OT: The biggest advance in science brought about by AI so far:
....on topic
....I know someone who would disagree
....an application where time is absolutely critical and can / is changing lives forever for the fortunate ones
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QUESTION:
is AI currently used in any meaningful way to interpret mri / cat scans in a more timely and accurate way for stroke victims
Yes, absolutely. AI is currently used in a highly meaningful and impactful way to interpret MRI and CT scans for stroke victims, fundamentally changing the acute stroke workflow.
The urgency of stroke care—where "time is brain"—makes it one of the most successful and widespread applications of AI in medicine.
Here are the primary areas of meaningful impact in terms of timeliness and accuracy:
1. Timeliness: Drastically Reducing Time-to-Treatment
AI's most significant clinical benefit is speed, which directly translates to better patient outcomes.
- Triage and Prioritization (The "AI Alert"): AI software analyzes the scan (usually a non-contrast CT or CT Angiography/Perfusion) immediately upon acquisition, often in minutes. If it detects a critical finding like a Large Vessel Occlusion (LVO) or an Intracranial Hemorrhage (ICH), it automatically sends an alert to the entire stroke team (neurologists, neuro-interventionalists, emergency room staff) via mobile devices. This bypasses the traditional waiting time for a human radiologist's initial read and communication.
- Clinical Result: Studies have shown that AI tools can significantly reduce the time from a patient arriving at the door to them receiving treatment (door-to-treatment time), in some cases saving over 20 minutes, which is crucial for maximizing the amount of salvageable brain tissue.
- Facilitating Transfers: For patients in smaller "spoke" hospitals that need to be transferred to a larger "hub" hospital for clot removal (thrombectomy), AI enables the hub's specialists to see the images and the AI's analysis before the patient even arrives, allowing the operating team to be ready the moment the patient rolls in.
2. Accuracy: Enhancing Diagnosis and Treatment Decisions
AI helps both confirm and quantify damage, leading to more informed treatment decisions.
- Quantitative Analysis (Perfusion): For ischemic stroke, treatment depends on the amount of brain tissue that is already dead (core infarct) versus the tissue that is still at risk but salvageable (penumbra). AI software automatically calculates and color-codes these volumes from CT Perfusion or MRI scans, providing objective, standardized data.
- Clinical Result: This quantitative data is essential for determining a patient's eligibility for life-saving procedures like mechanical thrombectomy, especially for patients presenting outside the traditional six-hour treatment window.
- High Diagnostic Efficacy: AI systems demonstrate a high level of diagnostic accuracy, with meta-analyses showing:
- Hemorrhagic Stroke (ICH): Pooled sensitivity (correctly identifying a stroke) and specificity (correctly ruling out a stroke) are often above 90%, closely approaching that of human radiologists.
- Ischemic Stroke: Similar high performance is seen for detecting signs of clot and ischemia.
In short, AI for stroke imaging is far beyond a promising research tool—it is a widely adopted, FDA-cleared and clinically validated technology that is an essential part of the workflow in thousands of hospitals and is increasingly integrated into major health guidelines for acute stroke management.
QUESTION:
OK....to what extent have these AI techniques been implemented?
The implementation of AI techniques in acute stroke imaging is already widespread and an expected standard of care, particularly in major stroke centers in developed nations.
It is no longer a niche research topic; it is an active and expanding commercial market integrated into the standard clinical workflow.
Here is a breakdown of the extent of implementation:
1. High Adoption in US Stroke Centers
- Widespread Use: Surveys of US stroke centers indicate that a very high percentage, around 85% or more, of certified high-volume stroke centers (those that perform the most life-saving clot removal procedures, or Endovascular Thrombectomy - EVT) utilize AI for imaging analysis.
- Focus on EVT Centers: The adoption is highest in Comprehensive Stroke Centers (CSCs) and Thrombectomy-Capable Stroke Centers (TSCs) because the AI's primary function—detecting large vessel occlusions (LVOs) and quantifying salvageable tissue—is directly tied to their most critical procedures.
- Leading Platforms: Commercial platforms like Viz.ai and RapidAI are the dominant players in the US market, with each reporting adoption in over 1,500 hospitals nationwide, including the majority of the largest healthcare systems.
2. Global Commercial Expansion
- Global Footprint: The leading AI platforms have achieved significant international adoption. For example, one major platform reported being in use in over 1,600 hospitals across more than 60 countries.
- Market Growth: The global market for AI in stroke detection is experiencing a massive surge, with projections for the market size to grow substantially, reflecting a rapid and increasing rate of implementation worldwide.
3. Integration into Guidelines and Expected Standards
- AHA/ASA Requirements: Major professional organizations, such as the American Heart Association (AHA) and American Stroke Association (ASA), have begun to explicitly integrate the use of AI into the foundational requirements for certified stroke programs. This establishes AI-assisted neuroimaging for CT and CT Angiography (CTA) as a minimum expectation for stroke centers.
- Workflow Integration: The AI is not a separate application; it's often designed to run in parallel with the hospital's Picture Archiving and Communication System (PACS). This means the analysis runs automatically and alerts are sent simultaneously to the care team while the images are still being acquired and prepared for the human radiologist.
4. Current Focus of Implementation
The most common and clinically integrated applications include:
| AI Function | Modality | Purpose in Clinical Practice | | LVO Detection & Alerting | CTA | Timeliness: Automatically detects the most critical large vessel clots and sends an immediate mobile alert to the interventional team. | | Perfusion Analysis | CTP or MRI | Accuracy/Decision-Making: Automatically calculates the volume of the ischemic core (dead tissue) and penumbra (at-risk tissue) to determine eligibility for thrombectomy. | | ICH Detection & Triage | Non-Contrast CT | Timeliness: Detects life-threatening bleeding and prioritizes the case for immediate physician review. | | e-ASPECTS Scoring | Non-Contrast CT | Accuracy/Standardization: Automatically calculates the Alberta Stroke Program Early CT Score, which is a key measure of early ischemic damage. |
In essence, for any patient presenting to a major hospital in the US or other high-resource countries with suspected acute stroke, it is highly likely that an AI program will analyze their CT or MRI scans and generate its findings before the human stroke specialist has formally signed the report.
QUESTION:
so if an outlying hospital can use this AI technique and produce a good diagnosis within an hour of the stroke onset, the patient could possibly be transferred to a stroke center hospital in time (in less than 4 hours of the stroke) to effect a procedure that can prevent permanent brain damage??....is this realistic?
Yes, this scenario is absolutely realistic and is the primary goal and proven outcome of implementing AI in stroke care systems.
The ability of an outlying hospital (often called a "spoke" hospital) to quickly diagnose and transfer a patient to a stroke center (a "hub" hospital) for a permanent brain damage-preventing procedure (Endovascular Thrombectomy, or EVT) is precisely where AI offers its most significant benefit.
1. The Critical AI Impact: Reducing Transfer Time
The AI's main contribution in the transfer process is drastically reducing the Door-In-Door-Out (DIDO) time at the first hospital.
- Before AI (Serial Workflow): A suspected stroke patient arrives at the spoke hospital, gets a CT scan, the scan is sent to the local radiologist queue, the radiologist reads it, reports an LVO, the ED doctor calls the hub neurologist, who then calls the interventionalist. This is a serial process, with delays at every step.
- Real-world median DIDO times without AI were often over 3 hours (174-227 minutes).
- With AI (Parallel Workflow):
- The patient gets a CT scan.
- The AI software immediately analyzes the images (in minutes).
- If a Large Vessel Occlusion (LVO) is detected, the AI sends an automated, simultaneous alert to the entire stroke team at both the spoke hospital and the receiving hub hospital (the neurologist, interventionalist, and transfer team) via a mobile app.
- The hub team can review the images and the AI's analysis from their phone and begin preparing the Cath Lab while the patient is still being stabilized and prepped for transport at the spoke hospital. This is a parallel process.
- Proven Results: Studies show that AI implementation in spoke hospitals has significantly reduced DIDO times by an average of 39 to over 100 minutes, with many hospitals achieving the goal of reducing their DIDO time by nearly 50%.
2. Making the 4-Hour Goal Achievable
You asked if the patient could be transferred in time (in less than 4 hours of the stroke onset) to effect a procedure.
The critical target is the total time from Last Known Well (LKW) to the start of the EVT procedure (groin puncture), which is ideally within 6 hours, but even 4 hours is better.
| Typical Times in an Optimized AI System | Time Window | | Stroke Onset (LKW) to Spoke Hospital Arrival | 30 - 60 minutes | | Spoke Hospital Workup (CT/AI Diagnosis) | 30 - 60 minutes | | Spoke Hospital Door-In-Door-Out (DIDO) | Target: < 120 minutes (2 hours) | | Total Time until Transfer Out | ~2.5 hours from LKW | | Transfer Time (Air/Ground) | 30 - 90 minutes (highly variable) | | Arrival at Hub Hospital | ~3-4 hours from LKW |
By shaving an hour or more off the DIDO time, the AI system makes it highly feasible for many patients who present to a spoke hospital to arrive at the comprehensive stroke center within the critical 4.5-hour window (the limit for the dissolving drug tPA) or the 6-hour window (the earliest definitive EVT window).
3. The Power of the "Tissue Window"
Even more importantly, the AI is essential for determining if a patient is still eligible for EVT even beyond 6 hours (up to 24 hours).
The AI software (specifically the perfusion component) doesn't just look at the clock; it looks at the tissue. It automatically quantifies the size of the irreversibly damaged tissue (ischemic core) versus the salvageable tissue (penumbra).
This allows the stroke center to proceed with the EVT procedure based on the amount of brain tissue at risk—the "tissue window"—rather than a strict, unforgiving time cutoff.
In summary, AI is the "time saver" that converts a delayed, borderline case at a rural hospital into a successful, time-sensitive intervention at a comprehensive stroke center, maximizing the chances of preventing permanent disability. |
