Multicellular dosimetric chain for molecular radiotherapy exemplified with dose simulations on 3D cell spheroids

Marker-controlled watershed with deep edge emphasis and optimized H-minima transform for automatic segmentation of densely cultivated 3D cell nuclei

BACKGROUND

The segmentation of 3D cell nuclei is essential in many tasks, such as targeted molecular radiotherapies (MRT) for metastatic tumours, toxicity screening, and the observation of proliferating cells. In recent years, one popular method for automatic segmentation of nuclei has been deep learning enhanced marker-controlled watershed transform. In this method, convolutional neural networks (CNNs) have been used to create nuclei masks and markers, and the watershed algorithm for the instance segmentation. We studied whether this method could be improved for the segmentation of densely cultivated 3D nuclei via developing multiple system configurations in which we studied the effect of edge emphasizing CNNs, and optimized H-minima transform for mask and marker generation, respectively.

RESULTS

The dataset used for training and evaluation consisted of twelve in vitro cultivated densely packed 3D human carcinoma cell spheroids imaged using a confocal microscope. With this dataset, the evaluation was performed using a cross-validation scheme. In addition, four independent datasets were used for evaluation. The datasets were resampled near isotropic for our experiments. The baseline deep learning enhanced marker-controlled watershed obtained an average of 0.69 Panoptic Quality (PQ) and 0.66 Aggregated Jaccard Index (AJI) over the twelve spheroids. Using a system configuration, which was otherwise the same but used 3D-based edge emphasizing CNNs and optimized H-minima transform, the scores increased to 0.76 and 0.77, respectively. When using the independent datasets for evaluation, the best performing system configuration was shown to outperform or equal the baseline and a set of well-known cell segmentation approaches.

CONCLUSIONS

The use of edge emphasizing U-Nets and optimized H-minima transform can improve the marker-controlled watershed transform for segmentation of densely cultivated 3D cell nuclei. A novel dataset of twelve spheroids was introduced to the public.

Advancements in the use of Auger electrons in science and medicine during the period 2015-2019

Auger electrons can be highly radiotoxic when they are used to irradiate specific molecular sites. This has spurred basic science investigations of their radiobiological effects and clinical investigations of their potential for therapy. Focused symposia on the biophysical aspects of Auger processes have been held quadrennially. This 9th International Symposium on Physical, Molecular, Cellular, and Medical Aspects of Auger Processes at Oxford University brought together scientists from many different fields to review past findings, discuss the latest studies, and plot the future work to be done. This review article examines the research in this field that was published during the years 2015-2019 which corresponds to the period since the last meeting in Japan. In addition, this article points to future work yet to be done. There have been a plethora of advancements in our understanding of Auger processes. These advancements range from basic atomic and molecular physics to new ways to implement Auger electron emitters in radiopharmaceutical therapy. The highly localized doses of radiation that are deposited within a 10 nm of the decay site make them precision tools for discovery across the physical, chemical, biological, and medical sciences.

Targeting Micrometastases: The Effect of Heterogeneous Radionuclide Distribution on Tumor Control Probability

The spatial distribution of radiopharmaceuticals that emit short-range high linear-energy-transfer electrons greatly affects the absorbed dose and their biological effectiveness. The purpose of this study was to investigate the effect of heterogeneous radionuclide distribution on tumor control probability (TCP) in a micrometastases model. Methods: Cancer cell lines; MDA-MB-468, SQ20B and 231-H2N were grown as spheroids to represent micrometastases. The intracellular distribution of a representative radiopeptide (111In-labelled epidermal growth factor, EGF) and radioimmunotherapeutic (111In-labelled Trastuzumab) was determined in cell internalization experiments. The intratumoral distribution was evaluated by microautoradiography of spheroids. γH2AX staining was performed on spheroid sections to correlate DNA damage with radionuclide distribution. Experimental surviving fractions (SFexp ) were obtained using clonogenic assays. A random closed-packed algorithm, which models the random packing behavior of cells and reflects variation in the radii of cells and nuclei, was used to simulate 3-D spheroids. Calculated survival fractions (SFcal ) were generated using an iterative modelling method based on Monte Carlo determined absorbed dose with the PENELOPE code and were compared to (SFexp ). Radiobiological parameters deduced from experimental results and MC simulations were used to predict the TCP for a 3-D spheroid model. Results: Calculated SFs were in good agreement with experimental data, particularly when an increased value for relative biological effectiveness (RBE) was applied to self-dose deposited by sources located in the nucleus and when radiobiological parameters were adjusted to account for dose protraction. Only in MDA-MB-468 spheroids treated with 111In-EGF was a TCP>0.5 achieved, indicating that for this cell type the radiopeptide would be curative when targeting micrometastases. This is attributed to the relative radiosensitivity of MDA-MB-468 cells, high nuclear uptake of the radiopeptide and uniform distribution of radioactivity throughout the spheroid. Conclusion: It is imperative to include biological endpoints when evaluating the distribution of radionuclides in models emulating micrometastatic disease. The spatial distribution of radioactivity is a clear determinant of biological effect and TCP as demonstrated in this study.