correct reading of this result is that automated quantitative analysis agreed with the invasive reference standard more closely than expert visual assessment did, and did so reproducibly. That is a meaningful finding about interpretive consistency \u2014 visual CCTA reading is known to be experience-dependent and to overestimate stenosis \u2014 but it is a statement about diagnosis, not about prognosis.<\/p>\n Prognostic discrimination: predicting future events<\/h4>\nIn the CONFIRM2 registry, AI-QCT was tested for incremental prognostic value over the qualitative and semiquantitative measures currently recommended in practice. Adding AI-QCT improved discrimination for major adverse cardiovascular events over CAD-RADS 2.0, CACS, and the modified Duke Index.\u2074<\/p>\n \n\n\nComparator (alone)<\/strong><\/td>\nAUC alone<\/strong><\/td>\nAUC + AI-QCT<\/strong><\/td>\n<\/tr>\n<\/thead>\n\n\n| CAD-RADS 2.0<\/td>\n | 0.79<\/td>\n | 0.81<\/td>\n<\/tr>\n | \n| Coronary artery calcium score<\/td>\n | 0.70<\/td>\n | 0.79<\/td>\n<\/tr>\n | \n| Modified Duke Index<\/td>\n | 0.76<\/td>\n | 0.81<\/td>\n<\/tr>\n | \n| PCE + CACS (SCAPIS, + CCTA)\u00b9<\/td>\n | 0.764<\/td>\n | 0.779<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Table 3.<\/strong> Prognostic discrimination for future events.\u00b9\u02d2\u2074 The CONFIRM2 rows describe specific models within one registry of symptomatic patients referred for CCTA; the SCAPIS row describes an asymptomatic general-population cohort and non-AI CCTA variables. These are not<\/strong> interchangeable, and none of them is a universal performance characteristic of AI-QCT.<\/p>\nTaken together, the honest summary is this: quantitative, AI-assisted CCTA measurements can provide incremental prognostic information beyond conventional clinical risk assessment, calcium scoring, and qualitative CCTA reads \u2014 but the magnitude of that improvement varies substantially with the population studied, the endpoint chosen, and the model specification. In the contemporary prognostic studies discussed here, reported event-prediction AUCs for AI-QCT are approximately 0.75 to 0.81 rather than 0.90.\u00b9\u02d2\u2074<\/p>\n What Quantitative Plaque Analysis Measures, and Why It Matters<\/h3>\nTraditional risk equations such as the Framingham Risk Score and the Pooled Cohort Equations infer vascular risk from surrogate variables \u2014 age, sex, blood pressure, lipids, smoking, diabetes \u2014 rather than from the artery itself.\u2079\u02d2\u00b9\u2070 They perform reasonably at the population level and imperfectly at the individual level, because the relationship between risk factors and plaque development is heterogeneous. Two people with identical risk-factor profiles can have very different coronary arteries.<\/p>\n Quantitative CCTA measures the disease directly. Rather than reporting only the tightest narrowing, it characterizes plaque throughout the coronary tree by volume, composition, and vessel remodeling. Several of these features carry prognostic information:<\/p>\n \n- Total plaque volume (TPV).<\/strong> Higher total atherosclerotic burden is independently associated with future events across multiple cohorts. Effect sizes are study-specific and depend on the population, the units in which volume is expressed, and the covariates adjusted for; a risk estimate from one cohort should not be quoted as a general property of plaque volume.\u2074\u02d2\u2075<\/li>\n
- Noncalcified plaque (NCP) volume.<\/strong> In CONFIRM2, each 50-mm\u00b3 increase in noncalcified plaque was associated with a 1%<\/strong> relative increase in MACE risk in women and 11.6%<\/strong> in men.\u2075<\/li>\n
- Low-attenuation plaque (\u226430 HU).<\/strong> A CT marker associated with lipid-rich, necrotic-core plaque characteristics \u2014 an imaging correlate rather than a direct measurement of necrotic core. In SCOT-HEART, low-attenuation plaque burden was the strongest predictor of fatal or nonfatal myocardial infarction (adjusted HR 60<\/strong> per doubling; 95% CI, 1.10\u20132.34), and a burden above 4% was associated with an HR of 4.65<\/strong> (95% CI, 2.06\u201310.5).\u00b2<\/li>\n
- Positive (outward) remodeling.<\/strong> Outward expansion of the vessel wall may allow substantial plaque to accumulate before marked luminal narrowing becomes apparent, which is one reason lumen-focused assessment can underestimate disease burden.<\/li>\n<\/ul>\n
The biology underlying these measurements is more nuanced than a simple “calcium is safe, soft plaque is dangerous” dichotomy. Dense calcification is generally associated with more stable lesion behavior, and calcification does often follow inflammatory injury as part of a healing response \u2014 but calcified plaque is not inert, and calcium burden remains a strong marker of overall atherosclerotic disease. Conversely, noncalcified plaque is not synonymous with vulnerable plaque; it is a heterogeneous category, only part of which has the lipid-rich, thin-capped phenotype associated with rupture. The useful statement is narrower and better supported: plaque composition adds prognostic information that calcium score alone does not capture.<\/p>\n A related point is frequently overstated in consumer coverage. It is well documented that many acute coronary events arise from lesions that were not severely obstructive on prior imaging, which is a central reason plaque burden and composition can carry information beyond stenosis severity. It does not follow that “most heart attacks are caused by non-obstructive soft plaque” \u2014 that phrasing compresses several distinct issues (pre-event stenosis severity, plaque phenotype, rupture versus erosion, and the limitations of retrospective angiographic comparison) into a single claim that the evidence does not cleanly support.<\/p>\n Scanner Technology: What Wide-Detector CT Actually Delivers<\/h3>\nContemporary wide-detector CT systems can acquire the entire heart within a single cardiac cycle in appropriately selected patients. This reduces misregistration (“stitching”) artifacts that arise when a volume is assembled from multiple heartbeats, and it permits high-quality coronary imaging at relatively low radiation doses when protocols are optimized.<\/p>\n Several caveats belong alongside that statement, because they are routinely omitted:<\/p>\n \n- Marketing terms such as “640-slice” describe a reconstruction characteristic of a wide-area detector system rather than an independent measure of image quality, and they do not by themselves establish superior outcome prediction. Detector coverage (for example, 16 cm) and acquisition architecture are the more meaningful descriptors.<\/li>\n
- Radiation dose cannot be stated as a single number. It varies with scanner generation, prospective versus retrospective gating, tube voltage and current, heart rate and rhythm, body habitus, scan length, and reconstruction algorithm.\u00b9\u00b9 Sub-millisievert coronary CTA is achievable in favorable patients with optimized protocols; it is not a general expectation.<\/li>\n
- Spatial resolution figures are scanner- and protocol-specific and should be verified against the manufacturer’s technical specification for the exact system and acquisition mode in question before being cited.<\/li>\n
- Single-beat acquisition reduces \u2014 but does not eliminate \u2014 the need for heart-rate control, and does not eliminate motion artifact.<\/li>\n<\/ul>\n
The practical significance of wide-detector systems for this discussion is that reproducible, lower-dose acquisition makes serial imaging more feasible, which in turn makes longitudinal plaque tracking a technically feasible clinical and research proposition. Routine serial CCTA performed specifically to monitor plaque remains an evolving strategy rather than established standard care for most patients.<\/p>\n Is Plaque Modifiable? EVAPORATE and the Limits of What It Shows<\/h3>\nEVAPORATE, a randomized, double-blind, placebo-controlled trial of 80 patients with elevated triglycerides on statin therapy, used serial CCTA to assess the effect of icosapent ethyl on plaque progression over 18 months. It found reduction in low-attenuation plaque volume in the treatment arm alongside progression in the placebo arm.\u2077<\/p>\n EVAPORATE is a mechanistic imaging trial. It was not an AI-QCT study and it was not powered for clinical events. It supports the proposition that plaque composition is modifiable and measurable over time; it does not validate the prognostic performance of any particular AI analysis platform, and it should not be cited as though it did.<\/p>\n TRANSFORM: A Trial Designed to Test the Outcome Question<\/h3>\nTRANSFORM (NCT06112418) is a prospective, randomized, open-label, blinded-endpoint trial enrolling patients at elevated cardiovascular risk without known symptomatic disease. Participants are randomized to guideline-directed risk-factor-based care or to a care strategy driven by an AI-based coronary plaque staging system, with repeat imaging at 24 months in the imaging arm.\u2078<\/p>\n TRANSFORM is ongoing<\/strong>. Its results are not yet available, and it therefore cannot be cited as evidence supporting any conclusion about the effectiveness of an imaging-guided prevention strategy. Its importance lies in what it is designed to establish: whether identifying and staging plaque earlier, and treating accordingly, actually reduces cardiovascular events compared with current practice. That is the question the existing observational and diagnostic literature cannot answer.<\/p>\nImpact on Clinical Decision-Making<\/h3>\nThere is reasonable evidence that quantitative plaque analysis changes what clinicians do. In the CERTAIN study, a multicenter crossover study of 750 consecutive patients referred for CCTA at five expert sites, physicians recorded their diagnosis and management plan based on conventional site interpretation and then repeated the assessment after AI-QCT analysis.\u2076<\/p>\n \n- Diagnosis or management changed in 1%<\/strong> of patients (P<\/em> < .001).\u2076<\/li>\n
- Statin initiation or intensification increased in an additional 1%<\/strong> of patients, and aspirin initiation in an additional 23.0%<\/strong> (P<\/em> < .001 for both).\u2076<\/li>\n
- The anticipated need for downstream noninvasive and invasive testing fell by 1%<\/strong> (P<\/em> < .001).\u2076<\/li>\n<\/ul>\n
These are changes in physician intent measured within a study design in which the same physicians assessed the same patients twice, in a fixed order, at high-volume expert centers. That design cannot exclude ordering effects, and intent to prescribe is not the same as improved outcomes. The finding is genuinely encouraging about clinical utility and genuinely insufficient as evidence of clinical benefit.<\/p>\n Coverage for AI-based coronary plaque analysis has expanded among United States payers since 2024, but policies remain plan-, indication-, and region-specific. Patients and clinicians should verify coverage directly with the payer rather than relying on general statements of availability.<\/p>\n Sex-Specific Implications<\/h3>\nOne of the most clinically relevant findings in this literature concerns sex differences in how plaque burden translates into risk. In the CONFIRM2 registry (3,551 symptomatic patients, 49.5% women, mean follow-up 4.8 \u00b1 2.2 years), women had roughly half the plaque burden of men and about half the MACE rate (3.2% vs 6.1%). But the relative risk conferred by each increment of plaque was consistently higher in women.\u2075<\/p>\n \n\n\nPlaque measure (per 50 mm\u00b3 increase)<\/strong><\/td>\nIncrease in MACE risk, women<\/strong><\/td>\nIncrease in MACE risk, men<\/strong><\/td>\n<\/tr>\n<\/thead>\n\n\n| Total plaque volume<\/td>\n | +17.7%<\/td>\n | +5.3%<\/td>\n<\/tr>\n | \n| Noncalcified plaque<\/td>\n | +27.1%<\/td>\n | +11.6%<\/td>\n<\/tr>\n | \n| Calcified plaque<\/td>\n | +22.9%<\/td>\n | +5.4%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Table 4.<\/strong> Sex-specific relative risk per 50-mm\u00b3 increment, CONFIRM2 registry (P<\/em> for interaction < .001).\u2075 Note that total plaque volume, noncalcified plaque, and calcified plaque have distinct values and must not be quoted interchangeably.<\/p>\nThe clinical implication is that a plaque volume that looks reassuringly “low” by absolute standards derived largely from men may carry meaningful prognostic weight in a woman. Quantitative measurement, which reports actual volumes rather than a qualitative impression, is well suited to detecting exactly this pattern \u2014 provided the interpretation is sex-aware.<\/p>\n Synthesis and Conclusion<\/h3>\nThe central argument holds. Coronary CT angiography identifies atherosclerotic disease that risk-factor equations and calcium scoring do not fully characterize, and quantitative, AI-assisted analysis of those images adds diagnostic reproducibility and incremental prognostic information. SCAPIS provides strong contemporary evidence that CCTA improves prediction of first coronary events beyond the PCE and CACS in a middle-aged general population, particularly among people those tools classify as low risk.\u00b9 CONFIRM2 shows that quantitative plaque measurement improves discrimination over the qualitative and semiquantitative measures used in practice today, and that plaque burden carries greater relative risk in women.\u2074\u02d2\u2075 CERTAIN shows that clinicians change their management when given this information.\u2076<\/p>\n What the evidence does not yet establish is equally important:<\/p>\n \n- It does not establish that AI-assisted CCTA predicts cardiovascular events with an AUC near 0.90. That figure comes from diagnostic accuracy against invasive angiography, not from event prediction.\u00b3\u02d2\u2074<\/li>\n
- It does not establish that imaging-guided prevention improves clinical outcomes. No completed randomized trial has demonstrated this. TRANSFORM is designed to test it and has not reported.\u2078<\/li>\n
- It does not establish that any single scanner configuration or analysis platform is superior in outcome terms.<\/li>\n<\/ul>\n
The reasonable conclusion is a strong one without being an overclaim: direct visualization and quantification of coronary plaque represents a substantive advance over inference from risk factors alone, and it identifies disease in people whom conventional tools reassure. Whether acting on that information reduces heart attacks is a question currently under randomized investigation, and the answer will come from TRANSFORM and trials like it rather than from registries, diagnostic accuracy studies, or extrapolation.<\/p>\n For an individual patient, the practical takeaway is unchanged by any of these caveats: finding plaque may identify an opportunity to intensify evidence-based preventive treatment, and serial CCTA studies demonstrate that plaque characteristics are measurably modifiable.\u2077 The appropriate posture toward the technology is confident engagement paired with accurate expectations about what the evidence currently supports.<\/p>\n References<\/h3>\n\n- Bergstr\u00f6m G, Engstr\u00f6m G, Bj\u00f6rnson E, et al. Coronary computed tomography angiography in prediction of first coronary events. JAMA<\/em>. 2026;335(3):245-254. doi:10.1001\/jama.2025.21077. (Published online November 9, 2025.)<\/li>\n
- Williams MC, Kwiecinski J, Doris M, et al. Low-attenuation noncalcified plaque on coronary computed tomography angiography predicts myocardial infarction: results from the multicenter SCOT-HEART trial (Scottish Computed Tomography of the HEART). Circulation<\/em>. 2020;141(18):1452-1462. doi:10.1161\/CIRCULATIONAHA.119.044720<\/li>\n
- Bernardo R, Nurmohamed NS, Bom MJ, et al. Diagnostic accuracy in coronary CT angiography analysis: artificial intelligence versus human assessment. Open Heart<\/em>. 2025;12(1):e003115. doi:10.1136\/openhrt-2024-003115<\/li>\n
- van Rosendael A, Nakanishi R, Bax JJ, et al. Prognostic value of AI-based quantitative coronary CTA vs human reader-based visual assessment: results from the CONFIRM2 registry. JACC Cardiovasc Imaging<\/em>. 2026;19(3):345-359. doi:10.1016\/j.jcmg.2025.09.021<\/li>\n
- Feuchtner GM, Lacaita PG, Bax JJ, et al. AI-quantitative CT coronary plaque features associate with a higher relative risk in women: CONFIRM2 registry. Circ Cardiovasc Imaging<\/em>. 2025;18(6):e018235. doi:10.1161\/CIRCIMAGING.125.018235<\/li>\n
- Nurmohamed NS, Cole JH, Budoff MJ, et al. Impact of atherosclerosis imaging-quantitative computed tomography on diagnostic certainty, downstream testing, coronary revascularization, and medical therapy: the CERTAIN study. Eur Heart J Cardiovasc Imaging<\/em>. 2024;25(6):857-866. doi:10.1093\/ehjci\/jeae029<\/li>\n
- Budoff MJ, Bhatt DL, Kinninger A, et al. Effect of icosapent ethyl on progression of coronary atherosclerosis in patients with elevated triglycerides on statin therapy: final results of the EVAPORATE trial. Eur Heart J<\/em>. 2020;41(40):3925-3932. doi:10.1093\/eurheartj\/ehaa652<\/li>\n
- [Trial registry record] TRANSFORM \u2014 A randomized comparison of Cleerly coronary artery disease stage-based care versus risk factor-based care for primary prevention of cardiovascular events. ClinicalTrials.gov identifier NCT06112418. US National Library of Medicine. Accessed August 2026. Cited for trial design and status only; no results have been reported.<\/li>\n
- Goff DC Jr, Lloyd-Jones DM, Bennett G, et al. 2013 ACC\/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology\/American Heart Association Task Force on Practice Guidelines. Circulation<\/em>. 2014;129(25 suppl 2):S49-S73. doi:10.1161\/01.cir.0000437741.48606.98<\/li>\n
- D\u2019Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation<\/em>. 2008;117(6):743-753. doi:10.1161\/CIRCULATIONAHA.107.699579<\/li>\n
- Hausleiter J, Meyer T, Hermann F, et al. Estimated radiation dose associated with cardiac CT angiography. JAMA<\/em>. 2009;301(5):500-507. doi:10.1001\/jama.2009.54<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"
Imagine que voc\u00ea est\u00e1 dirigindo seu carro por uma rodovia longa e silenciosa. Voc\u00ea se sente seguro porque est\u00e1 olhando para o seu painel. O tanque de combust\u00edvel est\u00e1 cheio, a temperatura do motor est\u00e1 normal e nenhuma luz de advert\u00eancia est\u00e1 piscando. Para voc\u00ea, o carro parece perfeito. Mas bem no fundo do motor, fora de vista, uma pequena linha de combust\u00edvel est\u00e1 vazando ou uma correia est\u00e1 come\u00e7ando a se desgastar. Voc\u00ea n\u00e3o saberia que h\u00e1 um problema apenas olhando para o painel. Voc\u00ea s\u00f3 saberia se parasse no acostamento, abrisse o cap\u00f4 e pedisse para um mec\u00e2nico examinar as pe\u00e7as reais.<\/p>\n A publica\u00e7\u00e3o do estudo de Bergstr\u00f6m et al. no Journal of the American Medical Association (JAMA) em 9 de novembro de 2025 representa um momento marcante na transi\u00e7\u00e3o da estimativa de risco baseada na popula\u00e7\u00e3o para a avalia\u00e7\u00e3o de risco individualizada baseada em doen\u00e7as.\u00b9 Este estudo de coorte observacional, realizado como parte do Estudo de Bioimagem Cardiopulmonar Sueco (SCAPIS), analisou 24.791 indiv\u00edduos com idade entre 50 e 64 anos sem doen\u00e7a cardiovascular estabelecida.<\/p>","protected":false},"author":16,"featured_media":8696,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[229,230,219,223],"tags":[],"class_list":["post-8687","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-imaging-and-detection","category-imaging-and-testing","category-lipids-medications-and-testing","category-plaque-arteries-and-disease"],"acf":[],"yoast_head":"\n A New Way of Looking Inside Your Heart Without Surgery - The Best Way to Predict a Heart Attack - The Premiere Heart Health Education Platform<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.curingheartdisease.com\/pt\/uma-nova-maneira-de-olhar-para-dentro-do-seu-coracao-sem-cirurgia-a-melhor-maneira-de-prever-um-ataque-cardiaco\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A New Way of Looking Inside Your Heart Without Surgery - The Best Way to Predict a Heart Attack - The Premiere Heart Health Education Platform\" \/>\n<meta property=\"og:description\" content=\"Imagine you are driving your car down a long, quiet highway. 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The publication of the Bergstr\u00f6m et al. study in the Journal of the American Medical Association (JAMA) on November 9, 2025, represents a landmark moment in the transition from population-based risk estimation to individualized, disease-based risk assessment.\u00b9 This observational cohort study, conducted as part of the Swedish Cardiopulmonary Bioimage Study (SCAPIS), analyzed 24,791 individuals aged 50 to 64 years without established cardiovascular disease.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.curingheartdisease.com\/pt\/uma-nova-maneira-de-olhar-para-dentro-do-seu-coracao-sem-cirurgia-a-melhor-maneira-de-prever-um-ataque-cardiaco\/\" \/>\n<meta property=\"og:site_name\" content=\"The Premiere Heart Health Education Platform\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/curingheartdisease\" \/>\n<meta property=\"article:published_time\" content=\"2026-01-30T21:58:20+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-09-01T13:00:31+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.curingheartdisease.com\/wp-content\/uploads\/2026\/01\/post-image-25.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"630\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Peter Megdal PhD\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@RMHDInc\" \/>\n<meta name=\"twitter:site\" content=\"@RMHDInc\" \/>\n<meta name=\"twitter:label1\" content=\"Escrito por\" \/>\n\t<meta name=\"twitter:data1\" content=\"Peter Megdal PhD\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. tempo de leitura\" \/>\n\t<meta name=\"twitter:data2\" content=\"14 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.curingheartdisease.com\\\/a-new-way-of-looking-inside-your-heart-without-surgery-the-best-way-to-predict-a-heart-attack\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.curingheartdisease.com\\\/a-new-way-of-looking-inside-your-heart-without-surgery-the-best-way-to-predict-a-heart-attack\\\/\"},\"author\":{\"name\":\"Peter Megdal PhD\",\"@id\":\"https:\\\/\\\/www.curingheartdisease.com\\\/#\\\/schema\\\/person\\\/1468f3f6d05d6929d0583938c1236e53\"},\"headline\":\"A New Way of Looking Inside Your Heart Without Surgery – The Best Way to Predict a Heart Attack\",\"datePublished\":\"2026-01-30T21:58:20+00:00\",\"dateModified\":\"2026-09-01T13:00:31+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.curingheartdisease.com\\\/a-new-way-of-looking-inside-your-heart-without-surgery-the-best-way-to-predict-a-heart-attack\\\/\"},\"wordCount\":3034,\"publisher\":{\"@id\":\"https:\\\/\\\/www.curingheartdisease.com\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/www.curingheartdisease.com\\\/a-new-way-of-looking-inside-your-heart-without-surgery-the-best-way-to-predict-a-heart-attack\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.curingheartdisease.com\\\/wp-content\\\/uploads\\\/2026\\\/01\\\/post-image-25.jpg\",\"articleSection\":[\"Imaging and Detection\",\"Imaging and Testing\",\"Lipids, Medications and Testing\",\"Plaque, Arteries and Disease\"],\"inLanguage\":\"pt-BR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.curingheartdisease.com\\\/a-new-way-of-looking-inside-your-heart-without-surgery-the-best-way-to-predict-a-heart-attack\\\/\",\"url\":\"https:\\\/\\\/www.curingheartdisease.com\\\/a-new-way-of-looking-inside-your-heart-without-surgery-the-best-way-to-predict-a-heart-attack\\\/\",\"name\":\"A New Way of Looking Inside Your Heart Without Surgery - 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