Molecular imaging biomarkers of resistance to radiation therapy for spontaneous nasal tumors in canines

Relative tumor volume has prognostic relevance in canine sinonasal tumors treated with radiation therapy: A retrospective study

Tumor volume is controversially discussed as a prognostic factor in dogs treated with radiation therapy for sinonasal tumors. Dogs’ body sizes vary widely and relative rather than absolute tumor volume might provide better prognostic information. Our hypothesis was that relative rather than absolute tumor volume (gross tumor volume, GTV) influences time to progression (TTP) and that a larger tumor volume is correlated with a higher tumor stage. We retrospectively investigated possible correlations of initial GTV to weight, body surface area (BSA), nasal cavity size and the tumor stage in 49 dogs with sinonasal tumors. Here, also presumed sinonasal tumors, esthesioneuroblastomas and histologically benign tumors were included. The possible impact of absolute and relative GTV on response and outcome were assessed according to imaging findings in 34 dogs with available follow-up computed tomographies (CTs) after definitive-intent radiation therapy with either a regular (10x4.2 Gy) or a simultaneously- integrated boost protocol (SIB; GTV boosted to 10x4.83 Gy). In contrast to absolute GTV (p<0.001), the relative GTVs were not correlated with dogs’ body sizes. Absolute GTV, GTV relative to weight and BSA were not associated with TTP based on CT imaging. However, GTV relative to nasal cavity showed a prognostic influence with a hazard ratio of 10.97 (95%CI:1.25–96.06). When looking at GTV relative to nasal cavity, stage 3 and 4 tumors were significantly larger than stage 1 and 2 tumors (p = 0.005). Our results suggest that GTV relative to nasal cavity could be prognostic for TTP and a larger tumor volume relative to nasal cavity is correlated with a higher tumor stage.

Dose-escalated simultaneously integrated boost radiation protocol fails to result in a survival advantage for sinonasal tumors in dogs

The prognosis for canine sinonasal tumors remains rather poor despite definitive-intent radiotherapy (RT). Theoretical calculations predicted improved outcomes with simultaneously integrated boost (SIB) protocols. With the hypothesis of clinically detectable differences in outcome between groups, our retrospective study evaluated prognostic variables and outcome in dogs treated with regular versus SIB RT. Dogs with sinonasal tumors treated with either a regular (10 × 4.2 Gy) or new SIB protocol (10 × 4.83 Gy to macroscopic tumor) were included. Information regarding signalment, tumor stage, type, clinical signs, radiation toxicity, response, and outcome was collected. Forty-nine dogs were included: 27 treated regularly and 22 treated with SIB RT. A total of 69.4% showed epistaxis, 6.1% showed epileptic seizures, 46.9% showed stage IV tumors, and 6.1% showed lymph node metastases. Early toxicity was mostly mild. Late grade 1 skin toxicity (alopecia/leucotrichia) was seen in 72.1% of dogs, and a possible grade 3 ocular toxicity (blindness) was seen in one dog. Complete/partial resolution of clinical signs was seen in 95.9% of patients as best clinical response and partial remission was seen as best imaging response in 34.7%. The median progression-free survival (PFS) was 274 days (95% CI: 117-383) for regular and 300 days (95% CI: 143-451) for SIB RT, which was not significantly different (P = 0.42). Similarly, the median overall survival (OS) was 348 days (95% CI: 121-500) for regular and 381 days (95% CI: 295-634) for the SIB RT (P = 0.18). Stratified by protocol, the hazard ratio of stage IV versus stage I-III tumors was 2.29 (95% CI: 1.156-4.551, P = 0.02) for OS but not PFS. All dogs showed acceptable toxicity. In contrast to theoretical predictions, however, we could not show a statistically significant better outcome with the new protocol.

Patterns of local residual disease and local failure after intensity modulated/image guided radiation therapy for sinonasal tumors in dogs

BACKGROUND

Most dogs with sinonasal tumors (SNT) treated with radiation therapy (RT) died because of local disease progression.

HYPOTHESIS/OBJECTIVES

Our hypothesis is that the majority of local failure and residual disease would occur within the radiation field.

ANIMALS

Twenty-two dogs with SNT treated with RT.

METHODS

Retrospective cohort study.

INCLUSION CRITERIA

dogs with SNT receiving 10 daily fractions of 4.2 Gy with intensity modulated radiation therapy (IMRT)/image guided radiation therapy (IGRT) and follow-up cone beam computed tomography (CBCT). Each CBCT was registered with the original radiation planning CT and the gross tumor volume (GTV) contoured. The GTV was classified as residual (GTVr) or a failure (GTVf). The dose statistic for each GTV was calculated with the original IMRT plan. For GTVf, failures were classified as "in-field," "marginal," or "out-field" if at least 95, 20-95, or less than 20% of the volume of failure was within 95% (D95) of the total prescription dose, respectively.

RESULTS

There were 52 follow-up CBCT/CTs. Overall there was a GTVr for 20 dogs and GTVf for 16 dogs. The majority of GTVr volume was within the original GTV. GTVf analysis showed that 75% (12/16) were "in-field," 19% (3/16) were "marginal" and 6% (1/16) were "out-field."

CONCLUSION AND CLINICAL IMPORTANCE

In-field failures are the main pattern for local recurrence, and there is evidence of radioresistant subvolumes within the GTV.

Optimal treatment plan adaptation using mid-treatment imaging biomarkers

Previous studies on personalized radiotherapy (RT) have mostly focused on baseline patient stratification, adapting the treatment plan according to mid-treatment anatomical changes, or dose boosting to selected tumor subregions using mid-treatment radiological findings. However, the question of how to find the optimal adapted plan has not been properly tackled. Moreover, the effect of information uncertainty on the resulting adaptation has not been explored. In this paper, we present a framework to optimally adapt radiation therapy treatments to early radiation treatment response estimates derived from pre- and mid-treatment imaging data while considering the information uncertainty. The framework is based on the optimal stopping in radiation therapy (OSRT) framework. Biological response is quantified using tumor control probability (TCP) and normal tissue complication probability (NTCP) models, and these are directly optimized for in the adaptation step. Two adaptation strategies are discussed: (1) uniform dose adaptation and (2) continuous dose adaptation. In the first strategy, the original fluence-map is simply scaled upwards or downwards, depending on whether dose escalation or de-escalation is deemed appropriate based on the mid-treatment response observed from the radiological images. In the second strategy, a full NTCP-TCP-based fluence map re-optimization is performed to achieve the optimal adapted plans. We retrospectively tested the performance of these strategies on 14 canine head and neck cases treated with tomotherapy, using as response biomarker the change in the 3'-deoxy-3'[(18)F]-fluorothymidine (FLT)-PET signals between the pre- and mid-treatment images, and accounting for information uncertainty. Using a 10% uncertainty level, the two adaptation strategies both yield a noteworthy average improvement in guaranteed (worst-case) TCP.

Spatial process decomposition for quantitative imaging biomarkers using multiple images of varying shapes

Quantitative imaging biomarkers (QIB) are extracted from medical images in radiomics for a variety of purposes including noninvasive disease detection, cancer monitoring, and precision medicine. The existing methods for QIB extraction tend to be ad hoc and not reproducible. In this article, a general and flexible statistical approach is proposed for handling up to three-dimensional medical images and reasonably capturing features with respect to specific spatial patterns. In particular, a model-based spatial process decomposition is developed where the random weights are unique to individual patients for component functions common across patients. Model fitting and selection are based on maximum likelihood, while feature extractions are via optimal prediction of the underlying true image. Simulation studies are conducted to investigate the properties of the proposed methodology. For illustration, a cancer image data set is analyzed and QIBs are extracted in association with a clinical endpoint.

Advanced Cancer Imaging Applied in the Comparative Setting

The potential for companion (pet) species with spontaneously arising tumors to act as surrogates for preclinical development of advanced cancer imaging technologies has become more apparent in the last decade. The utility of the companion model specifically centers around issues related to body size (including spatial target/normal anatomic characteristics), physical size and spatial distribution of metastasis, tumor heterogeneity, the presence of an intact syngeneic immune system and a syngeneic tumor microenvironment shaped by the natural evolution of the cancer. Companion species size allows the use of similar equipment, hardware setup, software, and scan protocols which provide the opportunity for standardization and harmonization of imaging operating procedures and quality assurance across imaging protocols, imaging hardware, and the imaged species. Murine models generally do not replicate the size and spatial distribution of human metastatic cancer and these factors strongly influence image resolution and dosimetry. The following review will discuss several aspects of comparative cancer imaging in more detail while providing several illustrative examples of investigational approaches performed or currently under exploration at our institutions. Topics addressed include a discussion on interested consortia; image quality assurance and harmonization; image-based biomarker development and validation; contrast agent and radionuclide tracer development; advanced imaging to assess and predict response to cytotoxic and immunomodulatory anticancer agents; imaging of the tumor microenvironment; development of novel theranostic approaches; cell trafficking assessment via non-invasive imaging; and intraoperative imaging to inform surgical oncology decision making. Taken in totality, these comparative opportunities predict that safety, diagnostic and efficacy data generated in companion species with naturally developing and progressing cancers would better recapitulate the human cancer condition than that of artificial models in small rodent systems and ultimately accelerate the integration of novel imaging technologies into clinical practice. It is our hope that the examples presented should serve to provide those involved in cancer investigations who are unfamiliar with available comparative methodologies an understanding of the potential utility of this approach.

Emerging Translational Opportunities in Comparative Oncology With Companion Canine Cancers: Radiation Oncology

It is estimated that more than 6 million pet dogs are diagnosed with cancer annually in the USA. Both primary care and specialist veterinarians are frequently called upon to provide clinical care that improves the quality and/or quantity of life for affected animals. Because these cancers develop spontaneously in animals that often share the same environment as their owners, have intact immune systems and are of similar size to humans, and because the diagnostic tests and treatments for these cancers are similar to those used for management of human cancers, canine cancer provides an opportunity for research that simultaneously helps improve both canine and human health care. This is especially true in the field of radiation oncology, for which there is a rich and continually evolving history of learning from the careful study of pet dogs undergoing various forms of radiotherapy. The purpose of this review article is to inform readers of the potential utility and limitations of using dogs in that manner; the peer-reviewed literature will be critically reviewed, and current research efforts will be discussed. The article concludes with a look toward promising future directions and applications of this pet dog “model.”

Role of Positron Emission Tomography in Imaging of Non-neurologic Disorders of the Head, Neck, and Teeth in Veterinary Medicine

Positron Emission Tomography (PET) is an imaging technique that provides functional information, in addition to structural information obtained with computed tomography (CT). The most common application is cancer staging, using ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG), a radioactive analog of glucose. Although limited data are available in the veterinary literature, human studies have demonstrated benefit with the addition of PET both for assessment of the primary tumor and for detection of metastatic disease. ¹⁸F-FDG PET appears to be more accurate at detecting the margin of oral neoplasia, in particular for tumors arising from highly vascularized tissue, such as the lingual and laryngeal areas. ¹⁸F-FDG PET has a high sensitivity for the detection of lymph node metastasis, however the specificity is variable between studies. Tracers beyond ¹⁸F-FDG can also be used for oncology imaging. ¹⁸F-Fluoride (¹⁸F-NaF) is an excellent osseous tracer, useful in assessing bone involvement of primary tumors or osseous metastasis. Other specific tracers can be used to assess cell proliferation or hypoxia for tumor characterization. ¹⁸F-FDG is also an excellent tracer for detection of inflammation. Human studies have demonstrated its value for the assessment of periodontitis and dental implant infection. ¹⁸F-NaF has been used to assess disorders of the temporomandibular joint in the human literature, demonstrating good correlation with arthralgia and therapeutic outcome. Both ¹⁸F-NaF and ¹⁸F-FDG had good concordance with localization of cervical pain in people. PET will likely have a growing role in veterinary medicine not only for oncologic imaging but also for assessment of inflammation and pain.

A prospective pilot study on early toxicity from a simultaneously integrated boost technique for canine sinonasal tumours using image-guided intensity-modulated radiation therapy

In order to overcome the common local treatment failure of canine sinonasal tumours, integrated boost techniques were tried in the cobalt/orthovoltage era, but dismissed because of unacceptable early (acute) toxicity. Intriguingly, a recent calculation study of a simultaneously integrated boost (SIB) technique for sinonasal irradiation using intensity-modulated radiation therapy (IMRT) predicted theoretical feasibility. In this prospective pilot study we applied a commonly used protocol of 10 × 4.2 Gy to the planning target volume (PTV) with a 20%-SIB dose to the gross tumour volume (GTV). Our hypothesis expected this dose escalation to be clinically tolerable if applied with image-guided IMRT. We included 9 dogs diagnosed with sinonasal tumours without local/distant metastases. For treatment planning, organs at risk were contoured according to strict anatomical guidelines. Planning volume extensions (GTV/CTV/PTV) were standardized to minimize interplanner variability. Treatments were applied with rigid patient positioning and verified daily with image guidance. After radiation therapy, we set focus on early ophthalmologic complications as well as mucosal and cutaneous toxicity. Early toxicity was evaluated at week 1, 2, 3, 8 and 12 after radiotherapy. Only mild ophthalmologic complications were found. Three patients (33%) had self-limiting moderate to severe early toxicity (grade 3 mucositis) which was managed medically. No patient developed ulcerations/haemorrhage/necrosis of skin/mucosa. The SIB protocol applied with image-guided IMRT to treat canine sinonasal tumours led to clinically acceptable side effects. The suspected increased tumour control probability and the risk of late toxicity with the used dose escalation of 20% has to be further investigated.

Assessing Tumor Oxygenation for Predicting Outcome in Radiation Oncology: A Review of Studies Correlating Tumor Hypoxic Status and Outcome in the Preclinical and Clinical Settings

Tumor hypoxia is recognized as a limiting factor for the efficacy of radiotherapy, because it enhances tumor radioresistance. It is strongly suggested that assessing tumor oxygenation could help to predict the outcome of cancer patients undergoing radiation therapy. Strategies have also been developed to alleviate tumor hypoxia in order to radiosensitize tumors. In addition, oxygen mapping is critically needed for intensity modulated radiation therapy (IMRT), in which the most hypoxic regions require higher radiation doses and the most oxygenated regions require lower radiation doses. However, the assessment of tumor oxygenation is not yet included in day-to-day clinical practice. This is due to the lack of a method for the quantitative and non-invasive mapping of tumor oxygenation. To fully integrate tumor hypoxia parameters into effective improvements of the individually tailored radiation therapy protocols in cancer patients, methods allowing non-invasively repeated, safe, and robust mapping of changes in tissue oxygenation are required. In this review, non-invasive methods dedicated to assessing tumor oxygenation with the ultimate goal of predicting outcome in radiation oncology are presented, including positron emission tomography used with nitroimidazole tracers, magnetic resonance methods using endogenous contrasts (R₁ and R2*-based methods), and electron paramagnetic resonance oximetry; the goal is to highlight results of studies establishing correlations between tumor hypoxic status and patients’ outcome in the preclinical and clinical settings.

Biological imaging in clinical oncology: radiation therapy based on functional imaging

Radiation therapy is one of the most effective tools for cancer treatment. In recent years, intensity-modulated radiation therapy has become increasingly popular in that target dose-escalation can be done while sparing adjacent normal tissues. For this reason, the development of measures to pave the way for accurate target delineation is of great interest. With the integration of functional information obtained by biological imaging with radiotherapy, strategies using advanced biological imaging to visualize metabolic pathways and to improve therapeutic index and predict treatment response are discussed in this article.

Genetic analysis of radiation-specific biomarkers in sinonasal squamous cell carcinomas

The aim of this study was to investigate the differences in the gene expression profiles of radiation-sensitive (RS) and radiation-resistant (RR) sinonasal squamous cell carcinoma (SNSCC) and to identify prognostic markers for the radiation reaction of SNSCC. We first examined the differentially expressed genes (DEGs) in RS and RR SNSCC tissues by analyzing clinical samples with GeneChip Human Transcriptome Array 2.0 (HTA 2.0).To understand the functional significance of the molecular changes, we examined the DEGs with Gene Ontology (GO) and pathway analyses to identify the core genes. The expression of several core genes (CCND2, COL5A2, GADD45B, and THBS2) was confirmed with reverse transcription quantitative PCR (RT-qPCR) in a larger series of tissues. We identified 208 DEGs, of which 76 were upregulated and 132 downregulated in the RS tissues relative to the RR tissues. The DEGs were mainly involved in the regulation of cell proliferation, the NF-kappaB signaling pathway, the cell adhesion molecule signaling pathway, and the extracellular matrix-receptor interaction signaling pathway. RT-qPCR confirmed that the CCND2, COL5A2, GADD45B, and THBS2 genes were significantly differentially expressed in the RS and RR tissues, consistent with the GeneChip data. These results extend our understanding of the molecular mechanisms underlying the sensitivity of SNSCC to radiation. The DEGs are involved in the differential response to radiation therapy and the dysregulated core genes identified in this study can be used to predict radiation sensitivity in SNSCC.

Molecular Imaging to Plan Radiotherapy and Evaluate Its Efficacy

Molecular imaging plays a central role in the management of radiation oncology patients. Specific uses of imaging, particularly to plan radiotherapy and assess its efficacy, require an additional level of reproducibility and image quality beyond what is required for diagnostic imaging. Specific requirements include proper patient preparation, adequate technologist training, careful imaging protocol design, reliable scanner technology, reproducible software algorithms, and reliable data analysis methods. As uncertainty in target definition is arguably the greatest challenge facing radiation oncology, the greatest impact that molecular imaging can have may be in the reduction of interobserver variability in target volume delineation and in providing greater conformity between target volume boundaries and true tumor boundaries. Several automatic and semiautomatic contouring methods based on molecular imaging are available but still need sufficient validation to be widely adopted. Biologically conformal radiotherapy (dose painting) based on molecular imaging-assessed tumor heterogeneity is being investigated, but many challenges remain to fully exploring its potential. Molecular imaging also plays increasingly important roles in both early (during treatment) and late (after treatment) response assessment as both a predictive and a prognostic tool. Because of potentially confounding effects of radiation-induced inflammation, treatment response assessment requires careful interpretation. Although molecular imaging is already strongly embedded in radiotherapy, the path to widespread and all-inclusive use is still long. The lack of solid clinical evidence is the main impediment to broader use. Recommendations for practicing physicians are still rather scarce. (18)F-FDG PET/CT remains the main molecular imaging modality in radiation oncology applications. Although other molecular imaging options (e.g., proliferation imaging) are becoming more common, their widespread use is limited by lack of tracer availability and inadequate reimbursement models. With the increasing presence of molecular imaging in radiation oncology, special emphasis should be placed on adequate training of radiation oncology personnel to understand the potential, and particularly the limitations, of quantitative molecular imaging applications. Similarly, radiologists and nuclear medicine specialists should be sensitized to the special need of the radiation oncologist in terms of quantification and reproducibility. Furthermore, strong collaboration between radiation oncology, nuclear medicine/radiology, and medical physics teams is necessary, as optimal and safe use of molecular imaging can be ensured only within appropriate interdisciplinary teams.

Predicting location of recurrence using FDG, FLT, and Cu-ATSM PET in canine sinonasal tumors treated with radiotherapy

Dose painting relies on the ability of functional imaging to identify resistant tumor subvolumes to be targeted for additional boosting. This work assessed the ability of FDG, FLT, and Cu-ATSM PET imaging to predict the locations of residual FDG PET in canine tumors following radiotherapy. Nineteen canines with spontaneous sinonasal tumors underwent PET/CT imaging with radiotracers FDG, FLT, and Cu-ATSM prior to hypofractionated radiotherapy. Therapy consisted of 10 fractions of 4.2 Gy to the sinonasal cavity with or without an integrated boost of 0.8 Gy to the GTV. Patients had an additional FLT PET/CT scan after fraction 2, a Cu-ATSM PET/CT scan after fraction 3, and follow-up FDG PET/CT scans after radiotherapy. Following image registration, simple and multiple linear and logistic voxel regressions were performed to assess how well pre- and mid-treatment PET imaging predicted post-treatment FDG uptake. R(2) and pseudo R(2) were used to assess the goodness of fits. For simple linear regression models, regression coefficients for all pre- and mid-treatment PET images were significantly positive across the population (P < 0.05). However, there was large variability among patients in goodness of fits: R(2) ranged from 0.00 to 0.85, with a median of 0.12. Results for logistic regression models were similar. Multiple linear regression models resulted in better fits (median R(2) = 0.31), but there was still large variability between patients in R(2). The R(2) from regression models for different predictor variables were highly correlated across patients (R ≈ 0.8), indicating tumors that were poorly predicted with one tracer were also poorly predicted by other tracers. In conclusion, the high inter-patient variability in goodness of fits indicates that PET was able to predict locations of residual tumor in some patients, but not others. This suggests not all patients would be good candidates for dose painting based on a single biological target.