Biologically conformal treatment: biomarkers and functional imaging in radiation oncology

Proliferation and apoptosis after whole-body irradiation: longitudinal PET study in a mouse model

PURPOSE

A reliable method for regional in vivo imaging of radiation-induced cellular damage would be of great importance for the detection of therapy-induced injury to healthy tissue and the choice of adequate treatment of radiation emergency patients in both civilian and military events. This study aimed to investigate in a mouse model if positron emission tomography (PET) imaging with proliferation and apoptosis markers is potentially suitable for this purpose.

METHODS

Four groups, including twenty mice (wild-type C57BL/6) each, were whole-body irradiated with 0 Gy, 0.5 Gy, 1 Gy, and 3 Gy and examined by PET over a six-month period at defined time points. 3'-[18F]fluoro-3'-deoxythymidine ([18F]FLT) and 2-(5-[18F]fluoropentyl)-2-methyl malonic acid ([18F]ML-10) were used to visualise proliferation and apoptosis. Regional standard uptake values were compared with respect to irradiation dose over time. Histologic data and peripheral blood cell values were correlated with the PET results.

RESULTS

The hematopoietic bone marrow showed a significantly increased [18F]FLT signal at early time points after radiation exposure (day 3 and day 7). This correlated with blood parameters, especially leukocytes, and histological data. A significantly increased [18F]FLT signal also occurred in the gastrointestinal tract and thymus at early time points. An increased [18F]ML-10 signal related to irradiation doses was observed in the bone marrow on day 8, but there was a high variability of standard uptake values and no correlation with histological data.

CONCLUSION

[18F]FLT showed potential to visualise the extent, regional distribution and recovery from radiation-induced cellular damage in the bone marrow, gastrointestinal tract and thymus. The potential of [18F]FLT imaging to assess the extent of bone marrow affected by irradiation might be especially useful to predict the subsequent severity of hematopoietic impairment and to adapt the therapy of the bone marrow reserve. [18F]ML-10 PET proved to be not sensitive enough for the reliable detection of radiation induced apoptosis.

A reinforcement learning approach for finding optimal policy of adaptive radiation therapy considering uncertain tumor biological response

Recent studies have shown that a tumor's biological response to radiation varies over time and has a dynamic nature. Dynamic biological features of tumor cells underscore the importance of using fractionation and adapting the treatment plan to tumor volume changes in radiation therapy treatment. Adaptive radiation therapy (ART) is an iterative process to adjust the dose of radiation in response to potential changes during the treatment. One of the key challenges in ART is how to determine the optimal timing of adaptations corresponding to tumor response to radiation. This paper aims to develop an automated treatment planning framework incorporating the biological uncertainties to find the optimal adaptation points to achieve a more effective treatment plan. First, a dynamic tumor-response model is proposed to predict weekly tumor volume regression during the period of radiation therapy treatment based on biological factors. Second, a Reinforcement Learning (RL) framework is developed to find the optimal adaptation points for ART considering the uncertainty in biological factors with the goal of achieving maximum final tumor control while minimizing or maintaining the toxicity level of the organs at risk (OARs) per the decision-maker's preference. Third, a beamlet intensity optimization model is solved using the predicted tumor volume at each adaptation point. The performance of the proposed RT treatment planning framework is tested using a clinical non-small cell lung cancer (NSCLC) case. The results are compared with the conventional fractionation schedule (i.e., equal dose fractionation) as a reference plan. The results show that the proposed approach performed well in achieving a robust optimal ART treatment plan under high uncertainty in the biological parameters. The ART plan outperformed the reference plan by increasing the mean biological effective dose (BED) value of the tumor by 2.01%, while maintaining the OAR BED within +0.5% and reducing the variability, in terms of the interquartile range (IQR) of tumor BED, by 25%.

Cancer-associated Fibroblasts Promote Irradiated Cancer Cell Recovery Through Autophagy

Tumor relapse after radiotherapy is a significant challenge to oncologists, even after recent the advances in technologies. Here, we showed that cancer-associated fibroblasts (CAFs), a major component of cancer stromal cells, promoted irradiated cancer cell recovery and tumor relapse after radiotherapy. We provided evidence that CAFs-produced IGF1/2, CXCL12 and β-hydroxybutyrate were capable of inducing autophagy in cancer cells post-radiation and promoting cancer cell recovery from radiation-induced damage in vitro and in vivo in mice. These CAF-derived molecules increased the level of reactive oxygen species (ROS) post-radiation, which enhanced PP2A activity, repressing mTOR activation and increasing autophagy in cancer cells. Consistently, the IGF2 neutralizing antibody and the autophagy inhibitor 3-MA reduce the CAF-promoted tumor relapse in mice after radiotherapy. Taken together, our findings demonstrated that CAFs promoted irradiated cancer cell recovery and tumor regrowth post-radiation, suggesting that targeting the autophagy pathway in tumor cells may be a promising therapeutic strategy for radiotherapy sensitization.

Dose-dependent uptake of 3'-deoxy-3'-[(18) F]fluorothymidine by the bowel after total-body irradiation

PURPOSE

The aim of this study is to non-invasively assess early, irradiation-induced normal tissue alterations via metabolic imaging with 3'-deoxy-3'-[(18) F]fluorothymidine ([(18) F]FLT).

PROCEDURES

Twenty-nine male C57BL/6 mice were investigated by [(18) F]FLT positron emission tomography for 7 days after total body irradiation (1, 4, and 8 Gy) versus 'sham' irradiation (0 Gy). Target/background ratios were determined. The imaging results were validated by histology and immunohistochemistry (Thymidine kinase 1, Ki-67).

RESULTS

[(18) F]FLT demonstrated a dose-dependent intestinal accumulation post irradiation. Mean target/background ratio (±standard error) 0 Gy: 1.4 (0.2), 1 Gy: 1.7 (0.1), 4 Gy: 3.1 (0.3), 8 Gy: 4.2 (0.6). Receiver operating characteristic analysis (area under the curve, p value): 0 vs. 1 Gy: 0.81, 0.049; 0 vs. 4 Gy: 1.0, 0.0016; and 0 vs. 8 Gy: 1.0, 0.0020. Immunohistochemistry confirmed the results.

CONCLUSIONS

[(18) F]FLT seems to provide dose-dependent information on radiation-induced proliferation in the bowel. This opens the perspective for monitoring therapy-related side-effects as well as assessing, e.g., radiation accident victims.

Early radiation-induced changes evaluated by intravoxel incoherent motion in the major salivary glands

PURPOSE

To investigate the potential of intravoxel incoherent motion (IVIM) MRI for early evaluation of irradiated major salivary glands.

MATERIALS AND METHODS

Thirty-four patients with head-neck cancer were included in a prospective study. All patients underwent three serial IVIM-MRI: before, half-way through, and at the end of radiotherapy (RT). Apparent diffusion coefficient (ADC), ADClow derived in the low b-value range, perfusion fraction f, and pure diffusion coefficient D were estimated. Pretreatment values and early changes of diffusion parameters were correlated with parotid mean dose (Dmean ) and volume reduction after RT.

RESULTS

Changes in diffusion parameters over time were all significant (P < 0.001 for ADC, ADClow , and D, P = 0.003 for f). Variations of ADC, ADClow , and f were not correlated with Dmean (P = 0.089, P = 0.252 and P = 0.884, respectively), whereas a significant relationship was found between changes in D and Dmean (r = 0.197 with CI95% = 0.004-0.375, P = 0.046). Pretreatment f and Dmean were the best independent predictors for the percentage shrinkage (P = 0.0003 and 0.0597 respectively; R(2) = 0.391).

CONCLUSION

Early changes of irradiated major salivary glands can be noninvasively evaluated by IVIM-MRI. Perfusion-related coefficients in conjunction with dosimetric information increase our capability to predict the change in parotid volume and hence, if further validated, guide treatment strategy in RT.

Imaging radiation-induced normal tissue injury

Technological developments in radiation therapy and other cancer therapies have led to a progressive increase in five-year survival rates over the last few decades. Although acute effects have been largely minimized by both technical advances and medical interventions, late effects remain a concern. Indeed, the need to identify those individuals who will develop radiation-induced late effects, and to develop interventions to prevent or ameliorate these late effects is a critical area of radiobiology research. In the last two decades, preclinical studies have clearly established that late radiation injury can be prevented/ameliorated by pharmacological therapies aimed at modulating the cascade of events leading to the clinical expression of radiation-induced late effects. These insights have been accompanied by significant technological advances in imaging that are moving radiation oncology and normal tissue radiobiology from disciplines driven by anatomy and macrostructure to ones in which important quantitative functional, microstructural, and metabolic data can be noninvasively and serially determined. In the current article, we review use of positron emission tomography (PET), single photon emission tomography (SPECT), magnetic resonance (MR) imaging and MR spectroscopy to generate pathophysiological and functional data in the central nervous system, lung, and heart that offer the promise of, (1) identifying individuals who are at risk of developing radiation-induced late effects, and (2) monitoring the efficacy of interventions to prevent/ameliorate them.

Molecular biology: the key to personalised treatment in radiation oncology?

We know considerably more about what makes cells and tissues resistant or sensitive to radiation than we did 20 years ago. Novel techniques in molecular biology have made a major contribution to our understanding at the level of signalling pathways. Before the "New Biology" era, radioresponsiveness was defined in terms of physiological parameters designated as the five Rs. These are: repair, repopulation, reassortment, reoxygenation and radiosensitivity. Of these, only the role of hypoxia proved to be a robust predictive and prognostic marker, but radiotherapy regimens were nonetheless modified in terms of dose per fraction, fraction size and overall time, in ways that persist in clinical practice today. The first molecular techniques were applied to radiobiology about two decades ago and soon revealed the existence of genes/proteins that respond to and influence the cellular outcome of irradiation. The subsequent development of screening techniques using microarray technology has since revealed that a very large number of genes fall into this category. We can now obtain an adequately robust molecular signature, predicting for a radioresponsive phenotype using gene expression and proteomic approaches. In parallel with these developments, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) can now detect specific biological molecules such as haemoglobin and glucose, so revealing a 3D map of tumour blood flow and metabolism. The key to personalised radiotherapy will be to extend this capability to the proteins of the molecular signature that determine radiosensitivity.

A Markov decision process approach to temporal modulation of dose fractions in radiation therapy planning

The current state of the art in cancer treatment by radiation optimizes beam intensity spatially such that tumors receive high dose radiation whereas damage to nearby healthy tissues is minimized. It is common practice to deliver the radiation over several weeks, where the daily dose is a small constant fraction of the total planned. Such a 'fractionation schedule' is based on traditional models of radiobiological response where normal tissue cells possess the ability to repair sublethal damage done by radiation. This capability is significantly less prominent in tumors. Recent advances in quantitative functional imaging and biological markers are providing new opportunities to measure patient response to radiation over the treatment course. This opens the door for designing fractionation schedules that take into account the patient's cumulative response to radiation up to a particular treatment day in determining the fraction on that day. We propose a novel approach that, for the first time, mathematically explores the benefits of such fractionation schemes. This is achieved by building a stylistic Markov decision process (MDP) model, which incorporates some key features of the problem through intuitive choices of state and action spaces, as well as transition probability and reward functions. The structure of optimal policies for this MDP model is explored through several simple numerical examples.