Ex vivo radiation sensitivity assessment for individual head and neck cancer patients using deep learning-based automated nuclei and DNA damage foci detection

Introduction

Tumor biopsy tissue response to ex vivo irradiation is potentially an interesting biomarker for in vivo tumor response, therefore, for treatment personalization. Tumor response ex vivo can be characterized by DNA damage response, expressed by the large-scale presence of DNA damage foci in tumor nuclei. Currently, characterizing tumor nuclei and DNA damage foci is a manual process that takes hours per patient and is subjective to inter-observer variability, which is not feasible in for clinical decision making. Therefore, our goal was to develop a method to automatically segment nuclei and DNA damage foci in tumor tissue samples treated with radiation ex vivo to characterize the DNA damage response, as potential biomarker for in vivo radio-sensitivity.

Methods

Oral cavity tumor tissue of 21 patients was irradiated ex vivo (5 or 0 Gy), fixated 2 h post-radiation, and used to develop our method for automated nuclei and 53BP1 foci segmentation. The segmentation model used both deep learning and conventional image-analysis techniques. The training (22 %), validation (22 %), and test set (56 %) consisted of thousands of manually segmented nuclei and foci. The segmentations and number of foci per nucleus in the test set were compared to their ground truths.

Results

The automatic nuclei and foci segmentations were highly accurate (Dice = 0.901 and Dice = 0.749, respectively). An excellent correlation (R2 = 0.802) was observed for the foci per nucleus that outperformed reported inter-observation variation. The analysis took ∼ 8 s per image.

Conclusion

This model can replace manual foci analysis for ex vivo irradiation of head-and-neck squamous cell carcinoma tissue, reduces the image-analysis time from hours to minutes, avoids the problem of inter-observer variability, enables assessment of multiple images or conditions, and provides additional information about the foci size. Thereby, it allows for reliable and rapid ex vivo radio-sensitivity assessment, as potential biomarker for response in vivo and treatment personalization.

Interaction of therapeutic12C ions with bone-like targets: physical characterization and dosimetric effect at material interfaces

Carbon therapy is a promising treatment option for cancer. The physical and biological properties of carbon ions can theoretically allow for the delivery of curative doses to the tumor, while simultaneously limiting risks of toxicity to adjacent healthy structures. The treatment effectiveness can be further improved by decreasing the uncertainties stemming from several sources, including the modeling of tissue heterogeneity. Current treatment plans employ density-based conversion methods to translate patient-specific anatomy into a water system, where dose distribution is calculated. This approach neglects differences in nuclear interactions stemming from the elemental composition of each tissue. In this work, we investigated the interaction of therapeutic carbon ions with bone-like materials. The study concentrated on nuclear interactions and included attenuation curves of 200 and 400 AMeV beams in different types of bones, as well as kinetic energy spectra of all charged fragments produced up to 29 degrees from the beam direction. The comparison between measurements and calculations of the treatment planning system TRiP98 indicated that bone tissue causes less fragmentation of carbon ions than water. Overall, hydrogen and helium particles were found to be the most abundant species, while heavier fragments were mostly detected within 5 degrees from the beam direction. We also investigated how the presence of a soft tissue-bone interface could affect the depth-dose profile. The results revealed a dose spike in the transition region, that extended from the entry channel to the target volume. The findings of this work indicated that the tissue-to-water conversion method based only on density considerations can result in dose inaccuracies. Tissue heterogeneity regions containing bones can potentially produce dose spikes, whose magnitude will depend on the patient anatomy. Dose uncertainties can be decreased by modeling nuclear interactions directly in bones, without applying the tissue-to-water conversion.

Microdosimetric measurements as a tool to assess potential in-field and out-of-field toxicity regions in proton therapy

Relative biological effectiveness (RBE) variations are thought to be one of the primary causes of unexpected normal-tissue toxicities during tumor treatments with charged particles. Unlike carbon therapy, where treatment planning is optimized on the basis of the RBE-weighted dose, a constant RBE value of 1.1 is currently used in proton therapy. Assuming a uniform value can lead to under- or over-dosage, not just to the tumor but also to surrounding normal tissue. RBE changes have been linked with dose/fraction, the biological endpoint and beam properties. Understanding radiation quality and the associated RBE can improve the prediction of normal-tissue toxicities. In this study, we exploited microdosimetry for characterizing radiation quality in proton therapy in-field, and off-beam at 20 (beam edge), 50 (close out-of-field) and 100 (far out-of-field) mm from the beam center. We measured the lineal energy y spectra in a water phantom irradiated with 152 MeV protons, from which beam quality as well as the physical dose could be obtained. Taking advantage of the linear quadratic model and a modified version of the microdosimetric kinetic model, the microdosimetric data were combined with radiobiological parameters (α and β) of human salivary gland tumor cells for assessing cell survival RBE and RBE-weighted dose. The results indicate that if a dose of 60 Gy is delivered to the peak, the beam edge receives up to 6 Gy while the close and far out-of-field regions receive doses on the order of 10^-3 Gy and 10^-4 Gy, respectively. The RBE estimate in-beam shows large variations, ranging from 1.0 ± 0.2 at the entrance channel to 2.51 ± 0.15 at the tail. The beam edge follows a similar trend but the RBE calculated at the Bragg peak depth is 2.27 ± 0.17, i.e. twice the RBE in-beam (1.05 ± 0.15). Out-of-field, the estimated RBE is always significantly higher than 1.1 and increases with increasing lateral distance, reaching the overall highest value of 3.4 ± 0.3 at a depth of 206 mm and a lateral distance of 10 mm. The combination of RBE and dose into the biological dose points to the beam edge and the end-of-range in-beam as the areas with the highest risk of potential toxicities.

STUDY FOR A PASSIVE SCATTERING LINE DEDICATED TO RADIOBIOLOGY EXPERIMENTS AT THE TRENTO PROTON THERAPY CENTER

The recent worldwide spread of Proton Therapy centers paves the way to new opportunities for basic and applied research related to the use of accelerated proton beams. Clinical centers make use of proton beam energies up to about 230 MeV. This represents an interesting energy range for a large spectrum of applications, including detector testing, radiation shielding and space research. Additionally, radiobiology research might benefit for a larger availability of proton beams, especially in those centers where a room dedicated to research activities also exists. Here, we describe the initial activities for the setup of a radiobiology irradiation facility at the Trento Proton Therapy Center. Data referring to the characterization of the beam in air are essential to that purpose and will be presented. A basic setup for large field irradiation will be also proposed, which is needed for the majority of in vitro and in vivo radiobiology experiments.