Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives.

The rapid development of artificial intelligence (AI) has gained importance, with many tools already entering our daily lives. The medical field of radiation oncology is also subject to this development, with AI entering all steps of the patient journey. In this review article, we summarize contemporary AI techniques and explore the clinical applications of AI-based automated segmentation models in radiotherapy planning, focusing on delineation of organs at risk (OARs), the gross tumor volume (GTV), and the clinical target volume (CTV). Emphasizing the need for precise and individualized plans, we review various commercial and freeware segmentation tools and also state-of-the-art approaches. Through our own findings and based on the literature, we demonstrate improved efficiency and consistency as well as time savings in different clinical scenarios. Despite challenges in clinical implementation such as domain shifts, the potential benefits for personalized treatment planning are substantial. The integration of mathematical tumor growth models and AI-based tumor detection further enhances the possibilities for refining target volumes. As advancements continue, the prospect of one-stop-shop segmentation and radiotherapy planning represents an exciting frontier in radiotherapy, potentially enabling fast treatment with enhanced precision and individualization.

Exploring molecular glioblastoma: Insights from advanced imaging for a nuanced understanding of the molecularly defined malignant biology.

Background: Molecular glioblastoma (molGB) does not exhibit the histologic hallmarks of a grade 4 glioma but is nevertheless diagnosed as glioblastoma when harboring specific molecular markers. MolGB can easily be mistaken for similar-appearing lower-grade astrocytomas. Here, we investigated how advanced imaging could reflect the underlying tumor biology. Methods: Clinical and imaging data were collected for 7 molGB grade 4, 9 astrocytomas grade 2, and 12 astrocytomas grade 3. Four neuroradiologists performed VASARI-scoring of conventional imaging, and their inter-reader agreement was assessed using Fleiss κ coefficient. To evaluate the potential of advanced imaging, 2-sample t test, 1-way ANOVA, Mann-Whitney U, and Kruskal-Wallis test were performed to test for significant differences between apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) that were extracted fully automatically from the whole tumor volume. Results: While conventional VASARI imaging features did not allow for reliable differentiation between glioma entities, rCBV was significantly higher in molGB compared to astrocytomas for the 5th and 95th percentile, mean, and median values (P < .05). ADC values were significantly lower in molGB than in astrocytomas for mean, median, and the 95th percentile (P < .05). Although no molGB showed contrast enhancement initially, we observed enhancement in the short-term follow-up of 1 patient. Discussion: Quantitative analysis of diffusion and perfusion parameters shows potential in reflecting the malignant tumor biology of molGB. It may increase awareness of molGB in a nonenhancing, "benign" appearing tumor. Our results support the emerging hypothesis that molGB might present glioblastoma captured at an early stage of gliomagenesis.

Incidental dose distribution to contralateral internal mammary nodes in breast cancer patients undergoing adjuvant radiotherapy.

Background and purpose: In a relevant number of primary breast cancer patients, lymphatic drainage to the contralateral internal mammary nodes (cIMN) is being observed. Nevertheless, so far lymphatic drainage pathway to the cIMN is largely neglected during adjuvant radiotherapy. Materials and methods: This study evaluated the incidental dose to the cIMN for 120 volumetric modulated arc therapy (VMAT) treatment plans for node positive breast in dependence of internal mammary node irradiation (IMNI) and deep inspiration breath hold (DIBH). Additionally, incidental dose distribution to the cIMN based on the field design in the MA20, EORTC22922/10925 and AMAROS trials was assessed. Results: The incidental dose (Dmean ± SD) to the cIMN-CTV was 13.0 (±4.7) Gy with a maximum dose of < 30 Gy in 113/120 cases. If IMNI was included (n = 80), the Dmean to the cIMN-CTV was significantly higher compared to no IMNI, but still comparably low (n = 40; 14.3 Gy vs. 9.6 Gy; p = 0.0001). Furthermore, the dose in the cIMN during free breathing (n = 80) was higher compared to DIBH (n = 40; 13.9 Gy vs. 11.2 Gy; p = 0.002).Simulated treatment plans based on the randomized RNI trials revealed neglectable dose coverage of the cIMN (Dmean 1.0-1.8 Gy) for all protocols. Conclusion: Neither in the randomized RNI trials nor during contemporary treatment techniques clinically relevant dose distribution to the cIMN was observed. Further studies are warranted to assess the potential impact of intended irradiation of cIMN in high-risk patients.

CT-based radiomics for predicting breast cancer radiotherapy side effects.

Skin inflammation with the potential sequel of moist epitheliolysis and edema constitute the most frequent breast radiotherapy (RT) acute side effects. The aim of this study was to compare the predictive value of tissue-derived radiomics features to the total breast volume (TBV) for the moist cells epitheliolysis as a surrogate for skin inflammation, and edema. Radiomics features were extracted from computed tomography (CT) scans of 252 breast cancer patients from two volumes of interest: TBV and glandular tissue (GT). Machine learning classifiers were trained on radiomics and clinical features, which were evaluated for both side effects. The best radiomics model was a least absolute shrinkage and selection operator (LASSO) classifier, using TBV features, predicting moist cells epitheliolysis, achieving an area under the receiver operating characteristic (AUROC) of 0.74. This was comparable to TBV breast volume (AUROC of 0.75). Combined models of radiomics and clinical features did not improve performance. Exclusion of volume-correlated features slightly reduced the predictive performance (AUROC 0.71). We could demonstrate the general propensity of planning CT-based radiomics models to predict breast RT-dependent side effects. Mammary tissue was more predictive than glandular tissue. The radiomics features performance was influenced by their high correlation to TBV volume.

Imaging meningioma biology: Machine learning predicts integrated risk score in WHO grade 2/3 meningioma.

Background: Meningiomas are the most common primary brain tumors. While most are benign (WHO grade 1) and have a favorable prognosis, up to one-fourth are classified as higher-grade, falling into WHO grade 2 or 3 categories. Recently, an integrated risk score (IRS) pertaining to tumor biology was developed and its prognostic relevance was validated in a large, multicenter study. We hypothesized imaging data to be reflective of the IRS. Thus, we assessed the potential of a machine learning classifier for its noninvasive prediction using preoperative magnetic resonance imaging (MRI). Methods: In total, 160 WHO grade 2 and 3 meningioma patients from 2 university centers were included in this study. All patients underwent surgery with histopathological workup including methylation analysis. Preoperative MRI scans were automatically segmented, and radiomic parameters were extracted. Using a random forest classifier, 3 machine learning classifiers (1 multiclass classifier for IRS and 2 binary classifiers for low-risk and high-risk prediction, respectively) were developed in a training set (120 patients) and independently tested in a hold-out test set (40 patients). Results: Multiclass IRS classification had a test set area under the curve (AUC) of 0.7, mostly driven by the difficulties in clearly separating medium-risk from high-risk patients. Consequently, a classifier predicting low-risk IRS versus medium-/high-risk showed a very high test accuracy of 90% (AUC 0.88). In particular, "sphericity" was associated with low-risk IRS classification. Conclusion: The IRS, in particular molecular low-risk, can be predicted from imaging data with high accuracy, making this important prognostic classification accessible by imaging.

Membrane-bound Heat Shock Protein mHsp70 Is Required for Migration and Invasion of Brain Tumors.

Molecular chaperones, especially 70 kDa heat shock protein, in addition to their intracellular localization in cancer cells, can be exposed on the surface of the plasma membrane. We report that the membrane-associated chaperone mHsp70 of malignant brain tumors is required for high migratory and invasive activity of cancer cells. Live-cell inverted confocal microscopy of tumor samples from adult (n = 23) and pediatric (n = 9) neurooncologic patients showed pronounced protein expression on the membrane, especially in the perifocal zone. Mass spectrometry analysis of lipid rafts isolated from tumor cells confirmed the presence of the protein in the chaperone cluster (including representatives of other families, such as Hsp70, Hsc70, Hsp105, and Hsp90), which in turn, during interactome analysis, was associated with proteins involved in cell migration (e.g., Rac1, RhoC, and myosin-9). The use of small-molecule inhibitors of HSP70 (PES and JG98) led to a substantial decrease in the invasive potential of cells isolated from a tumor sample of patients, which indicates the role of the chaperone in invasion. Moreover, the use of HSP70 inhibitors in animal models of orthotopic brain tumors significantly delayed tumor progression, which was accompanied by an increase in overall survival. Data demonstrate that chaperone inhibitors, particularly JG98, disrupt the function of mHsp70, thereby providing an opportunity to better understand the diverse functions of this protein and offer aid in the development of novel cancer therapies. SIGNIFICANCE: Membrane-bound mHsp70 is required for brain tumor cell migration and invasion and therefore could be employed as a target for anticancer therapies.

Tissue-Specific Quantification of Radiation-Induced Cervical Fibrosis and Correlation with Cervical Range of Motion.

Background: Cervical fibrosis (CF) as a late consequence in patients after radiotherapy significantly impacts the long-term symptoms, functionality, and quality of life of these cancer patients due to a hardening process of different histological tissues. Modern Shear Wave Ultrasound Elastography now enables a differentiated analysis of the changes in various tissue types. In this study, tissue-specific changes in CF induced by radiation therapy in head and neck (ENT) cancer patients were quantified and correlated with cervical range of motion (CROM). Materials and Methods: 16 patients after radiation of the cervical lymphatic drainage were selected as the observation group (OG). Further, 16 people without radiation in the head and neck region were matched by gender, age, and BMI as the control group (CG). Stiffness measurements in kilopascal (kPa; 1 Pa = 1 N m-2) were performed using shear wave elastography (SWE) to assess the elasticity of muscle, fascia, and subcutaneous tissue within and surrounding the sternocleidomastoid muscle (SCM). Specific parameters of the OG were compared to the CG and correlated with functional parameters and quality of life (QoL). Results: The OG exhibited significantly higher stiffness values (Emean, Emax, Emin) across all tissue types than the CG, suggesting a tangible effect of radiation therapy on tissue stiffness. Muscle compartment analysis revealed the most significant stiffness differences. Thickness measurements indicated changes in the muscle and skin but not in the subcutaneous tissue. CROM measurements within the OG fell within normal ranges, suggesting a possible homogenizing effect of radiation treatment on CROM variability. Strong correlations were observed between age and specific stiffness measures, particularly in the OG group, indicating a broader impact of aging or radiation therapy on physiological measures. Significant correlations between tissue stiffness and CROM were found. Conclusion: CF after radiotherapy occurs primarily in the muscle tissue and its fascia, with the hardening being about twice as pronounced as in the average population and becoming more pronounced with increasing age and correlates with CROM.

Tumor Dormancy and Reactivation: The Role of Heat Shock Proteins.

Tumors are a heterogeneous group of cell masses originating in various organs or tissues. The cellular composition of the tumor cell mass interacts in an intricate manner, influenced by humoral, genetic, molecular, and tumor microenvironment cues that dictate tumor growth or suppression. As a result, tumors undergo a period of a dormant state before their clinically discernible stage, which surpasses the clinical dormancy threshold. Moreover, as a genetically imprinted strategy, early-seeder cells, a distinct population of tumor cells, break off to dock nearby or extravasate into blood vessels to secondary tissues, where they form disseminated solitary dormant tumor cells with reversible capacity. Among the various mechanisms underlying the dormant tumor mass and dormant tumor cell formation, heat shock proteins (HSPs) might play one of the most important roles in how the dormancy program plays out. It is known that numerous aberrant cellular processes, such as malignant transformation, cancer cell stemness, tumor invasion, metastasis, angiogenesis, and signaling pathway maintenance, are influenced by the HSPs. An accumulating body of knowledge suggests that HSPs may be involved in the angiogenic switch, immune editing, and extracellular matrix (ECM) remodeling cascades, crucial genetically imprinted strategies important to the tumor dormancy initiation and dormancy maintenance program. In this review, we highlight the biological events that orchestrate the dormancy state and the body of work that has been conducted on the dynamics of HSPs in a tumor mass, as well as tumor cell dormancy and reactivation. Additionally, we propose a conceptual framework that could possibly underlie dormant tumor reactivation in metastatic relapse.

Liquid Biopsy in Whole Blood for Identification of Gene Expression Patterns (mRNA and miRNA) Associated with Recurrence of Glioblastoma WHO CNS Grade 4.

GBM WHO CNS Grade 4 represents a major challenge for oncology due to its aggressive behavior. Conventional imaging has restrictions in detecting tumor recurrence. This prospective study aims to identify gene-based biomarkers in whole blood instead of isolating exosomes for the early detection of tumor recurrence. Blood samples (n = 33) were collected from seven GBM patients at time points before and after surgery as well as upon tumor recurrence. Four tumor tissue samples were assessed in parallel. Next-generation sequencing (NGS), including mRNA-seq and small RNA-seq, was used to analyze gene expression profiles in blood samples and tumor tissues. A novel filtering pipeline was invented to narrow down potential candidate genes. In total, between 6-93 mRNA and 1-19 small RNA candidates could be identified among the seven patients. The overlap of genes between the patients was minimal, indicating significant inter-individual variance among GBM patients. In summary, this prospective study supports the applicability of gene expression measurements in whole blood for the detection of tumor recurrence. It might provide an alternative to the challenging workflow of liquid biopsy after laborious exosome isolation from whole blood.

Resolving spatial response heterogeneity in glioblastoma.

PURPOSE: Spatial intratumoral heterogeneity poses a significant challenge for accurate response assessment in glioblastoma. Multimodal imaging coupled with advanced image analysis has the potential to unravel this response heterogeneity. METHODS: Based on automated tumor segmentation and longitudinal registration with follow-up imaging, we categorized contrast-enhancing voxels of 61 patients with suspected recurrence of glioblastoma into either true tumor progression (TP) or pseudoprogression (PsP). To allow the unbiased analysis of semantically related image regions, adjacent voxels with similar values of cerebral blood volume (CBV), FET-PET, and contrast-enhanced T1w were automatically grouped into supervoxels. We then extracted first-order statistics as well as texture features from each supervoxel. With these features, a Random Forest classifier was trained and validated employing a 10-fold cross-validation scheme. For model evaluation, the area under the receiver operating curve, as well as classification performance metrics were calculated. RESULTS: Our image analysis pipeline enabled reliable spatial assessment of tumor response. The predictive model reached an accuracy of 80.0% and a macro-weighted AUC of 0.875, which takes class imbalance into account, in the hold-out samples from cross-validation on supervoxel level. Analysis of feature importances confirmed the significant role of FET-PET-derived features. Accordingly, TP- and PsP-labeled supervoxels differed significantly in their 10th and 90th percentile, as well as the median of tumor-to-background normalized FET-PET. However, CBV- and T1c-related features also relevantly contributed to the model's performance. CONCLUSION: Disentangling the intratumoral heterogeneity in glioblastoma holds immense promise for advancing precise local response evaluation and thereby also informing more personalized and localized treatment strategies in the future.

A survey of cancer patients' interest in undertaking exercise to promote relaxation during radiotherapy for breast cancer and metastatic cancer.

BACKGROUND: Approximately 25-50% of patients undergoing radiotherapy (RT) experience psychological distress and anxiety, which can detrimentally affect both their quality of life and treatment outcomes. While previous research has demonstrated that relaxation exercises can enhance the tolerability of RT and alleviate associated stress and anxiety, the specific needs for such therapies in radiation oncology remain under-explored. This study aims to investigate the demand for and preferences toward relaxation exercises among radiotherapy patients, addressing a critical gap in patient-centered care. METHODS: A prospective pseudonymized survey study using a one-time paper-based questionnaire was conducted from 2022 to 2023 among patients undergoing curative-intent RT for breast cancer or patients undergoing palliative RT for bone metastases. Patients were asked in a 11-item questionnaire about their anxiety, pre-existing practice of relaxation exercises/interventions, their interest in relaxation exercises, and preferences on the type and format of instruction. Data were analyzed descriptively. RESULTS: 100 patients (74 female and 26 male) responded, of whom 68 received curative-intent adjuvant RT and 32 palliative RT. Median age was 62 years. 78% of patients indicated a desire to be actively involved in their radiotherapy, but only 27% had used relaxation exercises prior to RT. 44.8% of both curatively and palliatively treated patients who wanted to be actively involved in their therapy desired to learn how to best relax. 56.4% of respondents were willing to spend extra time learning offered exercises. CONCLUSION: The survey indicates that patients undergoing RT, both for curative or palliative intent, desire relaxation exercises to relieve stress and anxiety from RT. It is therefore important to assess the need for relaxation interventions in individual patients and to develop suitable programs or collaborate with other healthcare professionals to meet these needs.

Quantitative Assessment of Tumor Contact with Neurogenic Zones and Its Effects on Survival: Insights beyond Traditional Predictors.

So far, the cellular origin of glioblastoma (GBM) needs to be determined, with prevalent theories suggesting emergence from transformed endogenous stem cells. Adult neurogenesis primarily occurs in two brain regions: the subventricular zone (SVZ) and the subgranular zone (SGZ) of the hippocampal dentate gyrus. Whether the proximity of GBM to these neurogenic niches affects patient outcome remains uncertain. Previous studies often rely on subjective assessments, limiting the reliability of those results. In this study, we assessed the impact of GBM's relationship with the cortex, SVZ and SGZ on clinical variables using fully automated segmentation methods. In 177 glioblastoma patients, we calculated optimal cutpoints of minimal distances to the SVZ and SGZ to distinguish poor from favorable survival. The impact of tumor contact with neurogenic zones on clinical parameters, such as overall survival, multifocality, MGMT promotor methylation, Ki-67 and KPS score was also examined by multivariable regression analysis, chi-square test and Mann-Whitney-U. The analysis confirmed shorter survival in tumors contacting the SVZ with an optimal cutpoint of 14 mm distance to the SVZ, separating poor from more favorable survival. In contrast, tumor contact with the SGZ did not negatively affect survival. We did not find significant correlations with multifocality or MGMT promotor methylation in tumors contacting the SVZ, as previous studies discussed. These findings suggest that the spatial relationship between GBM and neurogenic niches needs to be assessed differently. Objective measurements disprove prior assumptions, warranting further research on this topic.

Radiomics-based prediction of local control in patients with brain metastases following postoperative stereotactic radiotherapy.

BACKGROUND: Surgical resection is the standard of care for patients with large or symptomatic brain metastases (BMs). Despite improved local control after adjuvant stereotactic radiotherapy, the risk of local failure (LF) persists. Therefore, we aimed to develop and externally validate a pre-therapeutic radiomics-based prediction tool to identify patients at high LF risk. METHODS: Data were collected from A Multicenter Analysis of Stereotactic Radiotherapy to the Resection Cavity of BMs (AURORA) retrospective study (training cohort: 253 patients from 2 centers; external test cohort: 99 patients from 5 centers). Radiomic features were extracted from the contrast-enhancing BM (T1-CE MRI sequence) and the surrounding edema (T2-FLAIR sequence). Different combinations of radiomic and clinical features were compared. The final models were trained on the entire training cohort with the best parameter set previously determined by internal 5-fold cross-validation and tested on the external test set. RESULTS: The best performance in the external test was achieved by an elastic net regression model trained with a combination of radiomic and clinical features with a concordance index (CI) of 0.77, outperforming any clinical model (best CI: 0.70). The model effectively stratified patients by LF risk in a Kaplan-Meier analysis (P < .001) and demonstrated an incremental net clinical benefit. At 24 months, we found LF in 9% and 74% of the low and high-risk groups, respectively. CONCLUSIONS: A combination of clinical and radiomic features predicted freedom from LF better than any clinical feature set alone. Patients at high risk for LF may benefit from stricter follow-up routines or intensified therapy.

Development and benchmarking of a Deep Learning-based MRI-guided gross tumor segmentation algorithm for Radiomics analyses in extremity soft tissue sarcomas.

BACKGROUND: Volume of interest (VOI) segmentation is a crucial step for Radiomics analyses and radiotherapy (RT) treatment planning. Because it can be time-consuming and subject to inter-observer variability, we developed and tested a Deep Learning-based automatic segmentation (DLBAS) algorithm to reproducibly predict the primary gross tumor as VOI for Radiomics analyses in extremity soft tissue sarcomas (STS). METHODS: A DLBAS algorithm was trained on a cohort of 157 patients and externally tested on an independent cohort of 87 patients using contrast-enhanced MRI. Manual tumor delineations by a radiation oncologist served as ground truths (GTs). A benchmark study with 20 cases from the test cohort compared the DLBAS predictions against manual VOI segmentations of two residents (ERs) and clinical delineations of two radiation oncologists (ROs). The ROs rated DLBAS predictions regarding their direct applicability. RESULTS: The DLBAS achieved a median dice similarity coefficient (DSC) of 0.88 against the GTs in the entire test cohort (interquartile range (IQR): 0.11) and a median DSC of 0.89 (IQR 0.07) and 0.82 (IQR 0.10) in comparison to ERs and ROs, respectively. Radiomics feature stability was high with a median intraclass correlation coefficient of 0.97, 0.95 and 0.94 for GTs, ERs, and ROs, respectively. DLBAS predictions were deemed clinically suitable by the two ROs in 35% and 20% of cases, respectively. CONCLUSION: The results demonstrate that the DLBAS algorithm provides reproducible VOI predictions for radiomics feature extraction. Variability remains regarding direct clinical applicability of predictions for RT treatment planning.

Carbon ion radiotherapy of hepatocellular carcinoma provides excellent local control: The prospective phase I PROMETHEUS trial.

Background & Aims: Inoperable hepatocellular carcinoma (HCC) can be treated by stereotactic body radiotherapy. However, carbon ion radiotherapy (CIRT) is more effective for sparing non-tumorous liver. High linear energy transfer could promote therapy efficacy. Japanese and Chinese studies on hypofractionated CIRT have yielded excellent results. Because of different radiobiological models and the different etiological spectrum of HCC, applicability of these results to European cohorts and centers remains questionable. The aim of this prospective study was to assess safety and efficacy and to determine the optimal dose of CIRT with active raster scanning based on the local effect model (LEM) I. Methods: CIRT was performed every other day in four fractions with relative biological effectiveness (RBE)-weighted fraction doses of 8.1-10.5 Gy (total doses 32.4-42.0 Gy [RBE]). Dose escalation was performed in five dose levels with at least three patients each. The primary endpoint was acute toxicity after 4 weeks. Results: Twenty patients received CIRT (median age 74.7 years, n = 16 with liver cirrhosis, Child-Pugh scores [CP] A5 [n = 10], A6 [n = 4], B8 [n = 1], and B9 [n = 1]). Median follow up was 23 months. No dose-limiting toxicities and no toxicities exceeding grade II occurred, except one grade III gamma-glutamyltransferase elevation 12 months after CIRT, synchronous to out-of-field hepatic progression. During 12 months after CIRT, no CP elevation occurred. The highest dose level could be applied safely. No local recurrence developed during follow up. The objective response rate was 80%. Median overall survival was 30.8 months (1/2/3 years: 75%/64%/22%). Median progression-free survival was 20.9 months (1/2/3 years: 59%/43%/43%). Intrahepatic progression outside of the CIRT target volume was the most frequent pattern of progression. Conclusions: CIRT of HCC yields excellent local control without dose-limiting toxicity. Impact and implications: To date, safety and efficacy of carbon ion radiotherapy for hepatocellular carcinoma have only been evaluated prospectively in Japanese and Chinese studies. The optimal dose and fractionation when using the local effect model for radiotherapy planning are unknown. The results are of particular interest for European and American particle therapy centers, but also of relevance for all specialists involved in the treatment and care of patients with hepatocellular carcinoma, as we present the first prospective data on carbon ion radiotherapy in hepatocellular carcinoma outside of Asia. The excellent local control should encourage further use of carbon ion radiotherapy for hepatocellular carcinoma and design of randomized controlled trials. Clinical Trials Registration: The study is registered at ClinicalTrials.gov (NCT01167374).

Single brain metastases - prognostic factors and impact of residual tumor burden on overall survival.

Background: Brain metastases (BM) are a common and challenging issue, with their incidence on the rise due to advancements in systemic therapies and increased patient survival. Most patients present with single BM, some of them without any further extracranial metastasis (i.e., solitary BM). The significance of postoperative intracranial tumor volume in the treatment of singular and solitary BM is still debated. Objective: This study aimed to determine the impact of resection and postoperative tumor burden on overall survival (OS) in patients with single BM. Methods: Patients with surgically treated single BM between 04/2007-01/2020 were retrospectively included. Residual tumor burden (RTB) was determined by manual segmentation of early postoperative brain MRI (72 h). Survival analyses were performed using Kaplan-Meier estimates for univariate analysis and Cox regression proportional hazards model for multivariate analysis, using preoperative Karnofsky performance status scale (KPSS), age, sex, RTB, incomplete resection and singular/solitary BM as covariates. Results: 340 patients were included, median age 64 years (54-71). 119 patients (35%) had solitary BM, 221 (65%) singular BM. Complete resection (RTB=0) was achieved in 73%, median preoperative tumor burden was 11.2 cm3 (5-25), and RTB 0 cm3 (0-0.2). Median OS of patients with singular BM was 13 months (4-33) vs 20 months (5-92) for solitary BM; p=0.062. Multivariate analysis revealed singular BM as independent risk factor for poorer OS: HR 1.840 (1.202-2.817), p=0.005. Complete vs. incomplete resection showed no significant OS difference (13 vs. 13 months, p=0.737). When focusing on solitary BM, complete resection led to a longer OS than incomplete resection (21 vs. 8 months), without statistical significance(p=0.250). Achieving RTB=0 resulted in higher OS for patients with solitary BM compared to singular BM (21 vs. 12 months, p=0.027). Patients who received postoperative radiotherapy (RT) had significantly longer OS compared to those without it (14 vs. 4 months, p<0.001), with favorable OS in those receiving stereotactic radiosurgery (SRS) (15 months (3-42), p<0.001) or hypofractionated stereotactic radiotherapy (HSRT). Conclusion: When complete intracranial tumor resection RTB=0 is achieved, patients with solitary BM have a favorable outcome compared to singular BM. Singular BM was confirmed as independent risk factor. There is a strong presumption that complete resection leads to an improved oncological prognosis. Patients with solitary BM tend to benefit with a favorable outcome following complete resection. Hence, surgical resection should be considered as a treatment option for patients presenting with either no or minimal extracranial disease. Furthermore, the highly favorable impact of postoperative RT on OS was demonstrated and confirmed, especially with SRS or HSRT.

Detecting Metastatic Patterns of Oligometastatic Breast Cancer: A Comparative Analysis of 18F-FDG PET/CT and Conventional CT Imaging.

Metastasis-directed therapy has the potential to improve progression-free and overall survival in oligometastatic disease (OMD). For breast cancer, however, randomized trials have failed so far to confirm this finding. Because the concept of metastasis-directed therapy in OMD is highly dependent on the accuracy of the imaging modality, we aimed to assess the impact of 18F-FDG PET/CT on the definition of OMD in breast cancer patients. Methods: Eighty patients with a total of 150 18F-FDG PET/CT images (between October 2006 and January 2022) were enrolled in this retrospective study at the Technical University of Munich. The inclusion criteria were OMD, defined as 1-5 distant metastases, at the time of 18F-FDG PET/CT. For the current study, we systemically compared the metastatic pattern on 18F-FDG PET/CT with conventional CT. Results: At the time of 18F-FDG PET/CT, 21.3% of patients (n = 32) had a first-time diagnosis of metastatic disease, 40.7% (n = 61) had a previous history of OMD, and 38% (n = 57) had a previous history of polymetastatic disease. In 45.3% of cases, the imaging modality (18F-FDG PET/CT vs. conventional CT) had an impact on the assessment of whether OMD was present. An identical metastatic pattern was observed in only 32% of cases.18F-FDG PET/CT detected additional metastases in 33.3% of cases, mostly in the nonregional lymph node system. Conclusion: The use of 18F-FDG PET/CT had a substantial impact on the definition of OMD and detection of metastatic pattern in breast cancer. Our results emphasize the importance of establishing a standardized definition for imaging modalities in future trials and clinical practices related to metastasis-directed therapy in breast cancer patients.

Toward image-based personalization of glioblastoma therapy: A clinical and biological validation study of a novel, deep learning-driven tumor growth model.

Background: The diffuse growth pattern of glioblastoma is one of the main challenges for accurate treatment. Computational tumor growth modeling has emerged as a promising tool to guide personalized therapy. Here, we performed clinical and biological validation of a novel growth model, aiming to close the gap between the experimental state and clinical implementation. Methods: One hundred and twenty-four patients from The Cancer Genome Archive (TCGA) and 397 patients from the UCSF Glioma Dataset were assessed for significant correlations between clinical data, genetic pathway activation maps (generated with PARADIGM; TCGA only), and infiltration (Dw) as well as proliferation (ρ) parameters stemming from a Fisher-Kolmogorov growth model. To further evaluate clinical potential, we performed the same growth modeling on preoperative magnetic resonance imaging data from 30 patients of our institution and compared model-derived tumor volume and recurrence coverage with standard radiotherapy plans. Results: The parameter ratio Dw/ρ (P < .05 in TCGA) as well as the simulated tumor volume (P < .05 in TCGA/UCSF) were significantly inversely correlated with overall survival. Interestingly, we found a significant correlation between 11 proliferation pathways and the estimated proliferation parameter. Depending on the cutoff value for tumor cell density, we observed a significant improvement in recurrence coverage without significantly increased radiation volume utilizing model-derived target volumes instead of standard radiation plans. Conclusions: Identifying a significant correlation between computed growth parameters and clinical and biological data, we highlight the potential of tumor growth modeling for individualized therapy of glioblastoma. This might improve the accuracy of radiation planning in the near future.

Influence of intestinal microbial metabolites on the abscopal effect after radiation therapy combined with immune checkpoint inhibitors.

Background: Most clinical studies failed to elicit a strong antitumor immune response and subsequent systemic tumor regression after radiation therapy (RT), even in combination with the immune checkpoint inhibitors (ICI) anti-CTLA4 or anti-PD1. Mechanistically, type I interferon (IFN-I) activation is essential for the development of such abscopal effects (AE); however, mechanisms driving or limiting IFN-I activation are ill defined. Groundbreaking discoveries have shown that antibiotics (ABx) can affect oncological outcomes and that microbiota-derived metabolites can modulate systemic antitumor immunity. Recent studies have demonstrated that the bacterial metabolites desaminotyrosine (DAT) and indole-3-carboxaldehyde (ICA) can enhance IFN-I activation in models of inflammatory diseases. Materials and Methods: The subcutaneous bilateral MC38 tumor model is a widely used experimental tool to study the AE in mice. We applied it to explore the influence of broad-spectrum ABx, DAT and ICA on the AE after radioimmunotherapy (RIT). We performed 1x8 Gy of the primary tumor ± anti-CTLA4 or anti-PD1, and ± daily oral application of ABx or metabolites. Result: Combinatory ABx had neither a significant effect on tumor growth of the irradiated tumor nor on tumor progression of the abscopal tumor after RIT with anti-CTLA4. Furthermore, DAT and ICA did not significantly impact on the AE after RIT with anti-CTLA4 or anti-PD1. Surprisingly, ICA even appears to reduce outcomes after RIT with anti-CTLA4. Conclusion: We did not find a significant impact of combinatory ABx on the AE. Experimental application of the IFN-I-inducing metabolites DAT or ICA did not boost the AE after combined RIT. Additional studies are important to further investigate whether the intestinal microbiota or specific microbiota-derived metabolites modulate the AE.

DEGRO guideline for personalized radiotherapy of brain metastases and leptomeningeal carcinomatosis in patients with breast cancer.

PURPOSE: The aim of this review was to evaluate the existing evidence for radiotherapy for brain metastases in breast cancer patients and provide recommendations for the use of radiotherapy for brain metastases and leptomeningeal carcinomatosis. MATERIALS AND METHODS: For the current review, a PubMed search was conducted including articles from 01/1985 to 05/2023. The search was performed using the following terms: (brain metastases OR leptomeningeal carcinomatosis) AND (breast cancer OR breast) AND (radiotherapy OR ablative radiotherapy OR radiosurgery OR stereotactic OR radiation). CONCLUSION AND RECOMMENDATIONS: Despite the fact that the biological subtype of breast cancer influences both the occurrence and relapse patterns of breast cancer brain metastases (BCBM), for most scenarios, no specific recommendations regarding radiotherapy can be made based on the existing evidence. For a limited number of BCBM (1-4), stereotactic radiosurgery (SRS) or fractionated stereotactic radiotherapy (SRT) is generally recommended irrespective of molecular subtype and concurrent/planned systemic therapy. In patients with 5-10 oligo-brain metastases, these techniques can also be conditionally recommended. For multiple, especially symptomatic BCBM, whole-brain radiotherapy (WBRT), if possible with hippocampal sparing, is recommended. In cases of multiple asymptomatic BCBM (≥ 5), if SRS/SRT is not feasible or in disseminated brain metastases (> 10), postponing WBRT with early reassessment and reevaluation of local treatment options (8-12 weeks) may be discussed if a HER2/Neu-targeting systemic therapy with significant response rates in the central nervous system (CNS) is being used. In symptomatic leptomeningeal carcinomatosis, local radiotherapy (WBRT or local spinal irradiation) should be performed in addition to systemic therapy. In patients with disseminated leptomeningeal carcinomatosis in good clinical condition and with only limited or stable extra-CNS disease, craniospinal irradiation (CSI) may be considered. Data regarding the toxicity of combining systemic therapies with cranial and spinal radiotherapy are sparse. Therefore, no clear recommendations can be given, and each case should be discussed individually in an interdisciplinary setting.