AI Boosts Knee Replacement Success to 90%

FEATURED RESEARCH

AI Boosts Knee Replacement Success to 90%

Total knee arthroplasty (TKA) is a surgical procedure that replaces a damaged knee joint with a prosthesis to relieve pain and restore function.

It’s a common solution for severe knee osteoarthritis, but traditional methods have limitations.

Now, researchers from Fujian Medical University are using AI to create detailed 3D models of the knee, improving the accuracy of preoperative planning and enhancing patient outcomes.

Why it matters: Traditional methods for preoperative planning in TKA rely on two-dimensional (2D) X-ray templates, which can be imprecise due to variances in X-ray positioning and magnification.

This often leads to mismatches in prosthesis size and alignment, potentially causing pain, joint stiffness, and reduced prosthesis lifespan.

The breakthrough: By using computed tomography (CT) data, AI algorithms create detailed three-dimensional models of the knee. This allows for highly accurate predictions of prosthesis size and alignment, tailored to each patient’s unique anatomy.

Results you can see:

In the study comparing 60 patients who underwent TKA, those who received AI-based 3D planning had significantly better outcomes:

• Precision: The AI group had a 90% accuracy rate in prosthesis size prediction, compared to just 66.7% in the 2D group.

• Alignment: The AI group also showed better femoral valgus correction angles and hip-knee-ankle angles, critical for joint stability and function.

• Recovery: Patients in the AI group reported higher satisfaction and better knee function scores at 3, 6, and 12 months post-surgery.

The impact: AI-driven 3D planning enhances surgical precision, improves patient recovery, and increases prosthesis longevity. This means fewer complications, less pain, and better mobility for patients.

For more details: Full Article

Brain Booster

Rosalind Franklin is best known for her work on which biological structure?

1. Mitochondria

2. Ribosomes

3. DNA

4. Chloroplasts

See below for the answer!

Seed to Success

NASAL RELIEF

SoundHealth Scores $7M to Launch AI-Driven Nasal Congestion Device

SoundHealth has secured $7 million in seed funding and launched SONU, an AI-enabled wearable device for nasal congestion relief.

This device, the first of its kind to receive FDA authorization, uses acoustic resonance therapy to treat allergic and non-allergic rhinitis, providing a drug-free solution to nasal congestion.

What is the device: Their latest product, SONU, combines AI with acoustic resonance therapy to relieve nasal congestion. Users scan their face with the SONU app, and the headband delivers personalized frequencies to clear nasal passages.

Why it matters: Nasal congestion affects one in four Americans daily, leading to sleep problems and other health issues. Traditional treatments often involve medications with side effects.

SONU offers a non-invasive, side-effect-free alternative, making it a significant advancement in respiratory health.

Future plans: With the new funding, SoundHealth plans to expand SONU’s applications to pediatric care and insomnia treatments. The company also aims to scale up production to meet increasing demand and continue clinical research to explore further uses of their technology.

For more details: Full Press Release

💰 6 Other funded companies

1. Radiology AI startup deepc raised $13 million in a Series A extension round, bringing its total funding to $30 million, to expand its AI integration platform in clinical settings and accelerate growth in North America and Europe.​ [Link]

2. Lumen raised €1 million in a single day on SeedBlink for its smart glasses designed for the visually impaired, which use Pedestrian Autonomous Driving (PAD AI) technology to replicate the functions of a guide dog. [Link]

3. Pearl raised $58 million in Series B funding to enhance its FDA-cleared AI dental diagnostics solutions. [Link]

4. Clarapath raised $36 million in a Series B round led by Northwell Ventures to commercialize its SectionStar™ platform, aiming to automate and modernize pathology lab processes, addressing labor shortages and enhancing diagnostic consistency. [Link]

5. Azitra, Inc., a biopharmaceutical company developing precision dermatology therapies using engineered proteins and AI-driven microbial screening, announced a $10 million public offering to fund their operations. [Link]

6. Subtle Medical raised $10 million in a Series B+ round, led by Samsung Ventures, bringing the total Series B to over $30 million to support the expansion of its AI-powered medical imaging technology globally. [Link]

New Partnerships

PRECISION ONCOLOGY

QDX Teams Up with Prelude Therapeutics to Tackle Uncharted Cancer Targets

QDX, a computational drug discovery company, has announced a significant collaboration with Prelude Therapeutics, a clinical-stage precision oncology company.

This partnership focuses on identifying and targeting previously undrugged oncology targets, aiming to develop new cancer therapies.

What’s happening: QDX utilizes its expertise in quantum mechanical simulations, supercomputing, and AI to push the boundaries of computational chemistry and drug discovery.

Prelude Therapeutics brings its precision oncology insights, making this collaboration poised to address some of the most challenging targets in cancer treatment.

The impact: This collaboration highlights the growing role of computational approaches in drug discovery.

The integration of quantum simulations and AI allows for the exploration of complex molecular interactions, potentially leading to breakthroughs in treating hard-to-target cancers.

Next steps: The partnership aims to accelerate the development of small molecules against critical oncology targets.

Peggy Scherle, CSO of Prelude, expressed optimism about the promise of computational drug discovery, while QDX's CEO, Loong Wang, emphasized the bespoke nature of the partnership, combining high-performance computing and innovative drug discovery methods.

For more details: Full Press Release

🤝 6 Other collaborations shaping the future

1. Humana has partnered with Google Cloud in a multiyear agreement to enhance its cloud infrastructure and develop generative AI solutions aimed at improving operational efficiency, clinical insights, and personalized care for its members. [Link]

2. Microsoft is collaborating with Mass General Brigham and the University of Wisconsin-Madison to develop AI models for radiology, aiming to improve medical image analysis and integrate AI solutions into clinical workflows using the Microsoft Azure AI platform. [Link]

3. Abridge, in collaboration with Epic and Mayo Clinic, is developing generative AI tools to enhance documentation workflows for nurses, aiming to reduce their administrative burden and improve efficiency. [Link]

4. The American Kidney Fund is partnering with Ubie to use AI for speeding up early kidney disease diagnoses by improving their AI-powered Symptom Checker. [Link]

5. Appier partnered with SkinX Thailand to implement its AI solutions, AIRIS and AIQUA, enhancing customer engagement and streamlining operations for SkinX's teledermatology services. [Link]

6. Emmes Group partnered with Miimansa AI to enhance clinical research by integrating Miimansa's generative AI tools into its Veridix AI platform, aiming to automate text processing and improve clinical trial efficiency. [Link]

Milestone Moments

⚡2 Product launches, 3 acquisition

1. Insilico Medicine has introduced an AI assistant named DORA to help draft medical research papers, targeting early-career researchers and non-native English speakers, with a free trial available later this year. [Link]

2. GE HealthCare is acquiring AI assets from Intelligent Ultrasound Group for $51 million to enhance real-time support in OB/GYN ultrasound exams and plans to integrate this technology across its broader ultrasound portfolio. [Link]

3. Commure is acquiring Augmedix for $139 million in an all-cash deal, aiming to strengthen its position in the competitive AI medical scribe market by integrating Augmedix’s ambient documentation solutions into its platform. [Link]

4. Sonio launched Soniopedia, an AI-powered tool for training prenatal diagnosis, offering real-time diagnostic simulations and a comprehensive cloud-based database to improve maternal-fetal medicine expertise. [Link]

5. Linus Health acquired Together Senior Health to enhance its AI capabilities for early detection and intervention of cognitive decline, integrating evidence-based solutions like the Moving Together™ program and the RADAR algorithm. [Link] 

Opinion and Perspectives

BIASED TRAINING DATA

The Hidden Risks of AI in Medical Devices

The big picture: As AI devices continue to shape healthcare, a pressing issue emerges: the risk of inherent biases. The recent FDA approval of DermaSensor, an AI-powered device aiding primary care physicians in detecting skin cancer, brings this issue to the forefront.

This innovation, while a significant step forward, also highlights the potential for deepening healthcare disparities if not carefully managed.

Why it matters: AI's integration into healthcare brings both opportunities and challenges. DermaSensor allows primary care physicians to assess skin cancer, reducing delays in diagnosis, particularly in areas with limited access to dermatologists.

However, the pivotal study for DermaSensor included 97.1% White participants, with only 0.7% Black or African Americans and 0.9% Asians, which could affect its accuracy for non-White patients.

Skin cancer is prevalent, with over 9,500 diagnoses and two deaths daily in the U.S. One in five Americans will develop skin cancer by age 70, making timely and accurate diagnosis crucial.

Furthermore, as of May 2024, 84% of the 882 FDA-approved AI/ML-powered devices were authorized in the last five years, raising concerns about whether current regulations ensure safety and efficacy.

The big picture: To ensure AI in healthcare is equitable and effective, it is essential to collect more diverse datasets to reduce biases and improve AI accuracy across all demographic groups.

The FDA should refine its evaluation processes to address AI-specific challenges, focusing on data quality and ongoing performance monitoring.

Applying equity-focused perspectives in AI development and regulatory approvals is crucial to meet public health needs and provide fair outcomes for all patients.

For more details: Full Article

We Value Your Thoughts!

Trivia Answer: DNA

Rosalind Franklin's X-ray diffraction images of DNA, especially "Photo 51," provided critical evidence for the double helix structure. Her precise measurements revealed key details, such as the helical shape and repeating structure, which were essential for Watson and Crick to finalize their DNA model.

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