Research Projects Funded

Kidney Cancer Research Your Donations Have Made Possible or Projects you are Currently Funding

Pathomics to predict the prognosis of patients with kidney cancer

Climb for Kidney Cancer made a pilot donation to the Center of Computational Imaging and Personalized Diagnostics at Case Western Reserve University with Dr. Anant Madabhushi. Through this grant we hope to spur the use of AI Computer Vision to predict prognosis from the H&E stain pathologic slides. This will help provide pilot data for a larger peer reviewed grant, thus leveraging your donations to Climb4KC.

International AI Challenge to predict aggressive kidney cancer on CT imaging, in conjunction with IBM-Knight Challenge 2022 with ISBI conference

Crowdsourcing Kidney Cancer Deep Learning KiTS21

In 2021 we hosted another international kidney and kidney tumor challenge in association with the 2021 MICCAI meeting. This time we segmented each of ~50,000 CT images from Kidney Cancer patients three times to see if teams could use this additional information to make better segmentations models.

Kidney Cancer Research Scholarships

This will be the fourth year of offering these summer research fellowships.  Because of the success we’ve had over the past several years, we had nearly 20 Climb 4 Kidney Cancer Scholars.  These scholarships will be used to attract some of the best and brightest minds to spend the summer carrying out kidney cancer research.  We hope to inspire these students to choose a career where they can help kidney cancer patients.  Funds will be used to provide a modest stipend, additional funds will be used for equipment necessary to carry out their research, computers, statistical and IT support, and funds to present their findings at national and international meetings such as the American Urological Association Annual Meeting and the GUASCO cancer symposium. Meet the Past Scholars.

Kidney Cancer Deep Learning Research Project – KITS19

This project aims to use CT scan images in patients with kidney tumors, combined with clinical data to automate the detection of kidney tumors and predict patient-relevant outcomes.  This cutting-edge research uses a technique known as Deep Learning and has shown promise in medical imaging.  With your help, we hope to create the world’s largest imaging archive of annotated kidney tumors on CT scans with detailed clinical data.  It will be called the Climb 4 Kidney Cancer or C4KC Kidney Tumor Database hosted on The Cancer Imaging Archive.

In 2019, we hosted an international contest to stimulate collaborative kidney cancer research and allow scientists from around the world to create algorithms that can automatically find a kidney and a kidney tumor.  Over 800 teams joined the challenge and 106 teams submitted predictions.  We completed another international kidney cancer AI challenge for the 2021 MICCAI conference.

Our past challenge helped to coordinate around 20,000 hours of kidney cancer research all around the world!

Our team was recognized as the top challenge attracting the highest number of participants for a 3D segmentation challenge ever, and having the most submissions ever to a challenge!  Your donations led to the coordination of 20,000+ hours of kidney cancer research!  Our research was also honored as the top paper in the imaging section of the EAU annual meeting in Barcelona, Spain 2019.

3D Printed Kidney Cancer Models for Surgical Planning and Education

We created one of the world’s first 3D printed kidney tumor models for simulated kidney cancer surgery on the Da Vinci Robot.  We developed a realistic kidney model with a tumor and 10 surgeons performed a simulated Kidney Cancer surgery.  When we develop this technology to be high fidelity and patient-specific we can create a realistic model that the surgeon could practice the surgery prior to doing the real one.  Now we’re working to improve the model with more lifelike materials as well as generating virtual reality models.

3D Printed Kidney with Tumor from CT Scan for Surgical Simulation U of Minnesota 2019

Automated Kidney Cancer Detection

We teamed up with computer scientists to create convoluted neural networks sometimes called machine learning or artificial intelligence to try and teach a computer to recognize a kidney and kidney tumor on CT imaging.  Through this project, we hope to assure those kidney tumors are never missed and hope to improve cancer predictions and outcomes in patients with renal tumors.

Gene Therapy

We need funding for a clinical trial of an exciting new gene therapy that has shown surprising success in a mouse model. This therapy has been shown to be safe in the phase 1 human model and the next step is to try it on a limited number of patients with kidney cancer.

Kidney Cancer Patient Education Tools

We have been working on a patient education application for patients with kidney cancer to be used on a tablet or phone.  This can replace hard to interpret doctors’ drawings, fuzzy ultrasounds, etc with images of kidneys and tumors corresponding with patient’s tumors that they can manipulate and understand the anatomy of the kidney and cancer and understand the potential complications of treatment.  Here is a mock-up of several possibilities, but we currently lack funding to finish the project.

Why Donate?
Kidney Cancer and Lack of Funding

Kidney Cancer is severely underfunded compared to other cancers.  Though kidney cancer falls in the top ten most common cancers, there has not been the same level of advocacy for kidney cancer compared to other top cancers like Breast, Prostate, Colon, and Lung.  We’re trying to fix that.

How to Help

Donate directly today. Your donation will be made to Team8. Climb 4 Kidney Cancer is a division of Team8, a 501-c non-profit dedicated to raising money for kidney cancer research. Learn more about us.

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Contact us for other ways to donate to these important projects at hello@climb4kc.org