De-intensification of postoperative radiotherapy in head and neck cancer irrespective of human papillomavirus status-results of a prospective multicenter phase II trial (DIREKHT Trial).

Background: Current standard treatment concepts in head and neck squamous cell carcinoma (HNSCC) are based on former studies using 2D and 3D treatment plans. However, modern radiation techniques allow for a more precise and individual dose application. Therefore, in a clearly defined patient population, de-intensified risk-adapted radiation is investigated. Methods: Patients with newly diagnosed HNSCC after surgery (with resection margins ≥1 mm and cM0) with the following tumor stages (TNM 7th Edition) were eligible for the study: oral cavity, oropharynx, or larynx: pT1-3, pN0-pN2b; hypopharynx: pT1-2, pN1. The patients should have either a low risk of local recurrence [≤pT2, resection margin ≥5 mm, no peritumoral lymphangiosis (L0), and no perineural invasion] or contralateral lymph node metastasis (≤3 ipsilateral lymph node metastases, in case of well-lateralized oropharyngeal or oral cavity cancer contralateral cN0, otherwise pN0). Patients were assigned to three different treatment regimes with reduction of the treated volume, radiation dose, or both, according to tumor stage and results of surgery performed. The primary objective was to show an LRR of <10% after 2 years. Findings: A total of 150 patients were enrolled. Tumor localizations were as follows: n = 53 (35.3%), oral cavity; n = 94 (62.7%), oropharynx (82% HPV-positive); n = 2 (1.3%), hypopharynx; and n = 1 (0.7%), larynx. A total of 61 patients (41.0%) were stage IVA, 81 (54.0%) were stage III, and 8 (5.3%) were stage II. Median follow-up was 36 months. Cumulative incidence of 2y-LRR was 5.6% (95% CI: 1.7%-9.2%) in the whole study population and 14.1% (95% CI: 3.8%-23.2%) in patients with oral cavity cancer. Cumulative incidence of 2y-LRR in non-irradiated or dose-reduced regions was 3.5% (95% CI: 0.4%-6.5%). After 2 years, disease-free survival was 92% (95% CI: 87%-96%) and overall survival was 94% (95% CI: 90%-98%) for the complete study cohort. Acute III° toxicity was as follows: dysphagia, 30%; xerostomia, 7%; mucositis, 19%; and dermatitis, 4%. Dysphagia and xerostomia decrease over time. After 27 months, late dysphagia III° and xerostomia II° were 1% and 9%, respectively. Interpretation: The study met its primary objective. De-intensification of postoperative radiotherapy irrespective of HPV status in a predefined patient population is associated with a favorable toxicity profile without compromising LRR. In an unplanned subgroup analysis, a significantly increased risk of LRR was observed in patients with oral cavity cancer. In these patients, de-intensified radiotherapy should be applied with caution.

Comprehensive multimodal deep learning survival prediction enabled by a transformer architecture: A multicenter study in glioblastoma.

Background: This research aims to improve glioblastoma survival prediction by integrating MR images, clinical, and molecular-pathologic data in a transformer-based deep learning model, addressing data heterogeneity and performance generalizability. Methods: We propose and evaluate a transformer-based nonlinear and nonproportional survival prediction model. The model employs self-supervised learning techniques to effectively encode the high-dimensional MRI input for integration with nonimaging data using cross-attention. To demonstrate model generalizability, the model is assessed with the time-dependent concordance index (Cdt) in 2 training setups using 3 independent public test sets: UPenn-GBM, UCSF-PDGM, and Rio Hortega University Hospital (RHUH)-GBM, each comprising 378, 366, and 36 cases, respectively. Results: The proposed transformer model achieved a promising performance for imaging as well as nonimaging data, effectively integrating both modalities for enhanced performance (UCSF-PDGM test-set, imaging Cdt 0.578, multimodal Cdt 0.672) while outperforming state-of-the-art late-fusion 3D-CNN-based models. Consistent performance was observed across the 3 independent multicenter test sets with Cdt values of 0.707 (UPenn-GBM, internal test set), 0.672 (UCSF-PDGM, first external test set), and 0.618 (RHUH-GBM, second external test set). The model achieved significant discrimination between patients with favorable and unfavorable survival for all 3 datasets (log-rank P 1.9 × 10-8, 9.7 × 10-3, and 1.2 × 10-2). Comparable results were obtained in the second setup using UCSF-PDGM for training/internal testing and UPenn-GBM and RHUH-GBM for external testing (Cdt 0.670, 0.638, and 0.621). Conclusions: The proposed transformer-based survival prediction model integrates complementary information from diverse input modalities, contributing to improved glioblastoma survival prediction compared to state-of-the-art methods. Consistent performance was observed across institutions supporting model generalizability.

ERBB2/ ERBB3-mutated S100/ SOX10-positive unclassified high-grade uterine sarcoma: first detailed description of a novel entity.

With the increasing use of innovative next generation sequencing (NGS) platforms in routine diagnostic and research settings, the genetic landscape of uterine sarcomas has been dynamically evolving during the last two decades. Notably, the majority of recently recognized genotypes in uterine sarcomas represent gene fusions, while recurrent oncogene mutations of diagnostic and/ or therapeutic value have been rare. Recently, a distinctive aggressive uterine sarcoma expressing S100 and SOX10, but otherwise lacking diagnostic morphological, immunophenotypic and molecular features of other uterine malignancies has been presented in a scientific abstract form (USCAP, 2023), but detailed description and delineation of the entity is still missing. We herein describe two high-grade unclassified uterine sarcomas characterized by spindle to round cell morphology and diffuse expression of S100 and SOX10, originating in the uterine body and cervix of 53- and 45-year-old women and carrying an ERBB3 (p.Glu928Gly) and an ERBB2 (p.Val777Leu) mutation, respectively. Both tumors harbored in addition genomic HER2 amplification, ATRX mutation and CDKN2A deletion. Methylation studies revealed a methylome most similar to MPNST-like tumors, but distinct from melanoma, MPNST, clear cell sarcoma, and endometrial stromal sarcoma. Case 1 died of progressive peritoneal metastases after multiple trials of chemotherapy 47 months after diagnosis. Case 2 is a recent case who presented with a cervical mass, which was biopsied. This study defines a novel heretofore unrecognized aggressive uterine sarcoma with unique phenotypic and genotypic features. Given the potential value of targeting HER2, recognizing this tumor type is mandatory for appropriate therapeutic strategies and for better future delineation of the entity.

Exosomal ROR1 in peritoneal fluid identifies peritoneal disseminated PDAC and is associated with poor survival.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest forms of cancer and peritoneal dissemination is one major cause for this poor prognosis. Exosomes have emerged as promising biomarkers for gastrointestinal cancers and can be found in all kinds of bodily fluids, also in peritoneal fluid (PF). This is a unique sample due to its closeness to gastrointestinal malignancies. The receptor tyrosine kinase-like orphan receptor 1 (ROR1) has been identified as a potential biomarker in human cancers and represents a promising target for an immunotherapy approach, which could be considered for future treatment strategies. Here we prospectively analyzed the exosomal surface protein ROR1 (exo-ROR1) in PF in localized PDAC patients (PER-) on the one hand and peritoneal disseminated tumor stages (PER+) on the other hand followed by the correlation of exo-ROR1 with clinical-pathological parameters. Methods: Exosomes were isolated from PF and plasma samples of non-cancerous (NC) (n = 15), chronic pancreatitis (CP) (n = 4), localized PDAC (PER-) (n = 18) and peritoneal disseminated PDAC (PER+) (n = 9) patients and the surface protein ROR1 was detected via FACS analysis. Additionally, soluble ROR1 in PF was analyzed. ROR1 expression in tissue was investigated using western blots (WB), qPCR, and immunohistochemistry (IHC). Exosome isolation was proven by Nano Tracking Analysis (NTA), WB, Transmission electron microscopy (TEM), and BCA protein assay. The results were correlated with clinical data and survival analysis was performed. Results: PDAC (PER+) patients have the highest exo-ROR1 values in PF and can be discriminated from NC (p <0.0001), PDAC (PER-) (p <0.0001), and CP (p = 0.0112). PDAC (PER-) can be discriminated from NC (p = 0.0003). In plasma, exo-ROR1 is not able to distinguish between the groups. While there is no expression of ROR1 in the exocrine pancreatic tissue, PDAC and peritoneal metastasis show expression of ROR1. High exo-ROR1 expression in PF is associated with lower overall survival (p = 0.0482). Conclusion: With exo-ROR1 in PF we found a promising diagnostic and prognostic biomarker possibly discriminating between NC, PDAC (PER-) and PDAC (PER+) and might shed light on future diagnostic and therapeutic concepts in PDAC.

Treatment with (chemo)-radiation in old patients (≥76 years of age) with newly diagnosed non-metastatic squamous cell cancer of the head and neck region: real-world data from a tertiary referral center.

Purpose: Treatment of patients with cancer of the head and neck region is in focus in a multitude of studies. Of these patients, one patient group, those aged 76 and more, is mostly underrepresented despite requiring thorough and well-reasoned treatment decisions to offer curative treatment. This study investigates real-world data on curative treatment of old (≥76 years) patients with newly diagnosed squamous cell carcinoma of the head and neck region (HNSCC). Patients and methods: Between January 2010 and December 2021, we identified 71 patients older than 76 years with newly diagnosed HNSCC and cM0 at the Department of Radiation Oncology of the University Hospital of Erlangen-Nuremberg. Using electronic medical records, we analyzed treatment patterns and outcomes in terms of overall survival (OS), progression-free survival (PFS), and locoregional control (LRC) rate. Additionally, we performed univariate risk analysis and Cox regression in order to identify predictive factors associated with the abovementioned treatment outcomes. Results: The median follow-up was 18 months. OS was 83%, 79%, and 72% after 1 year, 2 years, and 3 years, respectively. PFS was 69%, 54%, and 46% after 1 year, 2 years, and 3 years, respectively. A total of 34 (48%) patients were treated with standard therapy according to current guidelines. The reasons for deviation from standard therapy before or during treatment were as follows: unfitness for cisplatin-based chemotherapy (n = 37), reduction of chemotherapy (n = 3), and dose reduction/interruption of radiotherapy (n = 8). Carboplatin-based systemic therapy showed improved PFS compared to cisplatin or cetuximab (60 vs. 28 vs. 15 months, p = 0.037) but without impact on OS (83 vs. 52 vs. 38 months, p = 0.807). Oropharyngeal tumor localization (p = 0.026) and combined treatment (surgery and postoperative treatment) (p = 0.008) were significant predictors for a better OS. In multivariate analysis, oropharyngeal tumor localization (p = 0.011) and combined treatment (p = 0.041) showed significantly increased PFS. After 1 year, 2 years, and 3 years, the cumulative incidence of locoregional recurrences (LRRs) was 13%, 24%, and 27%, respectively, and was significantly decreased in patients with oropharyngeal tumor localization (p = 0.037). Conclusions: Adherence to treatment protocols for radiotherapy alone in old patients with HNSCC is good, whereas the application of concurrent chemotherapy often deviates from guidelines in terms of de-escalation. An important risk factor for decreased OS, PFS, and a higher rate of LRR appears to be non-oropharyngeal tumor location in old patients.

Surgical and oncological outcome after extended lymph node dissection for carcinoma of the stomach and the esophagogastric junction: a retrospective analysis from an experienced single center.

Introduction: Gastric cancer remains the fourth leading cause of cancer-related death in Europe, while the proportion of adenocarcinomas of the esophagogastric junction has risen by more than one third over recent years. In 2018, 14,700 new cases of gastric cancer were estimated in Germany, while the 5-year relative survival rate is reported to be 33% for women and 30% for men; in the USA almost the same rate was reported, with 31% 5-year survival. Material and methods: Between 2001 and 2014, 590 patients with a diagnosis of gastric cancer underwent surgery in our institution, including 120 Siewert type II/III carcinomas of the esophagogastric junction. All patients underwent distal resection of the stomach, gastrectomy or total gastrectomy combined with transhiatal distal esophageal resection. All operations included D2-D3 lymph node dissection (LND). Data were recorded by the cancer registry of the department of surgery and analyzed retrospectively. Results: The patients were classified according to the TNM (UICC 2010) and Lauren classification. 29% of the patients underwent primary surgery and 31% received neoadjuvant therapy. The median number of harvested lymph nodes was 33 for patients diagnosed with gastric cancer, and 29 for esophagogastric adenocarcinomas, respectively. The anastomotic leak rate was 3%. In this study, the 5-year overall survival rate was 51% concerning gastric carcinomas, 44% for Siewert type II and 47% for Siewert III cancers of the esophagogastric junction. Conclusions: Increased survival with low complication rates were achieved after individualized and multimodal treatment concepts combined with consistently applied extended lymphadenectomy.

Machine Learning-Supported Diagnosis of Small Blue Round Cell Sarcomas Using Targeted RNA Sequencing.

Small blue round cell sarcomas (SBRCSs) are a heterogeneous group of tumors with overlapping morphologic features but markedly varying prognosis. They are characterized by distinct chromosomal alterations, particularly rearrangements leading to gene fusions, whose detection currently represents the most reliable diagnostic marker. Ewing sarcomas are the most common SBRCSs, defined by gene fusions involving EWSR1 and transcription factors of the ETS family, and the most frequent non-EWSR1-rearranged SBRCSs harbor a CIC rearrangement. Unfortunately, currently the identification of CIC::DUX4 translocation events, the most common CIC rearrangement, is challenging. Here, we present a machine-learning approach to support SBRCS diagnosis that relies on gene expression profiles measured via targeted sequencing. The analyses on a curated cohort of 69 soft-tissue tumors showed markedly distinct expression patterns for SBRCS subgroups. A random forest classifier trained on Ewing sarcoma and CIC-rearranged cases predicted probabilities of being CIC-rearranged >0.9 for CIC-rearranged-like sarcomas and <0.6 for other SBRCSs. Testing on a retrospective cohort of 1335 routine diagnostic cases identified 15 candidate CIC-rearranged tumors with a probability >0.75, all of which were supported by expert histopathologic reassessment. Furthermore, the multigene random forest classifier appeared advantageous over using high ETV4 expression alone, previously proposed as a surrogate to identify CIC rearrangement. Taken together, the expression-based classifier can offer valuable support for SBRCS pathologic diagnosis.

Benchmarking ChatGPT-4 on a radiation oncology in-training exam and Red Journal Gray Zone cases: potentials and challenges for ai-assisted medical education and decision making in radiation oncology.

Purpose: The potential of large language models in medicine for education and decision-making purposes has been demonstrated as they have achieved decent scores on medical exams such as the United States Medical Licensing Exam (USMLE) and the MedQA exam. This work aims to evaluate the performance of ChatGPT-4 in the specialized field of radiation oncology. Methods: The 38th American College of Radiology (ACR) radiation oncology in-training (TXIT) exam and the 2022 Red Journal Gray Zone cases are used to benchmark the performance of ChatGPT-4. The TXIT exam contains 300 questions covering various topics of radiation oncology. The 2022 Gray Zone collection contains 15 complex clinical cases. Results: For the TXIT exam, ChatGPT-3.5 and ChatGPT-4 have achieved the scores of 62.05% and 78.77%, respectively, highlighting the advantage of the latest ChatGPT-4 model. Based on the TXIT exam, ChatGPT-4's strong and weak areas in radiation oncology are identified to some extent. Specifically, ChatGPT-4 demonstrates better knowledge of statistics, CNS & eye, pediatrics, biology, and physics than knowledge of bone & soft tissue and gynecology, as per the ACR knowledge domain. Regarding clinical care paths, ChatGPT-4 performs better in diagnosis, prognosis, and toxicity than brachytherapy and dosimetry. It lacks proficiency in in-depth details of clinical trials. For the Gray Zone cases, ChatGPT-4 is able to suggest a personalized treatment approach to each case with high correctness and comprehensiveness. Importantly, it provides novel treatment aspects for many cases, which are not suggested by any human experts. Conclusion: Both evaluations demonstrate the potential of ChatGPT-4 in medical education for the general public and cancer patients, as well as the potential to aid clinical decision-making, while acknowledging its limitations in certain domains. Owing to the risk of hallucinations, it is essential to verify the content generated by models such as ChatGPT for accuracy.

Positive factors on survival of head and neck cancer of unknown primary: what the clinician can do.

BACKGROUND: Management of patients with head and neck cancer of unknown primary (HNCUP) is challenging. AIMS/OBJECTIVES: To provide a long-term analysis focusing on protective survival factors for clinical decision-making. Furthermore, the prognostic value of the current N classification system was evaluated. MATERIAL AND METHODS: We retrospectively analyzed patients with HNCUP between 2003 and 2016. Univariate and multivariate analyses were used to investigate predictors of overall survival (OS). RESULTS: A primary tumor was found in 67 of 290 patients with suspected HNCUP, leaving after exclusion 141 HNCUP cases for analysis, who received multi-step therapy (MST) (n = 108) or single therapy (n = 28). Chemotherapy (CT) (n = 101), curative MST, ≤3 positive lymph nodes (LN) (n = 33), squamous cell carcinoma (SCC) (n = 123), HPV+ (n = 21), M0 (n = 70) increased OS by 21.8%, 24.4%, 12.7%, 6.8%, 18.7%, 29.6%, respectively. 5- and 10-year OS was 78.1%/66.6%. The number of metastatic LNs predicted OS is better than N classification. CONCLUSION AND SIGNIFICANCE: Aspects for clinical decision-making: Curative MST and SCC histology were the most significant predictors for improved OS. Categorizing LN into 1, 2-3, and >3 LNs was more significant than the traditional N classification. The addition of CT to curative MST has a stronger impact on survival than HPV and N classifications.

Deep Learning and Registration-Based Mapping for Analyzing the Distribution of Nodal Metastases in Head and Neck Cancer Cohorts: Informing Optimal Radiotherapy Target Volume Design.

We introduce a deep-learning- and a registration-based method for automatically analyzing the spatial distribution of nodal metastases (LNs) in head and neck (H/N) cancer cohorts to inform radiotherapy (RT) target volume design. The two methods are evaluated in a cohort of 193 H/N patients/planning CTs with a total of 449 LNs. In the deep learning method, a previously developed nnU-Net 3D/2D ensemble model is used to autosegment 20 H/N levels, with each LN subsequently being algorithmically assigned to the closest-level autosegmentation. In the nonrigid-registration-based mapping method, LNs are mapped into a calculated template CT representing the cohort-average patient anatomy, and kernel density estimation is employed to estimate the underlying average 3D-LN probability distribution allowing for analysis and visualization without prespecified level definitions. Multireader assessment by three radio-oncologists with majority voting was used to evaluate the deep learning method and obtain the ground-truth distribution. For the mapping technique, the proportion of LNs predicted by the 3D probability distribution for each level was calculated and compared to the deep learning and ground-truth distributions. As determined by a multireader review with majority voting, the deep learning method correctly categorized all 449 LNs to their respective levels. Level 2 showed the highest LN involvement (59.0%). The level involvement predicted by the mapping technique was consistent with the ground-truth distribution (p for difference 0.915). Application of the proposed methods to multicenter cohorts with selected H/N tumor subtypes for informing optimal RT target volume design is promising.

The health-related quality of life of sarcoma patients treated with neoadjuvant versus adjuvant radiotherapy - Results of a multi-center observational study.

AIM: The sequence of radiotherapy and resection in patients with soft tissue sarcomas is usually discussed on an individual basis. Better understanding of potential differences of health-related quality of life (QoL) between patients undergoing adjuvant (ART) versus neoadjuvant radiotherapy (NART) is therefore helpful for clinical decision making. METHODS: Adult sarcoma patients from 39 hospitals completed the European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire (EORTC QLQ-C30). Differences in global QoL, physical functioning, role functioning, fatigue, pain, and insomnia between ART versus NART were investigated with multivariate regression, adjusting for age, gender, chemotherapy, grading, stage, tumor location, recurrence/distant metastasis, sarcoma type, time since last treatment, and treatment status using validated thresholds. RESULTS: A total of 1110 patients participated. Of them, 340 had received radiotherapy (NART: n = 95, 28%; ART: n = 245, 72%). Global QoL was 59.3 on average after NART and 60.5 after ART (Badj = 1.0, p = 0.74). Physical functioning was 65.9 compared to 70.5 (Badj = 4.2; p = 0.16), role function 48.8 vs. 56.7 (Badj = 7.0, p = 0.08), fatigue 47.5 vs. 45.4 (Badj = -1.2; p = 0.71), pain 40.2 vs. 34.1 (Badj = -6.8; p = 0.08), and insomnia 33.7 vs. 41.6 (Badj = 5.5, p = 0.16). Among patients with NART, clinically relevant QoL impairments were less frequent 2 years after treatment compared to < 2 years thereafter (n = 6 vs. n = 4 on average). CONCLUSION: There is little evidence for QoL differences in most domains and overall QoL between the two irradiation groups. However, patients after NART might experience worse role functioning and pain but fewer problems with insomnia compared to patients after ART.

Chemoradiotherapy plus hyperthermia (CRTH) versus chemoradiotherapy (CRT) alone in neoadjuvant treatment of soft tissue sarcoma: tumor response, treatment toxicity and disease control.

INTRODUCTION: Neoadjuvant chemotherapy and radiotherapy for the management of soft tissue sarcomas (STS) are still preferably delivered sequentially, with or without concurrent hyperthermia. Concurrent delivery of chemo-, radio- and thermotherapy may produce synergistic effects and reduce chemotherapy-free intervals. The few available studies suggest that concurrent chemoradiation (CRT) has a greater local effect. Data on the efficacy and toxicity of adding hyperthermia to CRT (CRTH) are sparse. MATERIALS AND METHODS: A cohort of 101 patients with STS of the extremities and trunk who received CRT (n = 33) or CRTH (n = 68) before resection of macroscopic tumor (CRT: n = 19, CRTH: n = 49) or re-resection following a non-oncological resection, so called 'whoops procedure', (CRT: n = 14, CRTH: n = 19) were included in this retrospective study. CRT consisted of two cycles of doxorubicine (50 mg/m2 on d2) plus ifosfamide (1500 mg/m2 on d1-5, q28) plus radiation doses of up to 60 Gy. Hyperthermia was delivered in two sessions per week. RESULTS: All patients received the minimum dose of 50 Gy. Median doses of ifosfamide and doxorubicin were comparable between CRT (75%/95%) and CRTH (78%/97%). The median number of hyperthermia sessions was seven. There were no differences in acute toxicities. Major wound complications occurred in 15% (CRT) vs. 25% (CRTH) (p = 0.19). In patients with macroscopic disease, the addition of hyperthermia resulted in a tendency toward improved remission: regression ≥90% occurred in 21/48 (CRTH) vs. 4/18 (CRT) patients (p = 0.197). With a median postoperative follow-up of 72 months, 6-year local control and overall survival rates for CRTH vs. CRT alone were 85 vs. 78% (p = 0.938) and 79 vs. 71% (p = 0.215). CONCLUSIONS: Both CRT and CRTH are well tolerated with an expected rate of wound complications. The results suggest that adding hyperthermia may improve tumor response.

Deep learning for automatic head and neck lymph node level delineation provides expert-level accuracy.

Background: Deep learning-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still underinvestigated in academic literature. In particular, there is no publicly available open-source solution for large-scale autosegmentation of HN_LNL in the research setting. Methods: An expert-delineated cohort of 35 planning CTs was used for training of an nnU-net 3D-fullres/2D-ensemble model for autosegmentation of 20 different HN_LNL. A second cohort acquired at the same institution later in time served as the test set (n = 20). In a completely blinded evaluation, 3 clinical experts rated the quality of deep learning autosegmentations in a head-to-head comparison with expert-created contours. For a subgroup of 10 cases, intraobserver variability was compared to the average deep learning autosegmentation accuracy on the original and recontoured set of expert segmentations. A postprocessing step to adjust craniocaudal boundaries of level autosegmentations to the CT slice plane was introduced and the effect of autocontour consistency with CT slice plane orientation on geometric accuracy and expert rating was investigated. Results: Blinded expert ratings for deep learning segmentations and expert-created contours were not significantly different. Deep learning segmentations with slice plane adjustment were rated numerically higher (mean, 81.0 vs. 79.6, p = 0.185) and deep learning segmentations without slice plane adjustment were rated numerically lower (77.2 vs. 79.6, p = 0.167) than manually drawn contours. In a head-to-head comparison, deep learning segmentations with CT slice plane adjustment were rated significantly better than deep learning contours without slice plane adjustment (81.0 vs. 77.2, p = 0.004). Geometric accuracy of deep learning segmentations was not different from intraobserver variability (mean Dice per level, 0.76 vs. 0.77, p = 0.307). Clinical significance of contour consistency with CT slice plane orientation was not represented by geometric accuracy metrics (volumetric Dice, 0.78 vs. 0.78, p = 0.703). Conclusions: We show that a nnU-net 3D-fullres/2D-ensemble model can be used for highly accurate autodelineation of HN_LNL using only a limited training dataset that is ideally suited for large-scale standardized autodelineation of HN_LNL in the research setting. Geometric accuracy metrics are only an imperfect surrogate for blinded expert rating.

Prospective Evaluation of CD45RA+/CCR7- Effector Memory T (TEMRA) Cell Subsets in Patients with Primary and Secondary Brain Tumors during Radiotherapy of the Brain within the Scope of the Prospective Glio-CMV-01 Clinical Trial.

Radiotherapy (RT) of the brain is a common treatment for patients with high-grade gliomas and brain metastases. It has previously been shown that reactivation of cytomegalovirus (CMV) frequently occurs during RT of the brain. This causes neurological decline, demands antiviral treatment, and is associated with a worse prognosis. CMV-specific T cells are characterized by a differentiated effector memory phenotype and CD45RA+ CCR7- effector memory T (TEMRA) cells were shown to be enriched in CMV seropositive individuals. In this study, we investigated the distribution of TEMRA cells and their subsets in the peripheral blood of healthy donors and, for the first time, prospectively within the scope of the prospective Glio-CMV-01 clinical trial of patients with high-grade glioma and brain metastases during radiation therapy as a potential predictive marker. First, we developed a multicolor flow cytometry-based assay to monitor the frequency and distribution of TEMRA cells in a longitudinal manner. The CMV serostatus and age were considered as influencing factors. We revealed that patients who had a reactivation of CMV have significantly higher amounts of CD8+ TEMRA cells. Further, the distribution of the subsets of TEMRA cells based on the expression of CD27, CD28, and CD57 is highly dependent on the CMV serostatus. We conclude that the percentage of CD8+ TEMRA cells out of all CD8+ T cells has the potential to serve as a biomarker for predicting the risk of CMV reactivation during RT of the brain. Furthermore, this study highlights the importance of taking the CMV serostatus into account when analyzing TEMRA cells and their subsets.

Differences and Similarities in the Pattern of Early Metabolic and Morphologic Response after Induction Chemo-Immunotherapy versus Induction Chemotherapy Alone in Locally Advanced Squamous Cell Head and Neck Cancer.

Background: In head and neck cancer patients, parameters of metabolic and morphologic response of the tumor to single-cycle induction chemotherapy (IC) with docetaxel, cis- or carboplatin are used to decide the further course of treatment. This study investigated the effect of adding a double immune checkpoint blockade (DICB) of tremelimumab and durvalumab to IC on imaging parameters and their significance with regard to tumor cell remission. Methods: Response variables of 53 patients treated with IC+DICB (ICIT) were compared with those of 104 who received IC alone. Three weeks after one cycle, pathologic and, in some cases, clinical and endoscopic primary tumor responses were evaluated and correlated with a change in 18F-FDG PET and CT/MRI-based maximum-standardized uptake values (SUVmax) before (SUVmaxpre), after treatment (SUVmaxpost) and residually (resSUVmax in % of SUVmaxpre), and in maximum tumor diameter (Dmax) before (Dmaxpre) and after treatment (Dmaxpost) and residually (resD). Results: Reduction of SUVmax and Dmax occurred in both groups; values were SUVmaxpre: 14.4, SUVmaxpost: 6.6, Dmaxpre: 30 mm and Dmaxpost: 23 mm for ICIT versus SUVmaxpre: 16.5, SUVmaxpost: 6.4, Dmaxpre: 21 mm, and Dmaxpost: 16 mm for IC alone (all p < 0.05). ResSUVmax was the best predictor of complete response (IC: AUC: 0.77; ICIT: AUC: 0.76). Metabolic responders with resSUVmax ≤ 40% tended to have a higher rate of CR to ICIT (88%; n = 15/17) than to IC (65%; n = 30/46; p = 0.11). Of the metabolic nonresponders (resSUVmax > 80%), 33% (n = 5/15) achieved a clinical CR to ICIT versus 6% (n = 1/15) to IC (p = 0.01). Conclusions: ICIT and IC quickly induce a response and 18F-FDG PET is the more accurate modality for identifying complete remission. The rate of discrepant response, i.e., pCR with metabolic nonresponse after ICIT was >30%.

Radio(chemo)therapy in anaplastic thyroid cancer-high locoregional but low distant control rates-a monocentric analysis of a tertiary referral center.

BACKGROUND: Anaplastic thyroid cancer (ATC) is a lethal disease with highly aggressive disease progression. This study analyses the influence of radio(chemo)therapy, R(C)T, on disease control, survival rates and predictors for survival. PATIENTS AND METHODS: A total of 33 patients with ATC, treated at a tertiary referral center between May 2001 and April 2020 were included. Univariate and multivariate analysis were used to investigate correlates of R(C)T and predictors on disease control and survival rates. RESULTS: Median follow-up was 4 months. In UICC stage IVA and IVB median overall survival (OS) was 8 months, median progression-free survival (PFS) was 6 months. Patients with UICC stage IVA and IVB and patients being irradiated with a radiation dose of more than 60 Gy showed increased OS. Of these patients, 3 were alive and free from disease. All of them receiving cisplatin-based radiochemotherapy and a minimum radiation dose of 66 Gy. UICC stage IVC showed a median OS of 2.5 months and a median PFS of 1 month. Only 2 of 16 patients had local failure. CONCLUSION: Depending on UICC stage, RT with high radiation dose can lead to improved OS or at least higher locoregional control. A limiting factor is the high incidence of distant metastases; therefore modern systemic treatment options should be integrated into multimodal therapy concepts.

Factors influencing downstaging after neoadjuvant long-course chemoradiotherapy in rectal carcinoma.

PURPOSE: This single-centre cohort study was designed to identify factors that can predict primary tumour downstaging by neoadjuvant chemoradiotherapy (nCRT) in rectal carcinoma. METHODS: Prospectively collected data from 555 patients with clinical T category (cT) cT3-4 rectal carcinoma treated between 1995 and 2019 were retrospectively analysed. All patients received long-term neoadjuvant chemoradiotherapy followed by surgery with curative intent at the Department of Surgery, University Hospital Erlangen, Germany. Patient-, tumour- and treatment-related factors with a potential impact on the downstaging of rectal carcinoma to pathological T category (pT) ≤ ypT2 and ypT0 were analysed in univariate and multivariate logistic regression analyses. The prognosis of patients with and without downstaging of the primary tumour was compared. RESULTS: A total of 288 (51.9%) patients showed downstaging to ≤ ypT2. Eighty-six (15.5%) patients achieved clinical complete regression (ypT0). In the multivariate logistic regression analysis, the factors cT category, BMI, ECOG score, CEA, histological type, extension in the rectum and year of the start of treatment were found to be independent factors for predicting downstaging to ≤ ypT2 after neoadjuvant chemoradiotherapy. The year of treatment initiation also remained an independent significant predictor for pathological complete regression. The prognosis was superior in patients with downstaging to ≤ ypT2 in terms of locoregional and distant recurrence as well as disease-free and overall survival. CONCLUSION: Factors predicting downstaging after long-term nCRT could be identified. This may be helpful for counselling patients and selecting the optimal treatment for patients with advanced rectal carcinoma.

[Highlights from the 2021 ASCO and ESMO annual meetings on radiotherapy of head and neck cancer]. / Highlights der ASCO- und ESMO-Jahrestagungen 2021 zur Strahlentherapie von Kopf-Hals-Tumoren.

At this year's annual meetings of the American Society of Clinical Oncology (ASCO) and the European Society for Medical Oncology (ESMO), several studies on radiotherapy of locally advanced head and neck cancer were presented. For the indication of definitive radiochemotherapy, particularly the administration of immune checkpoint inhibitors concomitant to radiotherapy was investigated. In the phase III GORTEC-REACH trial, combined inhibition of epidermal growth factor receptor (EGFR) and programmed death-ligand (PD-L1) concomitant to radiotherapy of locally advanced head and neck cancer was inferior to platinum-based chemoradiotherapy. However, this therapeutic approach may be more efficient than radiotherapy with simultaneous EGFR inhibition alone. The concept of the phase II CheckRad-CD8 trial with induction chemoimmunotherapy followed by chemotherapy-free radioimmunotherapy after appropriate patient selection also proved to be highly efficient. In initial phase II trials, dose de-escalation of radiotherapy seems feasible for HPV-positive oropharyngeal cancer after appropriate patient selection both postoperatively (ECOG-ACRIN E3311 trial) and after induction therapy (Optima II trial). However, dose de-escalation should currently not be performed outside of clinical trials. In addition, first studies indicate a benefit of functional imaging (diffusion-weighted magnetic resonance imaging [MRI] or F­fluoromisonidazole positron-emission tomography [FMISO-PET]) to establish personalized dose concepts in radiotherapy.