Proposal for the delineation of neoadjuvant target volumes in oesophageal cancer

PURPOSE: To define instructions for delineation of target volumes in the neoadjuvant setting in oesophageal cancer. MATERIALS AND METHODS: Radiation oncologists of five European centres participated in the following consensus process: [1] revision of published (MEDLINE) and national/institutional delineation guidelines; [2] first delineation round of five cases (patient 1-5) according to national/institutional guidelines; [3] consensus meeting to discuss the results of step 1 and 2, followed by a target volume delineation proposal; [4] circulation of proposed instructions for target volume delineation and atlas for feedback; [5] second delineation round of five new cases (patient 6-10) to peer review and validate (two additional centres) the agreed delineation guidelines and atlas; [6] final consensus on the delineation guidelines depicted in an atlas. Target volumes of the delineation rounds were compared between centres by Dice similarity coefficient (DSC) and maximum/mean undirected Hausdorff distances (Hmax/Hmean). RESULTS: In the first delineation round, the consistency between centres was moderate (CTVtotal: DSC = 0.59-0.88; Hmean = 0.2-0.4 cm). Delineations in the second round were much more consistent. Lowest variability was obtained between centres participating in the consensus meeting (CTVtotal: DSC: p < 0.050 between rounds for patients 6/7/8/10; Hmean: p < 0.050 for patients 7/8/10), compared to validation centres (CTVtotal: DSC: p < 0.050 between validation and consensus meeting centres for patients 6/7/8; Hmean: p < 0.050 for patients 7/10). A proposal for delineation of target volumes and an atlas were generated. CONCLUSION: We proposed instructions for target volume delineation and an atlas for the neoadjuvant radiation treatment in oesophageal cancer. These will enable a more uniform delineation of patients in clinical practice and clinical trials

Combined tumor plus nontumor interim FDG‐PET parameters are prognostic for response to chemoradiation in squamous cell esophageal cancer

We have investigated the prognostic value of two novel interim F-18-fluorodeoxyglucose positron emission tomography (FDG-PET) parameters in patients undergoing chemoradiation (CRT) for esophageal squamous cell carcinoma (ESCC): one tumor parameter (maximal standardized uptake ratio rSUR) and one normal tissue parameter (change of FDG uptake within irradiated nontumor-affected esophagus increment SUVNTO). PET data of 134 European and Chinese patients were analyzed. Parameter establishment was based on 36 patients undergoing preoperative CRT plus surgery, validation was performed in 98 patients receiving definitive CRT. Patients received PET imaging prior and during fourth week of CRT. Clinical parameters, baseline PET parameters, and interim PET parameters (rSUR and increment SUVNTO) were analyzed and compared to event-free survival (EFS), overall survival (OS), loco-regional control (LRC) and freedom from distant metastases (FFDM). Combining rSUR and increment SUVNTO revealed a strong prognostic impact on EFS, OS, LRC and FFDM in patients undergoing preoperative CRT. In the definitive CRT cohort, univariate analysis with respect to EFS revealed several staging plus both previously established interim PET parameters as significant prognostic factors. Multivariate analyses revealed only rSUR and increment SUVNTO as independent prognostic factors (p = 0.003, p = 0.008). Combination of these parameters with the cutoff established in preoperative CRT revealed excellent discrimination of patients with a long or short EFS (73% vs. 17% at 2 years, respectively) and significantly discriminated all other endpoints (OS, p < 0.001; LRC, p < 0.001; FFDM, p = 0.02), even in subgroups. Combined use of interim FDG-PET derived parameters increment SUVNTO and rSUR seems to have predictive potential, allowing to select responders for definitive CRT and omission of surgery

Orthotopic Glioblastoma Models for Evaluation of the Clinical Target Volume Concept

In times of high-precision radiotherapy, the accurate and precise definition of the primary tumor localization and its microscopic spread is of enormous importance. In glioblastoma, the microscopic tumor extension is uncertain and, therefore, population-based margins for Clinical Target Volume (CTV) definition are clinically used, which could either be too small&mdash;leading to increased risk of loco-regional recurrences&mdash;or too large, thus, enhancing the probability of normal tissue toxicity. Therefore, the aim of this project is to investigate an individualized definition of the CTV in preclinical glioblastoma models based on specific biological tumor characteristics. The microscopic tumor extensions of two different orthotopic brain tumor models (U87MG_mCherry; G7_mCherry) were evaluated before and during fractionated radiotherapy and correlated with corresponding histological data. Representative tumor slices were analyzed using Matrix-Assisted Laser Desorption/Ionization (MALDI) and stained for putative stem-like cell markers as well as invasion markers. The edges of the tumor are clearly shown by the MALDI segmentation via unsupervised clustering of mass spectra and are consistent with the histologically defined border in H&amp;E staining in both models. MALDI component analysis identified specific peaks as potential markers for normal brain tissue (e.g., 1339 m/z), whereas other peaks demarcated the tumors very well (e.g., 1562 m/z for U87MG_mCherry) irrespective of treatment. MMP14 staining revealed only a few positive cells, mainly in the tumor border, which could reflect the invasive front in both models. The results of this study indicate that MALDI information correlates with microscopic tumor spread in glioblastoma models. Therefore, an individualized CTV definition based on biological tumor characteristics seems possible, whereby the visualization of tumor volume and protein heterogeneity can be potentially used to define radiotherapy-sensitive and resistant areas

A convolutional neural network for fully automated blood SUV determination to facilitate SUR computation in oncological FDG-PET

Purpose!#!The standardized uptake value (SUV) is widely used for quantitative evaluation in oncological FDG-PET but has well-known shortcomings as a measure of the tumor's glucose consumption. The standard uptake ratio (SUR) of tumor SUV and arterial blood SUV (BSUV) possesses an increased prognostic value but requires image-based BSUV determination, typically in the aortic lumen. However, accurate manual ROI delineation requires care and imposes an additional workload, which makes the SUR approach less attractive for clinical routine. The goal of the present work was the development of a fully automated method for BSUV determination in whole-body PET/CT.!##!Methods!#!Automatic delineation of the aortic lumen was performed with a convolutional neural network (CNN), using the U-Net architecture. A total of 946 FDG PET/CT scans from several sites were used for network training (N = 366) and testing (N = 580). For all scans, the aortic lumen was manually delineated, avoiding areas affected by motion-induced attenuation artifacts or potential spillover from adjacent FDG-avid regions. Performance of the network was assessed using the fractional deviations of automatically and manually derived BSUVs in the test data.!##!Results!#!The trained U-Net yields BSUVs in close agreement with those obtained from manual delineation. Comparison of manually and automatically derived BSUVs shows excellent concordance: the mean relative BSUV difference was (mean ± SD) = (- 0.5 ± 2.2)% with a 95% confidence interval of [- 5.1,3.8]% and a total range of [- 10.0, 12.0]%. For four test cases, the derived ROIs were unusable (&amp;lt; 1 ml).!##!Conclusion!#!CNNs are capable of performing robust automatic image-based BSUV determination. Integrating automatic BSUV derivation into PET data processing workflows will significantly facilitate SUR computation without increasing the workload in the clinical setting

Proton radiography for inline treatment planning and positioning verification of small animals

<p><b>Introduction:</b> As proton therapy becomes increasingly well established, there is a need for high-quality clinically relevant <i>in vivo</i> data to gain better insight into the radiobiological effects of proton irradiation on both healthy and tumor tissue. This requires the development of easily applicable setups that allow for efficient, fractionated, image-guided proton irradiation of small animals, the most widely used pre-clinical model.</p> <p><b>Material and methods:</b> Here, a method is proposed to perform dual-energy proton radiography for inline positioning verification and treatment planning. Dual-energy proton radiography exploits the differential enhancement of object features in two successively measured two-dimensional (2D) dose distributions at two different proton energies. The two raw images show structures that are dominated by energy absorption (<i>absorption mode</i>) or scattering (<i>scattering mode</i>) of protons in the object, respectively. Data post-processing allowed for the separation of both signal contributions in the respective images. The images were evaluated regarding recognizable object details and feasibility of rigid registration to acquired planar X-ray scans.</p> <p><b>Results:</b> Robust, automated rigid registration of proton radiography and planar X-ray images in scattering mode could be reliably achieved with the animal bedding unit used as registration landmark. Distinguishable external and internal features of the imaged mouse included the outer body contour, the skull with substructures, the lung, abdominal structures and the hind legs. Image analysis based on the combined information of both imaging modes allowed image enhancement and calculation of 2D water-equivalent path length (WEPL) maps of the object along the beam direction.</p> <p><b>Discussion:</b> Fractionated irradiation of exposed target volumes (e.g., subcutaneous tumor model or brain) can be realized with the suggested method being used for daily positioning and range determination. Robust registration of X-ray and proton radiography images allows for the irradiation of tumor entities that require conventional computed tomography (CT)-based planning, such as orthotopic lung or brain tumors, similar to conventional patient treatment.</p

Combined Systemic Drug Treatment with Proton Therapy: Investigations on Patient-Derived Organoids

To optimize neoadjuvant radiochemotherapy of pancreatic ductal adenocarcinoma (PDAC), the value of new irradiation modalities such as proton therapy needs to be investigated in relevant preclinical models. We studied individual treatment responses to RCT using patient-derived PDAC organoids (PDO). Four PDO lines were treated with gemcitabine, 5-fluorouracile (5FU), photon and proton irradiation and combined RCT. Therapy response was subsequently measured via viability assays. In addition, treatment-naive PDOs were characterized via whole exome sequencing and tumorigenicity was investigated in NMRI Foxn1nu/nu mice. We found a mutational pattern containing common mutations associated with PDAC within the PDOs. Although we could unravel potential complications of the viability assay for PDOs in radiobiology, distinct synergistic effects of gemcitabine and 5FU with proton irradiation were observed in two PDO lines that may lead to further mechanistical studies. We could demonstrate that PDOs are a powerful tool for translational proton radiation research