Publications by authors named "Nicolaus Andratschke"

Purpose: To use imaging data from stereotactic MR-guided online adaptive radiotherapy (SMART) of ultracentral lung tumors (ULT) for development of a safe non-adaptive approach towards stereotactic body radiotherapy (SBRT) of ULT.

Patients And Methods: Analysis is based on 19 patients with ULT who received SMART (10 × 5.0-5.

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The PRIMALung EORTC-1901 trial investigates brain MRI ± PCI in all-stages of SCLC, aiming for non-inferior survival, improve cognition in the era of immunotherapy. @finn_corinne.

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Introduction: Reirradiation has gained increasing interest, as advances in systemic therapy increase the survival of patients with cancer, and modern radiation techniques allow more precise treatments. However, high-quality prospective evidence on the safety and efficacy of reirradiation to guide clinical practice remains scarce. This systematic review evaluates ongoing prospective studies on reirradiation to identify research gaps and priorities.

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Background/purpose: High doses to healthy cardiac substructures (CS) in stereotactic arrhythmia radioablation (STAR) raise concerns regarding potential treatment-induced cardio-toxicity. However, CS contours are not routinely created, hindering the understanding of the CS dose-effect relationships. To address this issue, the alignment of CS contouring was initiated within the STOPSTORM consortium.

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Article Synopsis
  • A subgroup of patients with oligometastatic cancer may benefit from local treatment of all cancer lesions to achieve longer disease-free survival, especially when brain metastases are involved.
  • An analysis of 7,000 PET scans identified 106 patients with both extracranial oligometastases and brain metastases, finding that brain involvement significantly impacted disease classification and treatment outcomes.
  • Patients with oligometastasic disease had a median survival of 28 months compared to 10 months for polymetastatic patients, suggesting that brain metastases should not automatically exclude individuals from clinical trials.
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With the emergence of high-precision radiotherapy technologies such as stereotactic ablative radiotherapy (SABR), MR guided brachytherapy, image guided intensity modulated photon and proton radiotherapy and most recently daily adaptive radiotherapy, reirradiation is increasingly recognized as a viable treatment option for many patients. This includes those with recurrent, metastatic or new malignancies post initial radiotherapy. The primary challenge in reirradiation lies in balancing tumor control against the risk of severe toxicity from cumulative radiation doses to previously irradiated normal tissue.

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Aims: Multidisciplinary tumor boards (MDTs) are an integral part of ensuring high-quality, evidence-based and personalized cancer care. In this study, we aimed to evaluate the adherence to and implementation of MDT recommendations in patients with oligometastatic disease (OMD).

Methods: We screened all oncologic positron emission tomography (PET) scans conducted at a single comprehensive cancer center in 2020.

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Background: The treatment options for patients with progressive malignant tumors despite primary radiotherapy are often limited. In selected cases, re-irradiation can be offered. This article concerns the selection criteria and results of re-irradiation for certain types of cancer.

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Purpose: STereotactic Arrhythmia Radioablation (STAR) showed promising results in patients with refractory ventricular tachycardia. However, clinical data are scarce and heterogeneous. The STOPSTORM.

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Background: Primary meningeal melanocytic tumors are ultra-rare entities with distinct histological and molecular features compared with other melanocytic or pigmented lesions, such as brain and leptomeningeal metastases from metastatic melanoma.

Methods: The European Network for Rare Cancers (EURACAN) Task Force on Ultra-Rare Brain Tumors (domain 10, subdomain 10) performed a literature review from January 1985 to December 2023 regarding the epidemiologic and clinical characteristics, histological and molecular features, radiological findings, and efficacy of local treatments (surgery and radiotherapy) and systemic treatments for these entities.

Results: Molecular analysis can detect specific mutations, including GNAQ, GNA11, SF3B1, EIF1AX, BAP1, that are typically found in circumscribed primary meningeal melanocytic tumors and not in other melanocytic lesions, whereas NRAS and BRAF mutations are typical for diffuse primary meningeal melanocytic tumors.

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Article Synopsis
  • The study investigates how differences in data from multiple hospitals affect the effectiveness of deep learning models for automatically segmenting brain metastases (BM) and evaluates a technique called "learning without forgetting" (LWF) to enhance model adaptability without needing to share sensitive data.
  • Six datasets from various universities were analyzed, and results showed that training on data from just one center provided diverse performance levels, while training on mixed data from multiple centers generally improved outcomes, especially for certain institutions.
  • The findings suggest that LWF outperformed traditional transfer learning methods in maintaining high sensitivity and precision during training, indicating it could be a valuable strategy for training models while addressing privacy concerns, despite challenges from data variability.
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Background And Purpose: Current radiotherapy guidelines rely heavily on imaging-based monitoring. Liquid biopsy monitoring promises to complement imaging by providing frequent systemic information about the tumor. In particular, cell-free DNA (cfDNA) sequencing offers a tumor-agnostic approach, which lends itself to monitoring heterogeneous cohorts of cancer patients.

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Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists. Early detection is crucial for improving patient survival rates. However, performing total body screening (TBS), i.

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  • Surgical resection is the primary treatment for patients with large or symptomatic brain metastases, but there's still a risk of local failure, prompting the development of a prediction tool to identify those at high risk.
  • Data from the AURORA study included 253 patients for training and 99 for external testing, utilizing radiomic features from MRI scans to enhance prediction accuracy.
  • The elastic net regression model combining radiomic and clinical features showed a significant improvement in predicting local failure, with lower risk groups experiencing only 9% failure at 24 months compared to 74% in high-risk groups, suggesting potential for improved patient follow-up and treatment.
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Background And Purpose: Magnetic resonance imaging (MRI) scans are highly sensitive to acquisition and reconstruction parameters which affect feature stability and model generalizability in radiomic research. This work aims to investigate the effect of image pre-processing and harmonization methods on the stability of brain MRI radiomic features and the prediction performance of radiomic models in patients with brain metastases (BMs).

Materials And Methods: Two T1 contrast enhanced brain MRI data-sets were used in this study.

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Introduction: The international phase II single-arm LungTech trial 22113-08113 of the European Organization for Research and Treatment of Cancer assessed the safety and efficacy of stereotactic body radiotherapy (SBRT) in patients with centrally located early-stage NSCLC.

Methods: Patients with inoperable non-metastatic central NSCLC (T1-T3 N0 M0, ≤7cm) were included. After prospective central imaging review and radiation therapy quality assurance for any eligible patient, SBRT (8 × 7.

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Background And Purpose: The feasibility of acquiring diffusion-weighted imaging (DWI) images on an MR-Linac for quantitative response assessment during radiotherapy was explored. DWI data obtained with a Spin Echo Echo Planar Imaging sequence adapted for a 0.35 T MR-Linac were examined and compared with DWI data from a conventional 3 T scanner.

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The purpose of this European Society for Radiotherapy and Oncology (ESTRO) project, endorsed by the European Association of Urology, is to explore expert opinion on the management of patients with oligometastatic and oligoprogressive renal cell carcinoma by means of stereotactic ablative radiotherapy (SABR) on extracranial metastases, with the aim of developing consensus recommendations for patient selection, treatment doses, and concurrent systemic therapy. A questionnaire on SABR in oligometastatic renal cell carcinoma was prepared by a core group and reviewed by a panel of ten prominent experts in the field. The Delphi consensus methodology was applied, sending three rounds of questionnaires to clinicians identified as key opinion leaders in the field.

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Article Synopsis
  • Standard imaging protocols ensure the quality of MR images for radiotherapy, but metallic implants can disrupt this integrity.
  • A new method evaluates the geometric distortions created by both passive and active implants during imaging with a low-field MR-LINAC.
  • Results indicate that while implants can cause significant distortions close to their location (up to 3 mm), the spatial integrity of images is maintained beyond a certain distance, which can help improve treatment plans involving nearby organs.
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Background: Oligoprogression is defined as cancer progression of a limited number of metastases under active systemic therapy. The role of metastasis-directed therapy, using stereotactic body radiotherapy (SBRT), is controversial as is the continuation versus switch of systemic therapy. We report outcomes of oligoprogressive patients after SBRT, and compare those patients that continued or switched their current line of systemic therapy.

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Background And Purpose: Studies investigating the application of Artificial Intelligence (AI) in the field of radiotherapy exhibit substantial variations in terms of quality. The goal of this study was to assess the amount of transparency and bias in scoring articles with a specific focus on AI based segmentation and treatment planning, using modified PROBAST and TRIPOD checklists, in order to provide recommendations for future guideline developers and reviewers.

Materials And Methods: The TRIPOD and PROBAST checklist items were discussed and modified using a Delphi process.

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Background And Purpose: To improve radiotherapy (RT) planning efficiency and plan quality, knowledge-based planning (KBP) and deep learning (DL) solutions have been developed. We aimed to make a direct comparison of these models for breast cancer planning using the same training, validation, and testing sets.

Materials And Methods: Two KBP models were trained and validated with 90 RT plans for left-sided breast cancer with 15 fractions of 2.

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Article Synopsis
  • - The study explores the continuum of metastatic disease, aiming to quantify the tumor burden and patterns of spread in patients referred for PET scans, revealing a complex relationship between the number of metastases and their organ distribution.
  • - Analysis of over 7,000 PET scans showed that 33% of patients had metastatic disease, with about half classified as oligometastatic (max 5 metastases) and half as polymetastatic (over 5 metastases), displaying common primary tumors like lung and breast cancers.
  • - Findings indicate that many patients either have a solitary metastasis or a high tumor burden (>10 metastases), but those with multiple metastases often have them concentrated in one or two organs, supporting existing theories of metast
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Article Synopsis
  • Stereotactic body radiation therapy (SBRT) for ultra-central lung tumors has high toxicity rates.
  • The proximal bronchial tree (PBT) was divided into seven sections to study differences in radiosensitivity.
  • A risk-adapted SBRT regimen with a specific dose has shown excellent tumor control and lower severe toxicity rates, with a modeling study suggesting a dose threshold for low bronchial toxicity.
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Magnetic resonance image guided radiation therapy (MRIgRT) is a relatively new technology that has already shown outcomes benefits but that has not yet reached its clinical potential. The improved soft-tissue contrast provided with MR, coupled with the immediacy of image acquisition with respect to the treatment, enables expansion of on-table adaptive protocols, currently at a cost of increased treatment complexity, use of human resources, and longer treatment slot times, which translate to decreased throughput. Many approaches are being investigated to meet these challenges, including the development of artificial intelligence (AI) algorithms to accelerate and automate much of the workflow and improved technology that parallelizes workflow tasks, as well as improvements in image acquisition speed and quality.

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