Presentation clinical applications of Artificial Intelligence for radiation oncology
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Presentation for the European Society for Therapeutic Radiation Oncology annual meeting of 2019 - ESTRO38
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Artificial Intelligence in Radiation Oncology
- The document discusses the use of artificial intelligence and radiomics in radiation oncology. It presents frameworks for radiomics analysis involving image registration, tumor segmentation, feature extraction, and predictive modeling.
- Specific applications discussed include using radiomics for lung cancer screening and prediction of tumor response. Radiomics features combined with machine learning models show improved performance over clinical guidelines for assessing lung nodule malignancy.
- Methods are also presented for quantifying tumor characteristics like spiculation through image analysis and extracting interpretable radiomics features. This can provide semantic information to radiologists for assessment.
Artificial Intelligence in Radiation Oncology.pptx
The document discusses artificial intelligence applications in radiation oncology, including automatic delineation of organs-at-risk using deep learning models like OARNet. It also discusses radiomics approaches for clinical decision support and outcomes prediction using features extracted from medical images with techniques like spiculation quantification for lung cancer screening.
Artificial Intelligence in Radiation Oncology
This document discusses artificial intelligence applications in radiation oncology. It begins with acknowledgements and then outlines several AI applications including radiomics tools for lung cancer screening, tumor response prediction, and predicting aggressive lung adenocarcinoma subtypes. It also discusses using AI for automatic tumor delineation and quantification of delineation variability as well as local tumor morphological changes prediction and metabolic tumor volume changes. The document provides details on methods and results for several of these AI applications in radiation oncology.
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Motion Management in Radiation Therapy
Motion management strategies in radiation therapy aim to account for tumor movement during treatment. Key strategies include gating methods that deliver radiation only during specific respiratory phases, breath hold methods that immobilize tumors during deep inhalation or exhalation, tracking methods that follow tumor motion in real-time and adjust beam targeting accordingly, and encompassing methods that define larger target volumes to cover full respiratory excursion. No single approach is clearly superior, as appropriate management depends on tumor location, motion extent, and available technology. The goal of all motion management is to safely escalate dose to tumors while reducing dose to surrounding healthy tissues.
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Artificial Intelligence in Radiation Oncology
- The document discusses the use of artificial intelligence and radiomics in radiation oncology. It presents frameworks for radiomics analysis involving image registration, tumor segmentation, feature extraction, and predictive modeling.
- Specific applications discussed include using radiomics for lung cancer screening and prediction of tumor response. Radiomics features combined with machine learning models show improved performance over clinical guidelines for assessing lung nodule malignancy.
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Artificial Intelligence in Radiation Oncology.pptx
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SBRT in lung cancer
This document provides an overview of image-guided radiation therapy (IGRT) for lung cancer. It discusses the role of IGRT in managing tumor motion through techniques like breath hold methods, free breathing with gating or tracking, and 4D imaging. Segmentation of the tumor and organs at risk on 4D CT scans is covered. Dose fractionation schedules and biological effective dose calculations for hypofractionated stereotactic body radiation therapy are reviewed. Toxicities, outcomes, and challenges of IGRT in lung cancer are also mentioned.
Final ICRU 62 ( International commission on radiation units and measurements)
The document discusses recommendations from reports by the International Commission on Radiation Units and Measurements (ICRU) for defining volumes used in radiation therapy planning and reporting. ICRU Report 62 provides additional details on volumes such as the internal target volume (ITV) and planning organ at risk volume (PRV), and introduces metrics like the conformity index. It also further classifies organs at risk as serial, parallel or serial-parallel based on their radiosensitivity.
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TBI is the radiotherapy technique to irradiate whole body before doing stem cell transplant. The main purpose of doing TBIB is to condition the immune system of body so that there will be maximum chance of transplant acceptance.
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Motion Management in Radiation Therapy
Motion management strategies in radiation therapy aim to account for tumor movement during treatment. Key strategies include gating methods that deliver radiation only during specific respiratory phases, breath hold methods that immobilize tumors during deep inhalation or exhalation, tracking methods that follow tumor motion in real-time and adjust beam targeting accordingly, and encompassing methods that define larger target volumes to cover full respiratory excursion. No single approach is clearly superior, as appropriate management depends on tumor location, motion extent, and available technology. The goal of all motion management is to safely escalate dose to tumors while reducing dose to surrounding healthy tissues.
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Stereotactic Body Radiation Therapy
Stereotactic body radiation therapy (SBRT) uses advanced technology to deliver high ablative doses of radiation to tumors in a precise manner. SBRT has been shown to be effective in treating various tumor types with acceptable toxicity. However, long term toxicity requires further study. New techniques aim to reduce treatment margins and account for organ motion to minimize dose to surrounding healthy tissues while ensuring accurate dose delivery to the tumor. SBRT shows promise but further prospective clinical trials are needed to fully evaluate efficacy and safety.
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Image Guided Radiation Therapy (IGRT)
This document discusses Image Guided Radiation Therapy (IGRT). It begins by explaining that radiotherapy has traditionally used imaging for treatment planning and execution when the target is not on the surface. It then describes various IGRT technologies, dividing them into non-radiation based systems like ultrasound, cameras, electromagnetic tracking and MRI; and radiation based systems like EPID, CBCT, fan beam KVCT and MVCT. These systems provide improved target localization and allow for corrections. IGRT aims to reduce errors and improve precision of radiotherapy.
Intensity modulated radiation therapy and Image guided radiation therapy
This document discusses various modern radiation therapy techniques including IMRT, IGRT, MVCBCT, and KVCBCT. It provides background on 2D and 3D conformal radiation therapy. IMRT uses intensity modulated beams and inverse planning to improve dose distribution. IGRT uses imaging before and during treatment for precise targeting. MVCBCT and KVCBCT provide volumetric imaging using megavoltage and kilovoltage sources, with KVCBCT offering better soft tissue contrast. Errors in patient positioning can be detected and corrected using these image-guided techniques.
Radiotherapy in nasopharynx
1) Radiotherapy is the primary treatment for nasopharyngeal carcinoma due to the excellent response to radiation and proximity to critical structures making surgery difficult.
2) Concurrent chemoradiation provides the greatest survival benefits compared to radiotherapy alone or adjuvant chemotherapy alone based on multiple studies. A network meta-analysis found the treatments with the highest probability of benefit were chemoradiation followed by adjuvant chemotherapy.
3) Positioning and immobilization techniques such as thermoplastic masks are used to precisely deliver high radiation doses to target volumes while sparing surrounding healthy tissues. Intensity-modulated radiotherapy has improved the conformality and reduced side effects compared to 3D conformal radiotherapy.
Prophylactic cranial irradiation
Prophylactic cranial irradiation (PCI) is used to prevent brain metastases in cancers with a high risk of spreading to the brain. It is indicated for small cell lung cancer and certain leukemias. PCI significantly reduces the rate of brain metastases in small cell lung cancer, especially when administered early at higher doses. For extensive stage small cell lung cancer, MRI surveillance may be an alternative to PCI. While PCI reduces brain metastases in leukemia, the risk of brain involvement is low for some types such as AML. The standard dose for PCI is 1200-1800 cGy in fractions, with timing and volumes depending on the cancer type. Potential toxicities include neurocognitive effects, endocrine disorders, and secondary cancers.
Smart radiotherapy
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Radiotherapy in ca esophagus
1) The document discusses various radiation techniques for treating cancer of the esophagus including 2D, 3D conformal radiation therapy, IMRT, and IGRT.
2) It covers topics like target volume delineation, field design considerations for different esophageal subsites, and evolution from 2D to 3D treatment planning.
3) While there is no consensus, most contemporary trials use margins of 3-5cm cranially and caudally on the gross tumor with approximately a 2cm radial margin.
Lecture-2-amber.pdf
AI techniques are being explored to derive real-world evidence from routine medical imaging and reports. Image segmentation algorithms can identify tumors and organs in medical images. Natural language processing of radiology reports containing over 700,000 structured records dating back to 2009 has mapped patterns of metastatic disease and generated real-time survival curves for different cancers using only the uncurated data. Further development aims to uncover true response rates, map cancers of unknown primary back in time, and generate hypotheses for clinical trials to potentially expedite research. Addressing issues around data biases, identity, and social justice will be important to responsibly develop these techniques.
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Stereotactic Body Radiation Therapy
Stereotactic body radiation therapy (SBRT) uses advanced technology to deliver high ablative doses of radiation to tumors in a precise manner. SBRT has been shown to be effective in treating various tumor types with acceptable toxicity. However, long term toxicity requires further study. New techniques aim to reduce treatment margins and account for organ motion to minimize dose to surrounding healthy tissues while ensuring accurate dose delivery to the tumor. SBRT shows promise but further prospective clinical trials are needed to fully evaluate efficacy and safety.
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This document discusses radiation therapy for breast cancer. It begins by outlining the important role of radiation therapy at various stages of breast cancer, including as part of breast conservation and after mastectomy. It then discusses indications for adjuvant radiation therapy based on factors like tumor size and lymph node involvement. The document reviews evidence from clinical trials demonstrating the benefits of radiation therapy after breast-conserving surgery in reducing recurrence rates and improving survival. It also discusses techniques, dosing, and toxicity considerations for radiation therapy delivery.
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Image guided adaptive radiotherapy
This seminar is presented in weekly journal club and seminar held in Apollo Hospital, Kolkata Department of Radiation Oncology.
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This document discusses hemi body irradiation (HBI) technique used to treat metastatic cancer. HBI involves irradiating only the upper or lower half of the body using parallel opposed radiation fields. It has advantages over total body irradiation like smaller field size and less side effects. HBI is used to palliate widely metastatic disease and as adjuvant therapy for certain cancers. Potential complications include nausea, diarrhea, pneumonitis and hematological effects. The document also provides an overview of cancer registries in India, which systematically collect cancer data to help understand cancer patterns and guide control programs. Population-based and hospital-based registries use active and passive methods to collect data on cancer incidence, stages and survival.
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This document discusses the use of stereotactic body radiation therapy (SBRT) for liver tumors. It provides details on common liver tumors including hepatocellular carcinoma and metastases. It describes SBRT as a treatment option for inoperable early stage tumors, as a bridge to transplant, and for intermediate or locally advanced stages. Key factors for patient selection and treatment planning such as tumor size, number and location, as well as liver function are summarized. The document also briefly discusses proton beam therapy and current clinical trials investigating SBRT for liver cancer.
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This document discusses motion management techniques for lung cancer radiotherapy. It begins by explaining why motion management is important, as standard CT scans do not fully capture lung tumor motion. It then describes 4DCT and other methods for assessing tumor motion, as well as techniques like ITV, gating, tracking and breath-holding to control for motion. Specific examples of tracking systems like ExacTrac and Cyberknife are provided. Overall, the document provides an overview of the challenges of lung tumor motion and different strategies used to manage it in radiation treatment planning and delivery.
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This document discusses Image Guided Radiation Therapy (IGRT). It begins by explaining that radiotherapy has traditionally used imaging for treatment planning and execution when the target is not on the surface. It then describes various IGRT technologies, dividing them into non-radiation based systems like ultrasound, cameras, electromagnetic tracking and MRI; and radiation based systems like EPID, CBCT, fan beam KVCT and MVCT. These systems provide improved target localization and allow for corrections. IGRT aims to reduce errors and improve precision of radiotherapy.
Intensity modulated radiation therapy and Image guided radiation therapy
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Radiotherapy in nasopharynx
1) Radiotherapy is the primary treatment for nasopharyngeal carcinoma due to the excellent response to radiation and proximity to critical structures making surgery difficult.
2) Concurrent chemoradiation provides the greatest survival benefits compared to radiotherapy alone or adjuvant chemotherapy alone based on multiple studies. A network meta-analysis found the treatments with the highest probability of benefit were chemoradiation followed by adjuvant chemotherapy.
3) Positioning and immobilization techniques such as thermoplastic masks are used to precisely deliver high radiation doses to target volumes while sparing surrounding healthy tissues. Intensity-modulated radiotherapy has improved the conformality and reduced side effects compared to 3D conformal radiotherapy.
Prophylactic cranial irradiation
Prophylactic cranial irradiation (PCI) is used to prevent brain metastases in cancers with a high risk of spreading to the brain. It is indicated for small cell lung cancer and certain leukemias. PCI significantly reduces the rate of brain metastases in small cell lung cancer, especially when administered early at higher doses. For extensive stage small cell lung cancer, MRI surveillance may be an alternative to PCI. While PCI reduces brain metastases in leukemia, the risk of brain involvement is low for some types such as AML. The standard dose for PCI is 1200-1800 cGy in fractions, with timing and volumes depending on the cancer type. Potential toxicities include neurocognitive effects, endocrine disorders, and secondary cancers.
Smart radiotherapy
Smart radiotherapy aims to precisely target tumor cells while sparing healthy cells. New techniques described in the document include using hypoxic cell sensitizers to target hypoxic tumor regions, anti-angiogenic agents to inhibit tumor blood vessels, and nanoparticles to enhance radiation dose and selectively deliver drugs. Molecular imaging helps optimize treatment by identifying tumor characteristics. Combining radiotherapy with immunotherapy or targeted depletion of host cells may also improve outcomes. Overall, the document discusses developing more precise radiation approaches through better understanding of tumor biology and microenvironment.
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This document discusses intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) optimization algorithms, including direct machine parameter optimization (DVO), leaf motion calculation (LMC), progressive gradient optimization (PGO), and multi-resolution dose calculation (MRDC). It emphasizes that theoretical physicists developing these algorithms have revolutionized the field of radiation oncology by enabling more conformal radiation treatments.
Image Guided Radiotherapy
This document discusses image-guided radiation therapy (IGRT) and its evolution and applications. It begins by defining IGRT as external beam radiation therapy using imaging prior to each treatment fraction to verify patient positioning. IGRT allows for reduction of safety margins by compensating for set-up errors and organ motion. The document then reviews the history of IGRT from early portal imaging to modern cone-beam CT and other volumetric imaging techniques. It provides examples of IGRT protocols and clinical outcomes for sites such as prostate, lung, liver, and central nervous system tumors.
How Radiation Therapy is Used to Treat Soft Tissue Sarcoma
Learn about the process of radiation therapy to treat soft tissue sarcoma, and how new radiation technology has improved treatment of the disease.
This presentation was given by Elizabeth H. Baldini, MD, MPH, radiation oncology director for the Center for Sarcoma and Bone Oncology at Dana-Farber Cancer Institute. It was originally presented as part of the "15 Years of GIST/Soft Tissue Sarcoma Symposium," held on Sept. 12, 2015 at Dana-Farber in Boston, Mass.
PENTEC GUIDELINES FOR PAEDIATRIC RADIOTHERAPY
This document outlines guidelines from the PENTEC group for minimizing late effects from radiation therapy in pediatric patients. It discusses the importance of considering both physical and cognitive development differences between adult and pediatric patients. Key recommendations include prioritizing the tumor target volume while avoiding excessive constraints on other organs. Dose constraints and gradients are discussed for specific organs like the vertebrae, where growth is ongoing. The goals of the PENTEC group are outlined as developing evidence-based dose guidelines to improve survivor outcomes and propose standardized dose-volume reporting.
Radiotherapy in ca esophagus
1) The document discusses various radiation techniques for treating cancer of the esophagus including 2D, 3D conformal radiation therapy, IMRT, and IGRT.
2) It covers topics like target volume delineation, field design considerations for different esophageal subsites, and evolution from 2D to 3D treatment planning.
3) While there is no consensus, most contemporary trials use margins of 3-5cm cranially and caudally on the gross tumor with approximately a 2cm radial margin.
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Abstract: The Multimedia for Medicine Medico Task, running for the first time as part of MediaEval 2017, focuses on detecting abnormalities, diseases and anatomical landmarks in images captured by medical devices in the gastrointestinal tract. The task characteristics are described, including the use case and its challenges, the dataset with ground truth, the required participant runs and the evaluation metrics.
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Design of Modified Bio-Inspired Algorithm for Identification and Segmentation...
Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body
1 Hassan
The document summarizes findings from a study on the appropriateness of upper endoscopy referrals in Italy. Key findings include:
1) 22% of over 13,000 endoscopies were deemed inappropriate based on guidelines. Relevant findings were found in 51% of appropriate referrals and 32% of inappropriate ones.
2) Common relevant findings included esophagitis, gastric erosions, esophageal varices, and ulcers. New cancers were found in 1.6% of patients.
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iHT2 Health IT Summit San Francisco 2013 - Christopher Longhurst, MD, CMIO, L...
iHT2 Health IT Summit San Francisco 2013 - Christopher Longhurst, MD, CMIO, L...Health IT Conference – iHT2
Christopher A. Longhurst, MD, MS
Chief Medical Information Officer
Lucile Packard Children’s Hospital
Clinical Associate Professor of Pediatrics
Stanford School of Medicine
Case Study "Using Big Data to Shift from Evidence-based Practice to Practice-based Evidence"
Packard Children's Hospital at Stanford has been on a journey towards a comprehensive electronic medical record (EMR) since 2004. These efforts resulted in national attention in 2010 with the publication of the first-ever correlation between implementation of computerized physician order entry (CPOE) and a decrease in hospital-wide mortality. This landmark was followed in 2011 with a paper in the NEJM describing the first documented use of aggregate EMR data to make a real-time patient care decision. In this talk, Dr. Chris Longhurst will share the "story behind the story" of these accomplishments and highlight opportunities for using applied clinical informatics to improve the value of healthcare we deliver to our patients.Challenges and opportunities for machine learning in biomedical research
1. Machine learning faces challenges in biomedical research due to data heterogeneity, lack of labeled data, and complexity in biological patterns and networks.
2. Combining machine learning and biological network models can help address these challenges by encoding data in biologically meaningful networks and extracting network-based features for prediction.
3. Examples applying this approach to cancer datasets showed that models based on network centrality features outperformed other methods, and deep learning using these features achieved the best prediction performance across multiple neuroblastoma datasets.
Michael DeBrota et al. - Assessment of Computational Histopathology in Thorac...
Background and Hypothesis:
Thoracic aortic aneurysm (TAA) histopathology includes elastic fiber (EF) abnormalities, mucoid extracellular matrix (MECM) accumulation, and smooth muscle derangement in the aortic medial layer. While semi-quantitative grading of these characteristics is a standard practice, computational characterization of medial layer components may facilitate novel quantitative analyses at higher throughput. We hypothesized that computational results would correlate with results of semi-quantitative grading of aortic histopathology.
Experimental Design:
Formalin-fixed, paraffin-embedded human aortic tissue sections were stained with Movat’s pentachrome to characterize aortic microstructure. Sections were also immunostained for nitrotyrosine residues to assess oxidative stress. Samples were initially graded semi-quantitatively by two independent blinded readers. Next, computational histopathology software was used a) to quantify the proportions of EF, MECM, and cellular area in the medial layer of pentachrome-stained sections and b) to quantify the distribution and intensity of positive nitrotyrosine staining in immunostained sections. Association between semi-quantitative grading and computed values was tested with ANOVA.
Results:
The cohort included 74 participants who underwent prophylactic aortic replacement for TAA and 23 healthy controls. The mean age was 54±17 years. On average, EFs accounted for 49% (range 6-90%) of medial tissue area, whereas MECM accounted for 25% (1-73%). The overall semi-quantitative grade of medial degeneration severity was associated with decrease in EF fraction (p=0.02). The grade of EF thinning also strongly correlated with decrease in EF fraction (p=1x10-6). Meanwhile, grade for accumulation of MECM was associated with increase in MECM (p=0.004). Increased semi-quantitative grading for nitrotyrosine levels was associated with increased nuclear signal optical density (p=9x10-10) and greater percentage of cells labeled as strongly positive (p=8x10-10).
Conclusion and Potential Impact:
We observed significant correlations between computed quantitative values and semi-quantitative grading. This suggests that computational histopathology is a valid method for investigation of human TAA tissues.
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Topics discussed in this webinar include:
The need for preclinical imaging
Technical overview: Optical, High Frequency Ultrasound, MRI, PET/CT, and Fluorescence in vivo Endomicroscopy
When each modality should be used
Different types of preclinical imaging applications
Multiplex imaging20180522 - universal health coverage from quantity to quality
Taiwan has achieved universal health coverage with a service coverage index of 85, on par with other high coverage countries like Canada, South Korea, and Japan. Key health indicators for Taiwan include a 97.7% antenatal care coverage rate, 70% tuberculosis treatment effectiveness, and 97.8% coverage for childhood immunizations. Taiwan also has strong programs for non-communicable diseases like diabetes, with quality targets met by over 90% of patients and extensive primary and secondary prevention programs for cancer.
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To present our experience of intensity-modulated radiotherapy (IMRT) with simultaneous modulated accelerated radiotherapy (SMART) boost technique in patients with nasopharyngeal carcinoma (NPC).Similar to Presentation clinical applications of Artificial Intelligence for radiation oncology (20)
Echo Directed Therapy Saves Lives in ICU - Vieillard-Baron
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Presentation clinical applications of Artificial Intelligence for radiation oncology
- 1. Clinical applications of AI for Radiation Oncology Jean-Emmanuel Bibault, MD, PhD Service d’oncologie radiothérapie - HEGP INSERM UMRS 872, Equipe 22: Information Sciences to support Personalized Medicine
- 2. Note Please note that the slides of this presentation can be shared on social media.
- 4. A few milestones Source: Andrew Beam
- 5. The explosion of medical data
- 7. Many different methods within « AI »
- 10. A FEW EXAMPLES
- 11. TEXT DATA Electronic Health Records
- 12. • 76214 patients • Prediction of 78 diseases Miotto et al, Scientific Reports, 2016
- 13. Miotto et al, Scientific Reports, 2016
- 14. 2 million adult and pediatric patients cared for at either the Stanford Hospital or the Lucile Packard Children’s hospital between 1995 and 2014 Prediction of death (3-12 months)
- 17. CheXnet • Deep Neural Network (121 layers) • Trained on 100 000 Chest X- Rays • 14 anomalies • Saliency map Rajpurkar P et al, arXiv, Dec 2017
- 18. Results Rajpurkar P et al, arXiv, Dec 2017
- 20. Results Accuracy (IC 95%) Sensibility (IC 95%) Specificity (IC 95%) AUC (IC 95%) Logistic Regression 69,5% (59,2% - 78,51%) 34,78% (16,38% - 57.27%) 80,56% (69.53% - 88.94%) 0,59 (0,458 – 0,686) Support Vector Machine 71,58% (61,4%-80,36%) 45,45% (24,39%-67,79%) 79,45% (68,38% - 88,02%) 0,62 (0.51 – 0.74) Deep Learning 80% (70,54% - 87,51%) 68,2% (45,13% - 86,14%) 83,56% (73,05% - 91,21%) 0,72 (0.65 - 0.87) Lambregts DMJ et al. 2011. « Diffusion-Weighted MRI for Selection of Complete Responders After Chemoradiation for Locally Advanced Rectal Cancer: A Multicenter Study » Annals of Surgical Oncology MRI 0-40% (0-53%) 92-98% (88-99%) 0,58-0,76 (0,47-0,86) MRI + DWI 52-64% (85-99%) 89-97% (85-99%) 0,78-0,8 (0,69-0,91) HUMAN PERFORMANCE?
- 21. Predict survival from CT scans
- 23. PATHOLOGY
- 24. 270 patients External validation on 129 other patients
- 25. AUC : 0.556 - 0.994
- 27. Automatic segmentation S. Nikolov et al, ArXiv, 2018
- 29. • CNN • 450 CT scans
- 31. Automatic treatment planning Mahmood et al, ArXiv, 2018
- 32. BUT WE NEED TO REMAIN VERY CAREFUL…
- 35. jean-emmanuel.bibault@aphp.fr twitter.com/jebibault import tensorflow as tf THANK YOU!