The document summarizes a study examining the predictive value of diffusion-weighted MRI for predicting response to neoadjuvant chemotherapy in breast cancer patients enrolled in the I-SPY 2 TRIAL. Apparent diffusion coefficient (ADC) values were measured from DW-MRI scans of 415 patients at various time points. Single predictor analysis found that percent change in ADC from baseline best predicted pathologic complete response, especially at later time points. A logistic regression model combining ADC, functional tumor volume from DCE-MRI, and clinical subtype achieved an AUC of 0.80 for predicting response at the pre-surgery time point, demonstrating the additive predictive value of DW-MRI.
The influence of surgical margins on local control after breast conserving su...Danijela Scepanovic
This document summarizes a study examining the influence of surgical margins on local control after breast-conserving surgery and postoperative radiotherapy. The study included 449 patients with early stage breast cancer who underwent lumpectomy followed by whole breast irradiation, with some also receiving a tumor bed boost. Negative surgical margins (greater than 5mm) were associated with significantly lower risk of local recurrence compared to positive margins (5mm or less). While boost did not provide a significant benefit for patients with positive margins, negative lymph-angioinvasion was found to significantly lower the risk of local recurrence. Several other factors like age, menopausal status, tumor size and type did not significantly influence local control.
1) IGRT in head and neck cancer aims to correct setup uncertainties using 2D or CT imaging and correct changes in tumors and organs during therapy using CT.
2) Studies show imaging every day can minimize setup deviations if using small PTV margins, and imaging frequency is more important than modality.
3) Rotational errors can be corrected by repositioning, replanning on new position, or using a rotating couch.
1. IMRT allows delivering different dose levels to multiple tumor targets simultaneously.
2. Advanced MRI techniques like DCE and T2 mapping can help better identify diseased sites and define boost targets for IMRT planning.
3. The presenter is working to incorporate MRI data like functional MRI into the radiotherapy planning process to help optimize dose distribution and improve patient outcomes.
Quantitative Image Analysis for Cancer Diagnosis and Radiation TherapyWookjin Choi
1.Lung Cancer Screening
1.1.Deep learning (feasible but not interpretable)
1.2.Radiomics (concise model)
1.3.Spiculation quantification (interpretable feature)
2.PET/CT Tumor Response
2.1.Aggressive Lung ADC subtype prediction (helpful for surgeons)
2.2.Pathologic response prediction (accurate but not concise)
2.3.Local tumor morphological changes (accurate and interpretable)
Imrt A New Treatment Method For Nasopharyngeal Cancerfondas vakalis
IMRT is a new treatment method for nasopharyngeal cancer that has the potential to improve local control, especially for T3 and T4 tumors, reduce post-irradiation complications, and reduce the rate of distant metastasis. A study of 13 NPC patients treated with IMRT found that it resulted in reduced acute reactions and improved dosimetry compared to conventional radiotherapy. Further research is needed to optimize target definition and dose distribution in IMRT for NPC.
Breast MRI for early prediction of residual disease following neoadjuvant che...Wen Li
This study evaluated the use of breast MRI to predict response to neoadjuvant chemotherapy for locally advanced breast cancer. The researchers optimized MRI parameters and cut-points for different breast cancer subtypes (HR+/HER2-, HER2+, triple negative) to maximize sensitivity while maintaining high specificity. They found maximum sensitivities as early as after one chemotherapy cycle for triple negative cancer and between chemotherapy regimens for HR+/HER2- and HER2+ cancers when specificity was over 90%. Optimizing MRI parameters and cut-points improved prediction of response compared to default settings. Future work will validate these optimized models in a larger patient cohort.
Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...breastcancerupdatecongress
This document discusses the use of breast MRI in evaluating response to neoadjuvant chemotherapy. MRI can provide both morphological and functional information about tumors. Studies show DCE-MRI and DWI-MRI may help assess response after 1-2 cycles of chemotherapy, with changes in tumor size, kinetic parameters and ADC values predicting pathological complete or near-complete response. Larger prospective trials are still needed to standardize MRI methods and thresholds to determine if changes on MRI could guide modifications to chemotherapy regimens for non-responders. Overall, MRI shows potential as a predictive marker and non-invasive method for monitoring early response to neoadjuvant breast cancer treatment.
The influence of surgical margins on local control after breast conserving su...Danijela Scepanovic
This document summarizes a study examining the influence of surgical margins on local control after breast-conserving surgery and postoperative radiotherapy. The study included 449 patients with early stage breast cancer who underwent lumpectomy followed by whole breast irradiation, with some also receiving a tumor bed boost. Negative surgical margins (greater than 5mm) were associated with significantly lower risk of local recurrence compared to positive margins (5mm or less). While boost did not provide a significant benefit for patients with positive margins, negative lymph-angioinvasion was found to significantly lower the risk of local recurrence. Several other factors like age, menopausal status, tumor size and type did not significantly influence local control.
1) IGRT in head and neck cancer aims to correct setup uncertainties using 2D or CT imaging and correct changes in tumors and organs during therapy using CT.
2) Studies show imaging every day can minimize setup deviations if using small PTV margins, and imaging frequency is more important than modality.
3) Rotational errors can be corrected by repositioning, replanning on new position, or using a rotating couch.
1. IMRT allows delivering different dose levels to multiple tumor targets simultaneously.
2. Advanced MRI techniques like DCE and T2 mapping can help better identify diseased sites and define boost targets for IMRT planning.
3. The presenter is working to incorporate MRI data like functional MRI into the radiotherapy planning process to help optimize dose distribution and improve patient outcomes.
Quantitative Image Analysis for Cancer Diagnosis and Radiation TherapyWookjin Choi
1.Lung Cancer Screening
1.1.Deep learning (feasible but not interpretable)
1.2.Radiomics (concise model)
1.3.Spiculation quantification (interpretable feature)
2.PET/CT Tumor Response
2.1.Aggressive Lung ADC subtype prediction (helpful for surgeons)
2.2.Pathologic response prediction (accurate but not concise)
2.3.Local tumor morphological changes (accurate and interpretable)
Imrt A New Treatment Method For Nasopharyngeal Cancerfondas vakalis
IMRT is a new treatment method for nasopharyngeal cancer that has the potential to improve local control, especially for T3 and T4 tumors, reduce post-irradiation complications, and reduce the rate of distant metastasis. A study of 13 NPC patients treated with IMRT found that it resulted in reduced acute reactions and improved dosimetry compared to conventional radiotherapy. Further research is needed to optimize target definition and dose distribution in IMRT for NPC.
Breast MRI for early prediction of residual disease following neoadjuvant che...Wen Li
This study evaluated the use of breast MRI to predict response to neoadjuvant chemotherapy for locally advanced breast cancer. The researchers optimized MRI parameters and cut-points for different breast cancer subtypes (HR+/HER2-, HER2+, triple negative) to maximize sensitivity while maintaining high specificity. They found maximum sensitivities as early as after one chemotherapy cycle for triple negative cancer and between chemotherapy regimens for HR+/HER2- and HER2+ cancers when specificity was over 90%. Optimizing MRI parameters and cut-points improved prediction of response compared to default settings. Future work will validate these optimized models in a larger patient cohort.
Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...breastcancerupdatecongress
This document discusses the use of breast MRI in evaluating response to neoadjuvant chemotherapy. MRI can provide both morphological and functional information about tumors. Studies show DCE-MRI and DWI-MRI may help assess response after 1-2 cycles of chemotherapy, with changes in tumor size, kinetic parameters and ADC values predicting pathological complete or near-complete response. Larger prospective trials are still needed to standardize MRI methods and thresholds to determine if changes on MRI could guide modifications to chemotherapy regimens for non-responders. Overall, MRI shows potential as a predictive marker and non-invasive method for monitoring early response to neoadjuvant breast cancer treatment.
24° CORSO RESIDENZIALE DI AGGIORNAMENTO
con il patrocinio dell’Associazione Italiana di Radioterapia Oncologica (AIRO)
Moderna Radioterapia, Nuove Tecnologie e Ipofrazionamento della Dose
Trattamenti ipofrazionati ed ipofrazionati-accelerati: effetti sul controllo tumorale e sulla tossicità (inclusa consequential late-toxicity)
This document summarizes new advances in quantitative multiparametric breast MRI. It discusses using diffusion, perfusion, and radiomics parameters to characterize breast lesions and predict response to neoadjuvant chemotherapy. Diffusion metrics like ADC, perfusion metrics like Ktrans and Ve, and radiomics features can differentiate benign from malignant lesions, predict molecular subtypes, and determine response to therapy with moderate accuracy. Baseline radiomics features achieved an AUC of 0.91 for predicting response to neoadjuvant chemotherapy in one study. Quantitative MRI is providing new insights into breast cancer characterization and treatment monitoring.
This document provides an overview of neoadjuvant and adjuvant therapy strategies for patients with resectable pancreatic cancer. It summarizes results from several key clinical trials evaluating different chemotherapy regimens in the neoadjuvant and adjuvant settings. It also discusses ongoing trials investigating newer treatment approaches for resectable and borderline resectable disease.
adjuvant Abemaciclib in High risk HR+ EBCssuserc11ccf
Here are my responses to the questions:
1. Factors I would consider in defining high risk early breast cancer include node status, tumor size, tumor grade, Ki67 level, menopausal status, and response to neoadjuvant chemotherapy.
2. For this 65-year-old postmenopausal patient, I would consider adjuvant endocrine therapy with an aromatase inhibitor plus abemaciclib (AI + Abemaciclib).
3. For this 45-year-old premenopausal patient, I would consider adjuvant endocrine therapy with an LHRHa plus aromatase inhibitor or tamoxifen plus abemaciclib (LHRHa + AI/Tamoxifen + Abem
IRJET-A Novel Approach for MRI Brain Image Classification and DetectionIRJET Journal
This document proposes a new approach for classifying and detecting brain tumors in MRI images. The method uses discrete wavelet transform for feature extraction, support vector machine for classification, and incremental supervised neural network and invariant moments for tumor detection. MRI brain images are first classified as normal or tumorous. For images detected as tumorous, the method then segments the image and uses moments to determine the symmetry axis and detect any asymmetry which would indicate the location of the tumor. The approach is evaluated on a dataset of 60 MRI images, achieving 98.33% classification accuracy in distinguishing normal and tumorous images.
Artificial Intelligence To Reduce Radiation-induced Cardiotoxicity In Lung Ca...Wookjin Choi
Traditionally, radiation-induced cardiotoxicity has been studied using cardiac radiation doses rather than functional imaging. We developed artificial intelligence (AI) models based on novel cardiac delta radiomics using pre- and post-treatment FDG-PET/CT scans to predict overall survival in lung cancer patients undergoing radiotherapy. We identified four clinically relevant delta radiomics features with the AI prediction models. The best model achieved an AUC of 0.91 on the training set and 0.87 on the test set. We are a pioneering group in AI for functional cardiac imaging. If validated, this approach will enable to use standard PET/CT scans as functional cardiac imaging with good predictive AUC for OS, as well as provide automated methods to provide functional cardiac information for clinical outcome prediction AI in lung cancer patients.
Quantitative image analysis for cancer diagnosis and radiation therapyWookjin Choi
1.Lung Cancer Screening
1.1.Deep learning (feasible but not interpretable)
1.2.Radiomics (concise model)
1.3.Spiculation quantification (interpretable feature)
2.PET/CT Tumor Response
2.1.Aggressive Lung ADC subtype prediction (helpful for surgeons)
2.2.Pathologic response prediction (accurate but not concise)
2.3.Local tumor morphological changes (accurate and interpretable)
Improving Patient Radiation Protection or Evaluating Risks in Medical Imaging...Eduardo Medina Gironzini
This document discusses key concepts in radiation dosimetry for medical imaging, including:
1) It defines common radiation protection terms like absorbed dose, equivalent dose, effective dose and explains their appropriate and limited uses for evaluating patient risk from medical imaging.
2) It notes that effective dose should not be used to assess risk to individuals from medical exposures and that organ doses are more relevant.
3) It discusses how uncertainty increases at each step moving from measurement of organ doses to estimation of effective dose and risk, limiting the usefulness of effective dose for medical applications.
4) For medical imaging, more detailed knowledge of organ doses, dose distributions and patient factors is needed than just effective dose alone to properly assess radiation
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.
ROLE OF DARATUMUMAB IN NEWLY DIAGNOSED MULTIPLE MYELOMA.pptxSeraj Aldeen
1. The document discusses three phase 3 trials (CASSIOPEIA, MAIA, and ALCYON) that evaluated the role of daratumumab in frontline treatment of multiple myeloma.
2. The MAIA trial showed that in transplant-ineligible newly diagnosed multiple myeloma patients, daratumumab with lenalidomide and dexamethasone (D-Rd) resulted in significantly longer progression-free survival compared to lenalidomide and dexamethasone (Rd) alone, with median PFS not reached for D-Rd versus 34.4 months for Rd.
3. D-Rd also resulted in higher overall response and complete response rates compared to Rd.
2 dimensional versus 3 dimensional (conformal)nesta2000
3D conformal radiation therapy provides more accurate targeting of breast tissue and reduces radiation exposure to surrounding organs like the heart and lungs compared to traditional 2D radiation therapy. A study of 60 breast cancer patients receiving post-mastectomy radiation found 3D therapy significantly lowered the radiation dose and estimated toxicity risk to the left lung and heart. Additionally, 3D therapy better covered the internal mammary lymph nodes target volume while maintaining similar coverage of other areas. Clinical results also showed less reduction in cardiac function for patients receiving 3D radiation therapy. The study concluded 3D conformal therapy should be offered to patients needing internal mammary node irradiation for improved target coverage and organ sparing.
- A pathologist discusses factors that can help predict prostate cancer pathologic stage before surgery, including PSA levels, Gleason score on biopsy, percentage of biopsy cores involved with cancer, and clinical stage. Nomograms using these factors can estimate likelihood of organ-confined disease or extracapsular extension.
- Repeat biopsy may help identify patients initially classified as low risk who actually have higher risk disease. Those with upgraded disease on repeat biopsy tended to have higher grade and stage cancers identified during prostatectomy.
- Transition zone cancers may be missed on standard biopsy but detected with targeted biopsies of this area. Identifying these tumors preoperatively is important for predicting pathologic features.
There are many guidelines and recommendations suggesting ablation/therapy in Differentiated Thyroid Carcinoma. This presentation will be focused on the details of these recommendations and guidelines.
Furthermore, it will be discussed the use of recombinant human thyrotropin (rhTSH) prior to radioactive iodine remnant ablation for patients with differentiated thyroid cancer.
BIOSTATISTICS MEAN MEDIAN MODE SEMESTER 8 AND M PHARMACY BIOSTATISTICS.pptxPayaamvohra1
1. The document provides information about biostatistics including measures of central tendency, dispersion, correlation, and regression. It defines terms like mean, median, mode, range, and standard deviation.
2. Examples of calculating mean, median, and mode from individual data sets, grouped frequency distributions, and continuous series are shown step-by-step.
3. Parametric tests like t-test, ANOVA, and tests of significance are also introduced. Overall, the document covers fundamental concepts in biostatistics through examples.
This document summarizes a research paper on computed tomography (CT) dose reduction and view number optimization. It discusses how CT uses X-rays to create images but that radiation exposure is a concern, especially for pediatric patients. The paper explores how iterative reconstruction techniques and compressed sensing theories have aimed to reduce views and dose while maintaining image quality. It presents the goal of investigating the relationship between image quality, view number, and radiation dose level. Numerical tests were performed to determine the optimal view number for a given dose level that achieves the best reconstruction quality.
This document provides definitions and examples of random and systematic errors that can occur during the radiotherapy treatment process. It discusses various sources of errors including patient setup, organ motion, and target deformation. Methods for managing errors such as offline and online correction techniques, immobilization devices, and image-guidance are presented. The importance of distinguishing between random and systematic errors when establishing appropriate planning target volume margins is also emphasized.
This presentation by Juraj Čorba, Chair of OECD Working Party on Artificial Intelligence Governance (AIGO), was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Professor Alex Robson, Deputy Chair of Australia’s Productivity Commission, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
This presentation was uploaded with the author’s consent.
24° CORSO RESIDENZIALE DI AGGIORNAMENTO
con il patrocinio dell’Associazione Italiana di Radioterapia Oncologica (AIRO)
Moderna Radioterapia, Nuove Tecnologie e Ipofrazionamento della Dose
Trattamenti ipofrazionati ed ipofrazionati-accelerati: effetti sul controllo tumorale e sulla tossicità (inclusa consequential late-toxicity)
This document summarizes new advances in quantitative multiparametric breast MRI. It discusses using diffusion, perfusion, and radiomics parameters to characterize breast lesions and predict response to neoadjuvant chemotherapy. Diffusion metrics like ADC, perfusion metrics like Ktrans and Ve, and radiomics features can differentiate benign from malignant lesions, predict molecular subtypes, and determine response to therapy with moderate accuracy. Baseline radiomics features achieved an AUC of 0.91 for predicting response to neoadjuvant chemotherapy in one study. Quantitative MRI is providing new insights into breast cancer characterization and treatment monitoring.
This document provides an overview of neoadjuvant and adjuvant therapy strategies for patients with resectable pancreatic cancer. It summarizes results from several key clinical trials evaluating different chemotherapy regimens in the neoadjuvant and adjuvant settings. It also discusses ongoing trials investigating newer treatment approaches for resectable and borderline resectable disease.
adjuvant Abemaciclib in High risk HR+ EBCssuserc11ccf
Here are my responses to the questions:
1. Factors I would consider in defining high risk early breast cancer include node status, tumor size, tumor grade, Ki67 level, menopausal status, and response to neoadjuvant chemotherapy.
2. For this 65-year-old postmenopausal patient, I would consider adjuvant endocrine therapy with an aromatase inhibitor plus abemaciclib (AI + Abemaciclib).
3. For this 45-year-old premenopausal patient, I would consider adjuvant endocrine therapy with an LHRHa plus aromatase inhibitor or tamoxifen plus abemaciclib (LHRHa + AI/Tamoxifen + Abem
IRJET-A Novel Approach for MRI Brain Image Classification and DetectionIRJET Journal
This document proposes a new approach for classifying and detecting brain tumors in MRI images. The method uses discrete wavelet transform for feature extraction, support vector machine for classification, and incremental supervised neural network and invariant moments for tumor detection. MRI brain images are first classified as normal or tumorous. For images detected as tumorous, the method then segments the image and uses moments to determine the symmetry axis and detect any asymmetry which would indicate the location of the tumor. The approach is evaluated on a dataset of 60 MRI images, achieving 98.33% classification accuracy in distinguishing normal and tumorous images.
Artificial Intelligence To Reduce Radiation-induced Cardiotoxicity In Lung Ca...Wookjin Choi
Traditionally, radiation-induced cardiotoxicity has been studied using cardiac radiation doses rather than functional imaging. We developed artificial intelligence (AI) models based on novel cardiac delta radiomics using pre- and post-treatment FDG-PET/CT scans to predict overall survival in lung cancer patients undergoing radiotherapy. We identified four clinically relevant delta radiomics features with the AI prediction models. The best model achieved an AUC of 0.91 on the training set and 0.87 on the test set. We are a pioneering group in AI for functional cardiac imaging. If validated, this approach will enable to use standard PET/CT scans as functional cardiac imaging with good predictive AUC for OS, as well as provide automated methods to provide functional cardiac information for clinical outcome prediction AI in lung cancer patients.
Quantitative image analysis for cancer diagnosis and radiation therapyWookjin Choi
1.Lung Cancer Screening
1.1.Deep learning (feasible but not interpretable)
1.2.Radiomics (concise model)
1.3.Spiculation quantification (interpretable feature)
2.PET/CT Tumor Response
2.1.Aggressive Lung ADC subtype prediction (helpful for surgeons)
2.2.Pathologic response prediction (accurate but not concise)
2.3.Local tumor morphological changes (accurate and interpretable)
Improving Patient Radiation Protection or Evaluating Risks in Medical Imaging...Eduardo Medina Gironzini
This document discusses key concepts in radiation dosimetry for medical imaging, including:
1) It defines common radiation protection terms like absorbed dose, equivalent dose, effective dose and explains their appropriate and limited uses for evaluating patient risk from medical imaging.
2) It notes that effective dose should not be used to assess risk to individuals from medical exposures and that organ doses are more relevant.
3) It discusses how uncertainty increases at each step moving from measurement of organ doses to estimation of effective dose and risk, limiting the usefulness of effective dose for medical applications.
4) For medical imaging, more detailed knowledge of organ doses, dose distributions and patient factors is needed than just effective dose alone to properly assess radiation
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.
ROLE OF DARATUMUMAB IN NEWLY DIAGNOSED MULTIPLE MYELOMA.pptxSeraj Aldeen
1. The document discusses three phase 3 trials (CASSIOPEIA, MAIA, and ALCYON) that evaluated the role of daratumumab in frontline treatment of multiple myeloma.
2. The MAIA trial showed that in transplant-ineligible newly diagnosed multiple myeloma patients, daratumumab with lenalidomide and dexamethasone (D-Rd) resulted in significantly longer progression-free survival compared to lenalidomide and dexamethasone (Rd) alone, with median PFS not reached for D-Rd versus 34.4 months for Rd.
3. D-Rd also resulted in higher overall response and complete response rates compared to Rd.
2 dimensional versus 3 dimensional (conformal)nesta2000
3D conformal radiation therapy provides more accurate targeting of breast tissue and reduces radiation exposure to surrounding organs like the heart and lungs compared to traditional 2D radiation therapy. A study of 60 breast cancer patients receiving post-mastectomy radiation found 3D therapy significantly lowered the radiation dose and estimated toxicity risk to the left lung and heart. Additionally, 3D therapy better covered the internal mammary lymph nodes target volume while maintaining similar coverage of other areas. Clinical results also showed less reduction in cardiac function for patients receiving 3D radiation therapy. The study concluded 3D conformal therapy should be offered to patients needing internal mammary node irradiation for improved target coverage and organ sparing.
- A pathologist discusses factors that can help predict prostate cancer pathologic stage before surgery, including PSA levels, Gleason score on biopsy, percentage of biopsy cores involved with cancer, and clinical stage. Nomograms using these factors can estimate likelihood of organ-confined disease or extracapsular extension.
- Repeat biopsy may help identify patients initially classified as low risk who actually have higher risk disease. Those with upgraded disease on repeat biopsy tended to have higher grade and stage cancers identified during prostatectomy.
- Transition zone cancers may be missed on standard biopsy but detected with targeted biopsies of this area. Identifying these tumors preoperatively is important for predicting pathologic features.
There are many guidelines and recommendations suggesting ablation/therapy in Differentiated Thyroid Carcinoma. This presentation will be focused on the details of these recommendations and guidelines.
Furthermore, it will be discussed the use of recombinant human thyrotropin (rhTSH) prior to radioactive iodine remnant ablation for patients with differentiated thyroid cancer.
BIOSTATISTICS MEAN MEDIAN MODE SEMESTER 8 AND M PHARMACY BIOSTATISTICS.pptxPayaamvohra1
1. The document provides information about biostatistics including measures of central tendency, dispersion, correlation, and regression. It defines terms like mean, median, mode, range, and standard deviation.
2. Examples of calculating mean, median, and mode from individual data sets, grouped frequency distributions, and continuous series are shown step-by-step.
3. Parametric tests like t-test, ANOVA, and tests of significance are also introduced. Overall, the document covers fundamental concepts in biostatistics through examples.
This document summarizes a research paper on computed tomography (CT) dose reduction and view number optimization. It discusses how CT uses X-rays to create images but that radiation exposure is a concern, especially for pediatric patients. The paper explores how iterative reconstruction techniques and compressed sensing theories have aimed to reduce views and dose while maintaining image quality. It presents the goal of investigating the relationship between image quality, view number, and radiation dose level. Numerical tests were performed to determine the optimal view number for a given dose level that achieves the best reconstruction quality.
This document provides definitions and examples of random and systematic errors that can occur during the radiotherapy treatment process. It discusses various sources of errors including patient setup, organ motion, and target deformation. Methods for managing errors such as offline and online correction techniques, immobilization devices, and image-guidance are presented. The importance of distinguishing between random and systematic errors when establishing appropriate planning target volume margins is also emphasized.
This presentation by Juraj Čorba, Chair of OECD Working Party on Artificial Intelligence Governance (AIGO), was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Professor Alex Robson, Deputy Chair of Australia’s Productivity Commission, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
This presentation was uploaded with the author’s consent.
Carrer goals.pptx and their importance in real lifeartemacademy2
Career goals serve as a roadmap for individuals, guiding them toward achieving long-term professional aspirations and personal fulfillment. Establishing clear career goals enables professionals to focus their efforts on developing specific skills, gaining relevant experience, and making strategic decisions that align with their desired career trajectory. By setting both short-term and long-term objectives, individuals can systematically track their progress, make necessary adjustments, and stay motivated. Short-term goals often include acquiring new qualifications, mastering particular competencies, or securing a specific role, while long-term goals might encompass reaching executive positions, becoming industry experts, or launching entrepreneurial ventures.
Moreover, having well-defined career goals fosters a sense of purpose and direction, enhancing job satisfaction and overall productivity. It encourages continuous learning and adaptation, as professionals remain attuned to industry trends and evolving job market demands. Career goals also facilitate better time management and resource allocation, as individuals prioritize tasks and opportunities that advance their professional growth. In addition, articulating career goals can aid in networking and mentorship, as it allows individuals to communicate their aspirations clearly to potential mentors, colleagues, and employers, thereby opening doors to valuable guidance and support. Ultimately, career goals are integral to personal and professional development, driving individuals toward sustained success and fulfillment in their chosen fields.
This presentation by Thibault Schrepel, Associate Professor of Law at Vrije Universiteit Amsterdam University, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
Why Psychological Safety Matters for Software Teams - ACE 2024 - Ben Linders.pdfBen Linders
Psychological safety in teams is important; team members must feel safe and able to communicate and collaborate effectively to deliver value. It’s also necessary to build long-lasting teams since things will happen and relationships will be strained.
But, how safe is a team? How can we determine if there are any factors that make the team unsafe or have an impact on the team’s culture?
In this mini-workshop, we’ll play games for psychological safety and team culture utilizing a deck of coaching cards, The Psychological Safety Cards. We will learn how to use gamification to gain a better understanding of what’s going on in teams. Individuals share what they have learned from working in teams, what has impacted the team’s safety and culture, and what has led to positive change.
Different game formats will be played in groups in parallel. Examples are an ice-breaker to get people talking about psychological safety, a constellation where people take positions about aspects of psychological safety in their team or organization, and collaborative card games where people work together to create an environment that fosters psychological safety.
This presentation by Yong Lim, Professor of Economic Law at Seoul National University School of Law, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
XP 2024 presentation: A New Look to Leadershipsamililja
Presentation slides from XP2024 conference, Bolzano IT. The slides describe a new view to leadership and combines it with anthro-complexity (aka cynefin).
This presentation by OECD, OECD Secretariat, was made during the discussion “Pro-competitive Industrial Policy” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/pcip.
This presentation was uploaded with the author’s consent.
This presentation by Nathaniel Lane, Associate Professor in Economics at Oxford University, was made during the discussion “Pro-competitive Industrial Policy” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/pcip.
This presentation was uploaded with the author’s consent.
Suzanne Lagerweij - Influence Without Power - Why Empathy is Your Best Friend...Suzanne Lagerweij
This is a workshop about communication and collaboration. We will experience how we can analyze the reasons for resistance to change (exercise 1) and practice how to improve our conversation style and be more in control and effective in the way we communicate (exercise 2).
This session will use Dave Gray’s Empathy Mapping, Argyris’ Ladder of Inference and The Four Rs from Agile Conversations (Squirrel and Fredrick).
Abstract:
Let’s talk about powerful conversations! We all know how to lead a constructive conversation, right? Then why is it so difficult to have those conversations with people at work, especially those in powerful positions that show resistance to change?
Learning to control and direct conversations takes understanding and practice.
We can combine our innate empathy with our analytical skills to gain a deeper understanding of complex situations at work. Join this session to learn how to prepare for difficult conversations and how to improve our agile conversations in order to be more influential without power. We will use Dave Gray’s Empathy Mapping, Argyris’ Ladder of Inference and The Four Rs from Agile Conversations (Squirrel and Fredrick).
In the session you will experience how preparing and reflecting on your conversation can help you be more influential at work. You will learn how to communicate more effectively with the people needed to achieve positive change. You will leave with a self-revised version of a difficult conversation and a practical model to use when you get back to work.
Come learn more on how to become a real influencer!
This presentation by Professor Giuseppe Colangelo, Jean Monnet Professor of European Innovation Policy, was made during the discussion “The Intersection between Competition and Data Privacy” held at the 143rd meeting of the OECD Competition Committee on 13 June 2024. More papers and presentations on the topic can be found at oe.cd/ibcdp.
This presentation was uploaded with the author’s consent.
This presentation by OECD, OECD Secretariat, was made during the discussion “The Intersection between Competition and Data Privacy” held at the 143rd meeting of the OECD Competition Committee on 13 June 2024. More papers and presentations on the topic can be found at oe.cd/ibcdp.
This presentation was uploaded with the author’s consent.
This presentation by Katharine Kemp, Associate Professor at the Faculty of Law & Justice at UNSW Sydney, was made during the discussion “The Intersection between Competition and Data Privacy” held at the 143rd meeting of the OECD Competition Committee on 13 June 2024. More papers and presentations on the topic can be found at oe.cd/ibcdp.
This presentation was uploaded with the author’s consent.
This presentation by Tim Capel, Director of the UK Information Commissioner’s Office Legal Service, was made during the discussion “The Intersection between Competition and Data Privacy” held at the 143rd meeting of the OECD Competition Committee on 13 June 2024. More papers and presentations on the topic can be found at oe.cd/ibcdp.
This presentation was uploaded with the author’s consent.
This presentation by OECD, OECD Secretariat, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
Artificial Intelligence, Data and Competition – OECD – June 2024 OECD discussion
Ismrm2018 wen li
1. The role of diffusion-weighted MRI in the
prediction of response in I-SPY 2 TRIAL
9/29/2018
Wen Li, Lisa J Wilmes, David C Newitt, Ella F Jones, Savannah Partridge, John
Kornak, Jessica Gibbs, Bo La Yun, Matthew Tanaka, Laura J Esserman, Nola Hylton
ISMRM 2018
2. Lisa Wilmes:
I have no financial interests or relationships to disclose with regard to the
subject matter of this presentation.
Declaration of
Financial Interests or Relationships
3. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL3
Content
Background and Purpose
Methods
Results
Conclusions
Discussions
4. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL4
I-SPY 2 TRIAL
Investigation of Serial Studies to Predict Your Therapeutic Response through
Imaging and Molecular Analysis
A response-adaptive phase II trial testing
novel agents for breast cancer
I-SPY 2 opened in March 2010; 22 sites
(>1500 patients screened)
Drugs ”graduate” within subtypes defined by
hormone receptor (HR) status, HER2
status, and Mammaprint score
4 longitudinal MRIs are acquired during
treatment
The primary endpoint is pathologic complete
response (pCR) at surgery
I-SPY 2 schema
MRI1
(DCE & DWI)
MRI0
(DCE & DWI)
MRI2
(DCE & DWI)
MRI3
(DCE & DWI)
5. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL5
Quantitative breast MRI
Functional tumor volume (FTV) measured from
DCE-MRI was found to predict pathologic
complete response (pCR) and recurrence free
survival (RFS) in I-SPY 1
In I-SPY 2, FTV is used to adjust patient
randomization ratios and to evaluate drug efficacy
DW-MRI was included in I-SPY 2 to investigate the
predictive value of apparent diffusion coefficient
(ADC) by subtype
DCE DWI ADC
DCE FTV
6. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL6
Purpose
To investigate the additive predictive value of DW-MRI to
DCE-MRI by subtype for prediction of response in the I-SPY 2
TRIAL
7. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL7
Content
Background and Purpose
Methods
Results
Conclusions
Discussions
8. 8
DW-MRI acquisition
The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL
Good quality
b=800 ADC map
b=800 ADC map
Data acquired from 21 sites
- 1.5 and 3 T
- 3 scanner vendors
DW-MRI was acquired prior to DCE-MRI
SE-EPI sequence with fat suppression with
total scan time ≤ 5 min
Quality ranking: exclude, poor, good
Poor quality
9. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL9
ADC measurement
ADC maps were generated using
2 b-values (0 and 800)
Multi-slice ROI was manually
delineated on the ADC map for the
whole tumor
0.8
1.29
2.26 2.19
Mean tumor ADC (x10-3mm2/sec)
T0 T1 T2 T3
DW-MRI ADC map DCE-MRI
T0
Pre-treatment
T1
Early treatment
T2
Inter-regimen
T3
Pre-surgery
10. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL10
Imaging predictors
DCE & DWI DCE & DWI DCE & DWI DCE & DWI
11. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL11
Imaging predictors
FTV0, ADC0 FTV1, ADC1 FTV2, ADC2 FTV3, ADC3
DCE & DWI DCE & DWI DCE & DWI DCE & DWI
%∆FTV0_1, %∆ADC0_1
%∆FTV0_2, %∆ADC0_2
%∆FTV0_3, %∆ADC0_3
12. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL12
Imaging predictors
FTV0, ADC0 FTV1, ADC1 FTV2, ADC2 FTV3, ADC3
pCR is the primary
endpoint of I-SPY 2
DCE & DWI DCE & DWI DCE & DWI DCE & DWI
%∆FTV0_1, %∆ADC0_1
%∆FTV0_2, %∆ADC0_2
%∆FTV0_3, %∆ADC0_3
13. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL13
Statistical analysis
Binary outcome: pCR vs. non-pCR
Single predictor analysis
- Wilcoxon rank sum test: difference in MR metrics for
pCR vs. non-pCR
- Area under the ROC curve (AUC) for predicting pCR
Multiple predictor analysis
- Logistic regression model was evaluated
- AUC was calculated with 10-fold cross validation
14. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL14
Content
Background and Purpose
Methods
Results
Conclusions
Discussions
15. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL15
Patient characteristics
415 patients from 4 completed I-SPY 2 drug arms
354 patients with measurable ADC
36%
17%10%
37%
Subtype distribution
HR+/HER2-
HR+/HER2+
HR-/HER2+
HR-/HER2- 0%
20%
40%
60%
80%
100%
pCR rate by subtype
pCR non-pCR
16. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL16
Single predictor analysis
In general, ADC increases more in pCR than in non-pCR and the differences increase over treatment
In the full cohort, %∆ADC shows statistically significant prediction of pCR at all time points
%∆ADC appears to predict pCR at inter-regimen and pre-surgery in all subtypes, though HR+/HER2+ does
not reach statistical significance
-50
0
50
100
Full
H
R
+/H
E
R
2-
H
R
+/H
E
R
2+
H
R
-/H
E
R
2+H
R
-/H
E
R
2-
%DADC0_3
outcomes
non_pCR
pCR
*** ***
* p<0.05
**p<0.0001
Percent change (%∆) in ADC from baseline
Early treatment Inter-regimen Pre-surgery
-50
0
50
100
Full
H
R
+/H
E
R
2-
H
R
+/H
E
R
2+
H
R
-/H
E
R
2+H
R
-/H
E
R
2-
%DADC0_1
outcomes
non_pCR
pCR
**
-50
0
50
100
Full
H
R
+/H
E
R
2-
H
R
+/H
E
R
2+
H
R
-/H
E
R
2+H
R
-/H
E
R
2-
%DADC0_2
outcomes
non_pCR
pCR
** * * *
17. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL17
Multiple predictor model
Combining predictors with logistic regression model
+
FTV0
+
%∆FTV0_2
subtype
+
%∆ADC0_3
+
ADC0
pCR
1. Select individual predictors for inclusion using likelihood ratio test (p<0.05)
2. Include predictors that increase AUC
3. Fitted separate models using only predictors up to T0, T1, T2, T3, respectively
FTV0
+
subtype
+
ADC0
%∆FTV0_1
FTV0
+
subtype
+
+
%∆ADC0_1
%∆FTV0_2
+
FTV0
+
subtype
+
%∆ADC0_2
22. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL22
Conclusions
As single predictors, both FTV and ADC can predict pCR as
early as after 3 cycles of neoadjuvant chemotherapy (T1) in
the full cohort
Models combining FTV and ADC yielded the highest cross-
validated AUCs at inter-regimen and pre-surgery time points
in the full cohort
The association between percent change of FTV and ADC
and pCR varies among breast cancer subtypes
23. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL23
Content
Background
Methods
Results
Conclusions
Discussion
24. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL24
Discussion
I-SPY 2 is an on-going multi-center multi-treatment clinical trial
- Differences in system manufacturers and field strength
- DW-MRI image quality highly variable across clinical sites in I-SPY 2
- Patients from multiple treatment arms were combined
Analysis by subtype, the goal of the study, is continuing
- Sample size is limited in certain breast cancer subtype, such as HR-/HER2+
- 11 drugs have graduated and available for analysis
Improvements in breast DW-MRI acquisition and analysis may
lead to higher predictive performance
25. The role of diffusion-weighted MRI in the prediction of response in I-SPY 2 TRIAL25
Acknowledgements
Patients who participated in I-SPY 2
All members of I-SPY TRIAL Investigators Network
ACRIN Core Laboratory
Funding: U01 CA151235; R01 CA132870