Tim Holland‐Letz
A5050943602- Prostate Cancer Treatment and Research
- Radiopharmaceutical Chemistry and Applications
- Optimal Experimental Design Methods
- Prostate Cancer Diagnosis and Treatment
- Statistical Methods in Clinical Trials
- Cutaneous Melanoma Detection and Management
- AI in cancer detection
- Melanoma and MAPK Pathways
- Cancer Immunotherapy and Biomarkers
- Radiomics and Machine Learning in Medical Imaging
- Hematopoietic Stem Cell Transplantation
- RNA Interference and Gene Delivery
- Advanced Multi-Objective Optimization Algorithms
- Computational Drug Discovery Methods
- Colorectal Cancer Screening and Detection
- MicroRNA in disease regulation
- Immune Cell Function and Interaction
- Immune cells in cancer
- Neuroblastoma Research and Treatments
- DNA Repair Mechanisms
- Cancer Genomics and Diagnostics
- Sepsis Diagnosis and Treatment
- Glioma Diagnosis and Treatment
- Medical Imaging Techniques and Applications
- Cardiac Imaging and Diagnostics
German Cancer Research Center
2016-2025
Heidelberg University
2016-2025
DKFZ-ZMBH Alliance
2013-2022
Heidelberger Institut für Radioonkologie
2019
National Center for Tumor Diseases
2019
Medical University of Vienna
2016
Comprehensive Cancer Center Vienna
2016
University Hospital of Zurich
2016
University of Zurich
2016
National Institutes of Health
2016
Abstract Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, approach has not been systematically validated in ground truth studies. Based a simulated data set with tracts, we organized an open international tractography challenge, which resulted 96 distinct submissions from 20 research groups. Here, report encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% bundles (to at least some...
Since the introduction of positron emission tomography (PET) imaging with 68Ga-PSMA-HBED-CC (=68Ga-DKFZ-PSMA-11), this method has been regarded as a significant step forward in diagnosis recurrent prostate cancer (PCa). However, published data exist for small patient cohorts only. The aim evaluation was to analyse diagnostic value 68Ga-PSMA-ligand PET/CT large cohort and influence several possibly interacting variables. We performed retrospective analysis 319 patients who underwent from 2011...
Positron emission tomography (PET) with choline tracers has found widespread use for the diagnosis of prostate cancer (PC). However, metabolism is not increased in a considerable number cases, whereas prostate-specific membrane antigen (PSMA) overexpressed most PCs. Therefore, (68)Ga-labelled PSMA ligand could be superior to by obtaining high contrast. The aim this study was compare such novel tracer standard choline-based PET/CT.Thirty-seven patients biochemical relapse PC [mean (PSA) 11.1...
Abstract Purpose Since the clinical introduction of 68 Ga-PSMA-11 PET/CT, this imaging method has rapidly spread and is now regarded as a significant step forward in diagnosis recurrent prostate cancer (PCa). The aim study was to analyse influence several variables with possible on PSMA ligand uptake large cohort. Methods We performed retrospective analysis 1007 consecutive patients who were scanned PET/CT (1 h after injection) from January 2014 2017 detect disease. Patients untreated...
Recent studies have successfully demonstrated the use of deep-learning algorithms for dermatologist-level classification suspicious lesions by excessive proprietary image databases and limited numbers dermatologists. For first time, performance a algorithm trained open-source images exclusively is compared to large number dermatologists covering all levels within clinical hierarchy.We used methods from enhanced deep learning train convolutional neural network (CNN) with 12,378 dermoscopic...
PET imaging with the prostate-specific membrane antigen (PSMA)–targeted radioligand <sup>68</sup>Ga-PSMA-11 is regarded as a significant step forward in diagnosis of prostate cancer (PCa). More recently, PSMA ligand was developed that can be labeled <sup>68</sup>Ga, <sup>111</sup>In, <sup>177</sup>Lu, and <sup>90</sup>Y. This ligand, named PSMA-617, therefore enables both therapy PCa. The aims this evaluation were to clinically investigate distribution <sup>68</sup>Ga-PSMA-617 normal tissues...
Immunotherapy with ipilimumab improves the survival of patients metastatic melanoma. Because only around 20% experience long-term benefit, reliable markers are needed to predict a clinical response. Therefore, we sought determine if some myeloid cells and related inflammatory mediators could serve as predictive factors for patients' response ipilimumab.We performed an analysis in peripheral blood 59 stage IV melanoma before treatment at different time points upon therapy using laboratory...
BackgroundMelanoma is the most dangerous type of skin cancer but curable if detected early. Recent publications demonstrated that artificial intelligence capable in classifying images benign nevi and melanoma with dermatologist-level precision. However, a statistically significant improvement compared dermatologist classification has not been reported to date.MethodsFor this comparative study, 4204 biopsy-proven (1:1) were used for training convolutional neural network (CNN). New techniques...
BackgroundIn recent studies, convolutional neural networks (CNNs) outperformed dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these artificial intelligence were considered as opponents. However, the combination classifiers frequently yields superior results, both machine learning among humans. this study, we investigated potential benefit combining human for skin cancer classification.MethodsUsing 11,444 images, which divided into five diagnostic categories,...
BackgroundThe diagnosis of most cancers is made by a board-certified pathologist based on tissue biopsy under the microscope. Recent research reveals high discordance between individual pathologists. For melanoma, literature reports 25–26% for classifying benign nevus versus malignant melanoma. Deep learning was successfully implemented to enhance precision lung and breast cancer diagnoses. The aim this study illustrate potential deep assist human assessment histopathologic melanoma...
BackgroundRecently, convolutional neural networks (CNNs) systematically outperformed dermatologists in distinguishing dermoscopic melanoma and nevi images. However, such a binary classification does not reflect the clinical reality of skin cancer screenings which multiple diagnoses need to be taken into account.MethodsUsing 11,444 images, covered dermatologic comprising majority commonly pigmented lesions faced screenings, CNN was trained through novel deep learning techniques. A test set...
Accurate melanoma diagnosis is crucial for patient outcomes and reliability of AI diagnostic tools. We assess interrater variability among eight expert pathologists reviewing histopathological images clinical metadata 792 melanoma-suspicious lesions prospectively collected at German hospitals. Moreover, we provide access to the largest panel-validated dataset featuring dermoscopic with metadata. Complete agreement achieved in 53.5% cases (424/792), a majority vote ( ≥ five pathologists)...
BACKGROUND: The GERMS Group initiated a prospective multicenter study to assess prevalence and nature of bacterial contamination pooled buffy‐coat platelet concentrates (PPCs) apheresis (APCs) by routine screening with culture system. STUDY DESIGN AND METHODS: In nine centers overall, 52,243 (PLT) (15,198 APCs, 37,045 PPCs) were analyzed aerobic anaerobic cultures (BacT/ALERT, bioMérieux). RESULTS: 135 PLT (PCs; 0.26%), bacteria could be identified in the first (0.4% for APCs vs. 0.2% PPCs;...
Since the introduction of PSMA PET/CT with 68Ga-PSMA-11, this modality for imaging prostate cancer (PC) has spread worldwide. Preclinical studies have demonstrated that short-term androgen deprivation therapy (ADT) can significantly increase expression on PC cells. Additionally, retrospective clinical data in large patient cohorts suggest a positive association between ongoing ADT and pathological scan. The present evaluation was conducted to further analyse influence long-term findings. A...
Background: Artificial intelligence has shown promise in numerous experimental studies, particularly skin cancer diagnostics. Translation of these findings into the clinic is logical next step. This translation can only be successful if patients’ concerns and questions are addressed suitably. We therefore conducted a survey to evaluate view artificial melanoma diagnostics Germany. Participants Methods: A web-based questionnaire was designed using LimeSurvey, sent by e-mail university...