Theragnostic imaging for radiation oncology: dose-painting by numbers

Interim 18F-FDG-PET based response-adaptive dose escalation of proton therapy for head and neck cancer: a treatment planning feasibility study

BACKGROUND

Image-driven dose escalation to tumor subvolumes has been proposed to improve treatment outcome in head and neck cancer (HNC). We used 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) acquired at baseline and into treatment (interim) to identify biologic target volumes (BTVs). We assessed the feasibility of interim dose escalation to the BTV with proton therapy by simulating the effects to organs at risk (OARs).

METHODS

We used the semiautomated just-enough-interaction (JEI) method to identify BTVs in 18F-FDG-PET images from nine HNC patients. Between baseline and interim FDG-PET, patients received photon radiotherapy. BTV was identified assuming that high standardized uptake value (SUV) at interim reflected tumor radioresistance. Using Eclipse (Varian Medical Systems), we simulated a 10% (6.8 Gy(RBE1.1)) and 20% (13.6 Gy(RBE1.1)) dose escalation to the BTV with protons and compared results with proton plans without dose escalation.

RESULTS

At interim 18F-FDG-PET, radiotherapy resulted in reduced SUV compared to baseline. However, spatial overlap between high-SUV regions at baseline and interim allowed for BTV identification. Proton therapy planning demonstrated that dose escalation to the BTV was feasible, and except for some 20% dose escalation plans, OAR doses did not significantly increase.

CONCLUSION

Our in silico analysis demonstrated the potential for interim 18F-FDG-PET response-adaptive dose escalation to the BTV with proton therapy. This approach may give more efficient treatment to HNC with radioresistant tumor subvolumes without increasing normal tissue toxicity. Studies in larger cohorts are required to determine the full potential for interim 18F-FDG-PET-guided dose escalation of proton therapy in HNC.

Rethinking the potential role of dose painting in personalized ultra-fractionated stereotactic adaptive radiotherapy

Fractionated radiotherapy was established in the 1920s based upon two principles: (1) delivering daily treatments of equal quantity, unless the clinical situation requires adjustment, and (2) defining a specific treatment period to deliver a total dosage. Modern fractionated radiotherapy continues to adhere to these century-old principles, despite significant advancements in our understanding of radiobiology. At UT Southwestern, we are exploring a novel treatment approach called PULSAR (Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy). This method involves administering tumoricidal doses in a pulse mode with extended intervals, typically spanning weeks or even a month. Extended intervals permit substantial recovery of normal tissues and afford the tumor and tumor microenvironment ample time to undergo significant changes, enabling more meaningful adaptation in response to the evolving characteristics of the tumor. The notion of dose painting in the realm of radiation therapy has long been a subject of contention. The debate primarily revolves around its clinical effectiveness and optimal methods of implementation. In this perspective, we discuss two facets concerning the potential integration of dose painting with PULSAR, along with several practical considerations. If successful, the combination of the two may not only provide another level of personal adaptation ("adaptive dose painting"), but also contribute to the establishment of a timely feedback loop throughout the treatment process. To substantiate our perspective, we conducted a fundamental modeling study focusing on PET-guided dose painting, incorporating tumor heterogeneity and tumor control probability (TCP).

Disease Control and Late Toxicity in Adaptive Dose Painting by Numbers Versus Nonadaptive Radiation Therapy for Head and Neck Cancer: A Randomized Controlled Phase 2 Trial

PURPOSE

Local recurrence remains the main cause of death in stage III-IV nonmetastatic head and neck cancer (HNC), with relapse-prone regions within high 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET)-signal gross tumor volume. We investigated if dose escalation within this subvolume combined with a 3-phase treatment adaptation could increase local (LC) and regional (RC) control at equal or minimized radiation-induced toxicity, by comparing adaptive 18F-FDG-PET voxel intensity-based dose painting by numbers (A-DPBN) with nonadaptive standard intensity modulated radiation therapy (S-IMRT).

METHODS AND MATERIALS

This 2-center randomized controlled phase 2 trial assigned (1:1) patients to receive A-DPBN or S-IMRT (+/-chemotherapy). Eligibility: nonmetastatic HNC of oral cavity, oro-/hypopharynx, or larynx, needing radio(chemo)therapy; T1-4N0-3 (exception: T1-2N0 glottic); KPS ≥ 70; ≥18 years; and informed consent.

PRIMARY OUTCOMES

1-year LC and RC. The dose prescription for A-DPBN was intercurrently adapted in 2 steps to an absolute dose-volume limit (≤1.75 cm3 can receive >84 Gy and normalized isoeffective dose >96 Gy) as a safety measure during the study course after 4/7 A-DPBN patients developed ≥G3 mucosal ulcers.

RESULTS

Ninety-five patients were randomized (A-DPBN, 47; S-IMRT, 48). Median follow-up was 31 months (IQR, 14-48 months); 29 patients died (17 of cancer progression). A-DPBN resulted in superior LC compared with S-IMRT, with 1- and 2-year LC of 91% and 88% versus 78% and 75%, respectively (hazard ratio, 3.13; 95% CI, 1.13-8.71; P = .021). RC and overall survival were comparable between arms, as was overall grade (G) ≥3 late toxicity (36% vs 20%; P = .1). More ≥G3 late mucosal ulcers were observed in active smokers (29% vs 3%; P = .005) and alcohol users (33% vs 13%; P = .02), independent of treatment arm. Similarly, in the A-DPBN arm, significantly more patients who smoked at diagnosis developed ≥G3 (46% vs 12%; P = .005) and ≥G4 (29% vs 8%; P = .048) mucosal ulcers. One arterial blowout occurred after a G5 mucosal toxicity.

CONCLUSIONS

A-DPBN resulted in superior 1- and 2-year LC for HNC compared with S-IMRT. This supports further exploration in multicenter phase 3 trials. It will, however, be challenging to recruit a substantial patient sample for such trials, as concerns have arisen regarding the association of late mucosal ulcers when escalating the dose in continuing smokers.

A Novel Framework for Thermoradiotherapy Treatment Planning

PURPOSE

Thermoradiotherapy combines radiation therapy with hyperthermia to increase therapeutic effectiveness. Currently, both modalities are optimized separately and in state-of-the-art research the enhanced therapeutic effect is evaluated using equivalent radiation dose in 2-Gy fractions (EQD2). This study proposes a novel thermoradiotherapy treatment planning framework with voxelwise EQD2 radiation therapy optimizing including thermal radiosensitization and direct thermal cytotoxicity.

METHODS AND MATERIALS

To demonstrate proof-of-concept of the planning framework, 3 strategies consisting of 20 radiation therapy fractions were planned for 4 prostate cancer cases with substantially different temperature distributions: (1) Conventional radiation therapy plan of 60 Gy combined with 4 hyperthermia sessions (RT60 + HT), (2) standalone uniform dose escalation to 68 Gy without hyperthermia (RT68), and (3) uniform target EQD2 that maximizes the tumor control probability (TCP) accounting for voxelwise thermal effects of 4 hyperthermia sessions without increasing normal tissue doses (RTHT + HT). Assessment included dose, EQD2, TCP, and rectal normal tissue complication probability (NTCP), alongside robustness analyses for TCP and NTCP against parameter uncertainties.

RESULTS

The estimated TCP of around 76% for RT60 without hyperthermia was increased to an average of 85.9% (range, 81.3%-90.5%) for RT60 + HT, 92.5% (92.4%-92.5%) for RT68, and 94.4% (91.7%-96.6%) for RTHT + HT. The corresponding averaged rectal NTCPs were 8.7% (7.9%-10.0%), 14.9% (13.8%-17.1%), and 8.4% (7.5%-9.7%), respectively. RT68 and RTHT + HT exhibited slightly enhanced TCP robustness against parameter uncertainties compared with RT60 + HT, and RT68 presented higher and less robust rectal NTCP values compared with the other planning strategies.

CONCLUSIONS

This study introduces an innovative thermoradiotherapy planning approach, integrating thermal effects into EQD2-based radiation therapy optimization. Results demonstrate an ability to achieve enhanced and uniform target EQD2 and TCP across various temperature distributions without elevating normal tissue EQD2 or NTCP compared with conventional methods. Although promising for improving clinical outcomes, realizable enhancements depend on accurate tumor- and tissue-specific data and precise quantification of hyperthermic effects, which are seamlessly integrable in the planning framework as they emerge.

Plan Assessment Metrics for Dose Painting in Stereotactic Radiosurgery

Purpose

As radiation therapy treatment precision increases with advancements in imaging and radiation delivery, dose painting treatment becomes increasingly feasible, where targets receive a nonuniform radiation dose. The high precision of stereotactic radiosurgery (SRS) makes it a good candidate for dose painting treatments, but no suitable metrics to assess dose painting SRS plans exist. Existing dose painting assessment metrics weigh target overdose and underdose equally but are unsuited for SRS plans, which typically avoid target underdose more. Current SRS metrics also prioritize reducing healthy tissue dose through selectivity and dose fall-off, and these metrics assume single prescriptions. We propose a set of metrics for dose painting SRS that would meet clinical needs and are calculated with nonuniform dose painting prescriptions.

Methods and Materials

Sample dose painting SRS prescriptions are first created from Gamma Knife SRS cases, apparent diffusion coefficient magnetic resonance images, and various image-to-prescription functions. Treatment plans are found through semi-infinite linear programming optimization and using clinically determined isocenters, then assessed with existing and proposed metrics. Modified versions of SRS metrics are proposed, including coverage, selectivity, conformity, efficiency, and gradient indices. Quality factor, a current dose painting metric, is applied both without changes and with modifications. A new metric, integral dose ratio, is proposed as a measure of target overdose.

Results

The merits of existing and modified metrics are demonstrated and discussed. A modified conformity index using mean or minimum prescription dose would be suitable for dose painting SRS with integral or maximum boost methods, respectively. Either modified efficiency index is a suitable replacement for the existing gradient index.

Conclusions

The proposed modified SRS metrics are appropriate measures of plan quality for dose painting SRS plans and have the advantage of giving equal values as the original SRS metrics when applied to single-prescription plans.

Plan robustness and RBE influence for proton dose painting by numbers for head and neck cancers

PURPOSE

To investigate the feasibility of dose painting by numbers (DPBN) with respect to robustness for proton therapy for head and neck cancers (HNC), and to study the influence of variable RBE on the TCP and OAR dose burden.

METHODS AND MATERIALS

Data for 19 patients who have been scanned pretreatment with PET-FDG and subsequently treated with photon therapy were used in the study. A dose response model developed for photon therapy was implemented in a TPS, allowing DPBN plans to be created. Conventional homogeneous dose and DPBN plans were created for each patient, optimized with either fixed RBE = 1.1 or a variable RBE model. Robust optimization was used to create clinically acceptable plans. To estimate the maximum potential loss in TCP due to actual SUV variations from the pre-treatment imaging, we applied a test case with randomized SUV distribution.

RESULTS

Regardless of the use of variable RBE for optimization or evaluation, a statistically significant increase (p < 0.001) in TCP was found for DPBN plans as compared to homogeneous dose plans. Randomizing the SUV distribution decreased the TCP for all plans. A correlation between TCP increase and variance of the SUV distribution and target volume was also found.

CONCLUSION

DPBN for protons and HNC is feasible and could lead to a TCP gain. Risks associated with the temporal variation of SUV distributions could be mitigated by imposing minimum doses to targets. The correlation found between TCP increase and SUV variance and target volume may be used for patient selection.

[18F]FDG-PET-Based Personalized Radiotherapy Dose Prescription

PET imaging with 2'-deoxy-2'-[18F]fluoro-D-glucose ([18F]FDG) has become one of the pillars in the management of malignant diseases. It has proven value in diagnostic workup, treatment policy, follow-up, and as prognosticator for outcome. [18F]FDG is widely available and standards have been developed for PET acquisition protocols and quantitative analyses. More recently, [18F]FDG-PET is also starting to be appreciated as a decision aid for treatment personalization. This review focuses on the potential of [18F]FDG-PET for individualized radiotherapy dose prescription. This includes dose painting, gradient dose prescription, and [18F]FDG-PET guided response-adapted dose prescription. The current status, progress, and future expectations of these developments for various tumor types are discussed.

Isotoxic dose escalated radiotherapy for glioblastoma based on diffusion-weighted MRI and tumor control probability-an in-silico study

OBJECTIVES

Glioblastoma (GBM) is the most common malignant primary brain tumor with local recurrence after radiotherapy (RT), the most common mode of failure. Standard RT practice applies the prescription dose uniformly across tumor volume disregarding radiological tumor heterogeneity. We present a novel strategy using diffusion-weighted (DW-) MRI to calculate the cellular density within the gross tumor volume (GTV) in order to facilitate dose escalation to a biological target volume (BTV) to improve tumor control probability (TCP).

METHODS

The pre-treatment apparent diffusion coefficient (ADC) maps derived from DW-MRI of ten GBM patients treated with radical chemoradiotherapy were used to calculate the local cellular density based on published data. Then, a TCP model was used to calculate TCP maps from the derived cell density values. The dose was escalated using a simultaneous integrated boost (SIB) to the BTV, defined as the voxels for which the expected pre-boost TCP was in the lowest quartile of the TCP range for each patient. The SIB dose was chosen so that the TCP in the BTV increased to match the average TCP of the whole tumor.

RESULTS

By applying a SIB of between 3.60 Gy and 16.80 Gy isotoxically to the BTV, the cohort's calculated TCP increased by a mean of 8.44% (ranging from 7.19 to 16.84%). The radiation dose to organ at risk is still under their tolerance.

CONCLUSIONS

Our findings indicate that TCPs of GBM patients could be increased by escalating radiation doses to intratumoral locations guided by the patient's biology (i.e., cellularity), moreover offering the possibility for personalized RT GBM treatments.

ADVANCES IN KNOWLEDGE

A personalized and voxel level SIB radiotherapy method for GBM is proposed using DW-MRI, which can increase the tumor control probability and maintain organ at risk dose constraints.

Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy

BACKGROUND

Biologically targeted radiation therapy treatment planning requires voxel-wise characterisation of tumours. Dynamic contrast enhanced (DCE) DCE MRI has shown promise in defining voxel-level biological characteristics. In this study we consider the relative value of qualitative, semi-quantitative and quantitative assessment of DCE MRI compared with diffusion weighted imaging (DWI) and T2-weighted (T2w) imaging to detect prostate cancer at the voxel level.

METHODS

Seventy prostate cancer patients had multiparametric MRI prior to radical prostatectomy, including T2w, DWI and DCE MRI. Apparent Diffusion Coefficient (ADC) maps were computed from DWI, and semi-quantitative and quantitative parameters computed from DCE MRI. Tumour location and grade were validated with co-registered whole mount histology. Kolmogorov-Smirnov tests were applied to determine whether MRI parameters in tumour and benign voxels were significantly different. Cohen's d was computed to quantify the most promising biomarkers. The Parker and Weinmann Arterial Input Functions (AIF) were compared for their ability to best discriminate between tumour and benign tissue. Classifier models were used to determine whether DCE MRI parameters improved tumour detection versus ADC and T2w alone.

RESULTS

All MRI parameters had significantly different data distributions in tumour and benign voxels. For low grade tumours, semi-quantitative DCE MRI parameter time-to-peak (TTP) was the most discriminating and outperformed ADC. For high grade tumours, ADC was the most discriminating followed by DCE MRI parameters Ktrans, the initial rate of enhancement (IRE), then TTP. Quantitative parameters utilising the Parker AIF better distinguished tumour and benign voxel values than the Weinmann AIF. Classifier models including DCE parameters versus T2w and ADC alone, gave detection accuracies of 78% versus 58% for low grade tumours and 85% versus 72% for high grade tumours.

CONCLUSIONS

Incorporating DCE MRI parameters with DWI and T2w gives improved accuracy for tumour detection at a voxel level. DCE MRI parameters should be used to spatially characterise tumour biology for biologically targeted radiation therapy treatment planning.

A novel approach for dose painting radiotherapy of brain metastases guided by mr perfusion images

Purpose

To investigate the feasibility and dosimetric index features of dose painting guided by perfusion heterogeneity for brain metastasis (BMs) patients.

Methods

A total of 50 patients with single BMs were selected for this study. CT and MR simulation images were obtained, including contrast-enhanced T1-weighted images (T1WI+C) and cerebral blood flow (CBF) maps from 3D-arterial spin labeling (ASL). The gross tumor volume (GTV) was determined by fusion of CT and T1WI+C images. Hypoperfused subvolumes (GTVH) with less than 25% of the maximum CBF value were defined as the dose escalation region. The planning target volume (PTV) and PTVH were calculated from GTV and GTVH respectively. The PTVN was obtained by subtracting PTVH from PTV, and conventional dose was given. Three kinds of radiotherapy plans were designed based on the CBF values. Plan 1 was defined as the conventional plan with an arbitrary prescription dose of 60 Gy for PTV. For dose painting, Plan 2 and Plan 3 escalated the prescription dose for PTVH to 72 Gy based on Plan 1, but Plan 3 removed the maximum dose constraint. Dosimetric indices were compared among the three plans.

Results

The mean GTV volume was 34.5 (8.4-118.0) cm3, and mean GTVH volume was 17.0 (4.5-58.3) cm3, accounting for 49.3% of GTV. Both conventional plan and dose painting plans achieved 98% target coverage. The conformity index of PTVH were 0.44 (Plan1), 0.64 and 0.72 (Plan 2 and Plan 3, P&lt;0.05). Compared to Plan 1, the D2%, D98% and Dmean values of the PTVH escalated by 20.50%, 19.32%, and 19.60% in Plan 2 and by 24.88%, 17.22% and 19.22% in Plan 3 respectively (P&lt;0.05). In the three plans, the index of achievement value for PTVH was between 1.01 and 1.03 (P&lt;0.05). The dose increment rates of Plan 2 and Plan 3 for each organs at risk (OARs) was controlled at 2.19% - 5.61% compared with Plan 1. The doses received by OARs did not significantly differ among the three plans (P &gt;0.05).

Conclusions

BMs are associated with significant heterogeneity, and effective escalation of the dose delivered to target subvolumes can be achieved with dose painting guided by 3D-ASL without extra doses to OARs.

Breathing-induced Errors in Quantification and Description of Dominant Intra-Prostatic Lesions (Dils) in PET Images: A Simulation Study by Means of The 4D NCAT Phantom

BACKGROUND

Respiratory movement and the motion range of the diaphragm can affect the quality and quantity of prostate images.

OBJECTIVE

This study aimed to investigate the magnitude of respiratory-induced errors to determine Dominant Intra- prostatic Lesions (DILs) in positron emission tomography (PET) images.

MATERIAL AND METHODS

In this simulation study, we employed the 4D NURBS-based cardiac-torso (4D-NCAT) phantom with a realistic breathing model to simulate the respiratory cycles of a patient to assess the displacement, volume, maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), signal to noise ratio (SNR), and the contrast of DILs in frames within the respiratory cycle.

RESULTS

Respiration in a diaphragm motion resulted in the maximum superior-inferior displacement of 3.9 and 6.1 mm, and the diaphragm motion amplitudes of 20 and 35 mm. In a no-motion image, the volume measurement of DILs had the smallest percentage of errors. Compared with the no-motion method, the percentages of errors in the average method in 20 and 35 mm- diaphragm motion were 25% and 105%, respectively. The motion effect was significantly reduced in terms of the values of SUV_max and SUV_mean in comparison with the values of SUV_max and SUV_mean in no- motion images. The contrast values in respiratory cycle frames were at a range of 3.3-19.2 mm and 6.5-46 for diaphragm movements' amplitudes of 20 and 35 mm.

CONCLUSION

The respiratory movement errors in quantification and delineation of DILs were highly dependent on the range of motion, while the average method was not suitable to precisely delineate DILs in PET/CT in the dose-painting technique.

Evaluation of Dose-Painting in the Dominant Intraprostatic Lesions by Radiobiological Parameters using 68Ga- PSMA PET/CT

BACKGROUND

Patients diagnosed with dominant intraprostatic lesions (DIL) may need radiation doses over than 80 Gy. Dose-painting by contours (DPC) is a useful technique which helps the patients. Dose-painting approach need to be evaluated.

OBJECTIVE

To evaluate the DCP technique in the case of boosting the DILs by radiobiological parameters, tumor control probability (TCP), and normal tissue complication probability (NTCP) via PET/CT images traced by ⁶⁸Ga-PSMA.

MATERIAL AND METHODS

In this analytical study, ⁶⁸Ga-PSMA PET/CT images were obtained from patients with DILs that were delineated using the Fuzzy c-mean (FCM) algorithm and thresholding methods. The protocol of therapy included two phases; at the first phase (ph1), a total dose of 72 Gy in 36 fractions were delivered to the planning target volume (PTV1); the seconds phase consisted of the application of variable doses to the PTV2. Moreover, two concepts were also considered to calculate the TCP using the Zaider-Minerbo model.

RESULTS

The lowest volume in DILs belonged to the DIL1 extracted by the FCM method. According to dose-volume parameters of the rectum and bladder, by the increase in the PTV dose higher than 92 Gy, the amounts of rectum and bladder doses are increased. There was no difference between the TCPs of DILs at doses higher than 86 Gy and 100 Gy for ordinary and high clone density, respectively.

CONCLUSION

Consequently, our dose-painting approach for DILs, extracted by the FCM method via PET/CT images, can reduce the total dose for prostate radiation with 100% tumor control and less normal tissue complications.

Dynamic Characteristics and Predictive Capability of Tumor Voxel Dose-Response Assessed Using 18F-FDG PET/CT Imaging Feedback

Purpose

Tumor voxel dose–response matrix (DRM) can be quantified using feedback from serial FDG-PET/CT imaging acquired during radiotherapy. This study investigated the dynamic characteristics and the predictive capability of DRM.

Methods

FDG-PET/CT images were acquired before and weekly during standard chemoradiotherapy with the treatment dose 2 Gy × 35 from 31 head and neck cancer patients. For each patient, deformable image registration was performed between the pretreatment/baseline PET/CT image and each weekly PET/CT image. Tumor voxel DRM was derived using linear regression on the logarithm of the weekly standard uptake value (SUV) ratios for each tumor voxel, such as SUV measured at a dose level normalized to the baseline SUV₀. The dynamic characteristics were evaluated by comparing the DRM_i estimated using a single feedback image acquired at the ith treatment week (i = 1, 2, 3, or 4) to the DRM estimated using the last feedback image for each patient. The predictive capability of the DRM estimated using 1 or 2 feedback images was evaluated using the receiver operating characteristic test with respect to the treatment outcome of tumor local–regional control or failure.

Results

The mean ± SD of tumor voxel SUV measured at the pretreatment and the 1st, 2nd, 3rd, 4th, and last treatment weeks was 6.76 ± 3.69, 5.72 ± 3.43, 3.85 ± 2.22, 3.27 ± 2.25, 2.5 ± 1.79, and 2.23 ± 1.27, respectively. The deviations between the DRM_i estimated using the single feedback image obtained at the ith week and the last feedback image were 0.86 ± 4.87, −0.06 ± 0.3, −0.09 ± 0.17, and −0.09 ± 0.12 for DRM₁, DRM₂, DRM₃, and DRM₄, respectively. The predictive capability of DRM₃ and DRM₄ was significant (p < 0.001). The area under the curve (AUC) was increased with the increase in treatment dose level. The DRMs constructed using the single feedback image achieved an AUC of 0.86~1. The AUC was slightly improved to 0.94~1 for the DRMs estimated using 2 feedback images.

Conclusion

Tumor voxel metabolic activity measured using FDG-PET/CT fluctuated noticeably during the first 2 treatment weeks and obtained a stabilized reduction rate thereafter. Tumor voxel DRM constructed using a single FDG-PET/CT feedback image after the 2nd treatment week (>20 Gy) has a good predictive capability. The predictive capability improved continuously using a later feedback image and marginally improved when two feedback images were applied.

Radiomics-guided radiation therapy: opportunities and challenges

Radiomics is an advanced image-processing framework, which extracts image features and considers them as biomarkers towards personalized medicine. Applications include disease detection, diagnosis, prognosis, and therapy response assessment/prediction. As radiation therapy aims for further individualized treatments, radiomics could play a critical role in various steps before, during and after treatment. Elucidation of the concept of radiomics-guided radiation therapy (RGRT) is the aim of this review, attempting to highlight opportunities and challenges underlying the use of radiomics to guide clinicians and physicists towards more effective radiation treatments. This work identifies the value of RGRT in various steps of radiotherapy from patient selection to follow-up, and subsequently provides recommendations to improve future radiotherapy using quantitative imaging features.

Hydrogen-Bonds Mediated Nanomedicine: Design, Synthesis and Applications

Among the various challenges in medicine, diagnosis, complete cure and healing of cancers remain difficult given the heterogeneity and complexity of such disease. Differing from conventional platforms with often unsatisfactory theranostic capabilities, the contribution of supramolecular interactions, such as hydrogen-bonds (H-bonds), to cancer nanotheranostics opens new perspectives for the design of biomedical materials, exhibiting remarkable properties and easier processability. Thanks to their dynamic characteristics, a feature generally observed for non-covalent interactions, H-bonding (macro)molecules can be used as supramolecular motifs for yielding drug- and diagnostic carriers that possess attractive features, arising from the combination of assembled nanoplatforms and the responsiveness of H-bonds. Thus H-bonded nanomedicine provides a rich toolbox that is useful to fulfill biomedical needs with unique advantages in early-stage diagnosis and therapy, demonstrating the promising potential in clinical translations and applications. We here summarize the design and synthetic routes towards H-bonded nanomedicines, focus on the growing understanding of the structure-function relationship for efficient cancer treatment. We propose a guidance for designing new H-bonded intelligent theranostic agents, to inspire more successful explorations of cancer nanotheranostics and finally to promote potential clinical translations. This article is protected by copyright. All rights reserved.

Clinical Feasibility Study of Gold Nanoparticles as Theragnostic Agents for Precision Radiotherapy

Background: Gold nanoparticles (AuNP) may be useful in precision radiotherapy and disease monitoring as theragnostic agents. In diagnostics, they can be detected by computerized tomography (CT) because of their higher atomic number. AuNP may also improve the treatment results in radiotherapy due to a higher cross-section, locally improving the physically absorbed dose. Methods: Key parameters values involved in the use of AuNP were imposed to be optimal in the clinical scenario. Mass concentration of AuNP as an efficient contrast agent in clinical CT was found and implemented in a Monte Carlo simulation method for dose calculation under different proposed therapeutic beams. The radiosensitization effect was determined in irradiated cells with AuNP. Results: an AuNP concentration was found for a proper contrast level and enhanced therapeutic effect under a beam typically used for image-guided therapy and monitoring. This lower energetic proposed beam showed potential use for treatment monitoring in addition to absorbed dose enhancement and higher radiosensitization at the cellular level. Conclusion: the results obtained show the use of AuNP concentration around 20 mg Au·mL⁻¹ as an efficient tool for diagnosis, treatment planning, and monitoring treatment. Simultaneously, the delivered prescription dose provides a higher radiobiological effect on the cancer cell for achieving precision radiotherapy.

Simulation CT-based radiomics for prediction of response after neoadjuvant chemo-radiotherapy in patients with locally advanced rectal cancer

Background

To report on the discriminative ability of a simulation Computed Tomography (CT)-based radiomics signature for predicting response to treatment in patients undergoing neoadjuvant chemo-radiation for locally advanced adenocarcinoma of the rectum.

Methods

Consecutive patients treated at the Universities of Tübingen (from 1/1/07 to 31/12/10, explorative cohort) and Florence (from 1/1/11 to 31/12/17, external validation cohort) were considered in our dual-institution, retrospective analysis. Long-course neoadjuvant chemo-radiation was performed according to local policy. On simulation CT, the rectal Gross Tumor Volume was manually segmented. A feature selection process was performed yielding mineable data through an in-house developed software (written in Python 3.6). Model selection and hyper-parametrization of the model was performed using a fivefold cross validation approach. The main outcome measure of the study was the rate of pathologic good response, defined as the sum of Tumor regression grade (TRG) 3 and 4 according to Dworak’s classification.

Results

Two-hundred and one patients were included in our analysis, of whom 126 (62.7%) and 75 (37.3%) cases represented the explorative and external validation cohorts, respectively. Patient characteristics were well balanced between the two groups. A similar rate of good response to neoadjuvant treatment was obtained in in both cohorts (46% and 54.7%, respectively; p = 0.247). A total of 1150 features were extracted from the planning scans. A 5-metafeature complex consisting of Principal component analysis (PCA)-clusters (whose main components are LHL Grey-Level-Size-Zone: Large Zone Emphasis, Elongation, HHH Intensity Histogram Mean, HLL Run-Length: Run Level Variance and HHH Co-occurence: Cluster Tendency) in combination with 5-nearest neighbour model was the most robust signature. When applied to the explorative cohort, the prediction of good response corresponded to an average Area under the curve (AUC) value of 0.65 ± 0.02. When the model was tested on the external validation cohort, it ensured a similar accuracy, with a slightly lower predictive ability (AUC of 0.63).

Conclusions

Radiomics-based, data-mining from simulation CT scans was shown to be feasible and reproducible in two independent cohorts, yielding fair accuracy in the prediction of response to neoadjuvant chemo-radiation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02053-y.

Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy

Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.

Radiotheranostics - Precision Medicine in Nuclear Medicine and Molecular Imaging

'See what you treat and treat what you see, at a molecular level', could be the motto of theranostics. The concept implies diagnosis (imaging) and treatment of cells (usually cancer) using the same molecule, thus guaranteeing a targeted cytotoxic approach of the imaged tumor cells while sparing healthy tissues. As the brilliant late Sam Gambhir would say, the imaging agent acts like a 'molecular spy' and reveals where the tumoral cells are located and the extent of disease burden (diagnosis). For treatment, the same 'molecular spy' docks to the same tumor cells, this time delivering cytotoxic doses of radiation (treatment). This duality represents the concept of a 'theranostic pair', which follows the scope and fundamental principles of targeted precision and personalized medicine. Although the term theranostic was noted in medical literature in the early 2000s, the principle is not at all new to nuclear medicine. The first example of theranostic dates back to 1941 when Dr. Saul Hertz first applied radioiodine for radionuclide treatment of thyroid cells in patients with hyperthyroidism. Ever since, theranostics has been an integral element of nuclear medicine and molecular imaging. The more we understand tumor biology and molecular pathology of carcinogenesis, including specific mutations and receptor expression profiles, the more specific these 'molecular spies' can be developed for diagnostic molecular imaging and subsequent radionuclide targeted therapy (radiotheranostics). The appropriate selection of the diagnostic and therapeutic radionuclide for the 'theranostic pair' is critical and takes into account not only the type of cytotoxic radiation emission, but also the linear energy transfer (LET), and the physical half-lives. Advances in radiochemistry and radiopharmacy with new radiolabeling techniques and chelators are revolutionizing the field. The landscape of cytotoxic systemic radionuclide treatments has dramatically expanded through the past decades thanks to all these advancements. This article discusses present and promising future theranostic applications for various types of diseases such as thyroid disorders, neuroendocrine tumors (NET), pediatric malignancies, and prostate cancer (PC), and provides an outlook for future perspectives.

Hypoxia Imaging As a Guide for Hypoxia-Modulated and Hypoxia-Activated Therapy

Significance: Oxygen imaging techniques, which can probe the spatiotemporal heterogeneity of tumor oxygenation, could be of significant clinical utility in radiation treatment planning and in evaluating the effectiveness of hypoxia-activated prodrugs. To fulfill these goals, oxygen imaging techniques should be noninvasive, quantitative, and capable of serial imaging, as well as having sufficient temporal resolution to detect the dynamics of tumor oxygenation to distinguish regions of chronic and acute hypoxia. Recent Advances: No current technique meets all these requirements, although all have strengths in certain areas. The current status of positron emission tomography (PET)-based hypoxia imaging, oxygen-enhanced magnetic resonance imaging (MRI), ¹⁹F MRI, and electron paramagnetic resonance (EPR) oximetry are reviewed along with their strengths and weaknesses for planning hypoxia-guided, intensity-modulated radiation therapy and detecting treatment response for hypoxia-targeted prodrugs. Critical Issues: Spatial and temporal resolution emerges as a major concern for these areas along with specificity and quantitative response. Although multiple oxygen imaging techniques have reached the investigative stage, clinical trials to test the therapeutic effectiveness of hypoxia imaging have been limited. Future Directions: Imaging elements of the redox environment besides oxygen by EPR and hyperpolarized MRI may have a significant impact on our understanding of the basic biology of the reactive oxygen species response and may extend treatment possibilities.

Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT

Over the past decade, spectral or dual‐energy CT has gained relevancy, especially in oncological radiology. Nonetheless, its use in the radiotherapy (RT) clinic remains limited. This review article aims to give an overview of the current state of spectral CT and to explore opportunities for applications in RT.

In this article, three groups of benefits of spectral CT over conventional CT in RT are recognized. Firstly, spectral CT provides more information of physical properties of the body, which can improve dose calculation. Furthermore, it improves the visibility of tumors, for a wide variety of malignancies as well as organs‐at‐risk OARs, which could reduce treatment uncertainty. And finally, spectral CT provides quantitative physiological information, which can be used to personalize and quantify treatment.

Investigating the potential of proton therapy for hypoxia-targeted dose escalation in non-small cell lung cancer

BACKGROUND

Hypoxia is known to be prevalent in solid tumors such as non-small cell lung cancer (NSCLC) and reportedly correlates with poor prognostic clinical outcome. PET imaging can provide in-vivo hypoxia measurements to support targeted radiotherapy treatment planning. We explore the potential of proton therapy in performing patient-specific dose escalation and compare it with photon volumetric modulated arc therapy (VMAT).

METHODS

Dose escalation has been calibrated to the patient specific tumor response of ten stage IIb-IIIb NSCLC patients by combining HX4-PET imaging and radiobiological modelling of oxygen enhancement ratio (OER) to target variable tumor hypoxia. In a dose-escalation-by-contour approach, escalated dose levels were simulated to the most hypoxic region of the primary target and its effectiveness in improving loco-regional tumor control was assessed. Furthermore, the impact on normal tissue of proton treatments including dose escalation was evaluated in comparison to the normal tissue complication probability (NTCP) of conventional VMAT plans.

RESULTS

Ignoring regions of tumor hypoxia can cause overestimation of TCP values by up to 10%, which can effectively be recovered on average to within 0.9% of the nominal TCP, using patient-specific dose escalations of up to 22% of the prescribed dose to PET defined hypoxic regions. Despite such dose escalations, the use of protons could also simultaneously reduce mean doses to the heart (- 14.3 Gy_RBE), lung (- 8.3 Gy_RBE), esophagus (- 6.9 Gy_RBE) and spinal cord (- 3.8 Gy) compared to non-escalated VMAT plans. These reductions are predicted to lead to clinically relevant decreases in NTCP for radiation-induced pneumonitis (- 11.3%), high grade heart toxicity (- 7.4%) and esophagitis (- 7.5%).

CONCLUSIONS

This study suggests that the administration of proton therapy for dose escalation to patient specific regions of tumor hypoxia in the treatment of NSCLC can mitigate TCP reduction due to hypoxia-induced radio resistance, while simultaneously reducing NTCP levels even when compared to non-escalated treatments delivered with state-of-the-art photon techniques.

Simulated dose painting of hypoxic sub-volumes in pancreatic cancer stereotactic body radiotherapy

Dose painting of hypoxic tumour sub-volumes using positron-emission tomography (PET) has been shown to improve tumour controlin silicoin several sites, predominantly head and neck and lung cancers. Pancreatic cancer presents a more stringent challenge, given its proximity to critical gastro-intestinal organs-at-risk (OARs), anatomic motion, and impediments to reliable PET hypoxia quantification. A radiobiological model was developed to estimate clonogen survival fraction (SF), using¹⁸F-fluoroazomycin arabinoside PET (FAZA PET) images from ten patients with unresectable pancreatic ductal adenocarcinoma to quantify oxygen enhancement effects. For each patient, four simulated five-fraction stereotactic body radiotherapy (SBRT) plans were generated: (1) a standard SBRT plan aiming to cover the planning target volume with 40 Gy, (2) dose painting plans delivering escalated doses to a maximum of three FAZA-avid hypoxic sub-volumes, (3) dose painting plans with simulated spacer separating the duodenum and pancreatic head, and (4), plans with integrated boosts to geometric contractions of the gross tumour volume (GTV). All plans saturated at least one OAR dose limit. SF was calculated for each plan and sensitivity of SF to simulated hypoxia quantification errors was evaluated. Dose painting resulted in a 55% reduction in SF as compared to standard SBRT; 78% with spacer. Integrated boosts to hypoxia-blind geometric contractions resulted in a 41% reduction in SF. The reduction in SF for dose-painting plans persisted for all hypoxia quantification parameters studied, including registration and rigid motion errors that resulted in shifts and rotations of the GTV and hypoxic sub-volumes by as much as 1 cm and 10 degrees. Although proximity to OARs ultimately limited dose escalation, with estimated SFs (∼10^-5) well above levels required to completely ablate a ∼10 cm³tumour, dose painting robustly reduced clonogen survival when accounting for expected treatment and imaging uncertainties and thus, may improve local response and associated morbidity.

Development of a novel radiotheranostic platform with a DOTA-based trifunctional chelating agent

Radiotheranostics has attracted attention as a powerful strategy for treating cancer patients with precision medicine. We designed and synthesized a novel DOTA-based trifunctional agent, ADIBO-DOTADG-ALB (ADA), which allowed compounds with targeting ligands, radiometals, and an albumin binder to be readily prepared. ADA exhibited promising properties as a theranostic platform.

Treatment Intensification in Locally Advanced/Unresectable NSCLC Through Combined Modality Treatment and Precision Dose Escalation

The best survival for patients with unresectable, locally advanced NSCLC is currently achieved through concurrent chemoradiation followed by durvalumab for a year. Despite the best standard of care treatment, the majority of patients still develop disease recurrence, which could be distant and/or local. Trials continue to try and improve outcomes for patients with unresectable NSCLC, typically through treatment intensification, with the addition of more systemic agents, or more radiation dose to the tumor. Although RTOG 0617 showed that uniform dose escalation across an unselected population of patients undergoing chemoradiation is not beneficial, efforts continue to select patients and tumor subsets that are likely to benefit from dose escalation. This review describes some of the ongoing therapeutic trials in unresectable NSCLC, with an emphasis on quantitative imaging and precision radiation dose escalation.

Positron emission tomography for radiotherapy planning in head and neck cancer: What impact?

PET-computed tomography (CT) plays a growing role to guide target volume delineation for head and neck cancer in radiation oncology. Pretherapeutic [18F]FDG PET-CT adds information to morphological imaging. First, as a whole-body imaging modality, it reveals regional or distant metastases that induce major therapeutic changes in more than 10% of the cases. Moreover, it allows better pathological lymph node selection which improves overall regional control and overall survival. Second, locally, it allows us to define the metabolic tumoral volume, which is a reliable prognostic feature for survival outcome. [18F]FDG PET-CT-based gross tumor volume (GTV) is on average significantly smaller than GTV based on CT. Nevertheless, the overlap is incomplete and more evaluation of composite GTV based on PET and GTV based on CT are needed. However, in clinical practice, the study showed that using GTV PET alone for treatment planning was similar to using GTVCT for local control and dose distribution was better as a dose to organs at risk significantly decreased. In addition to FDG, pretherapeutic PET could give access to different biological tumoral volumes - thanks to different tracers - guiding heterogeneous dose delivery (dose painting concept) to resistant subvolumes. During radiotherapy treatment, follow-up [18F]FDG PET-CT revealed an earlier and more important diminution of GTV than other imaging modality. It may be a valuable support for adaptative radiotherapy as a new treatment plan with a significant impact on dose distribution became possible. Finally, additional studies are required to prospectively validate long-term outcomes and lower toxicity resulting from the use of PET-CT in treatment planning.

Biology-guided radiotherapy: redefining the role of radiotherapy in metastatic cancer

The emerging biological understanding of metastatic cancer and proof-of-concept clinical trials suggest that debulking all gross disease holds great promise for improving patient outcomes. However, ablation of multiple targets with conventional external beam radiotherapy systems is burdensome, which limits investigation and utilization of complete metastatic ablation in the majority of patients with advanced disease. To overcome this logistical hurdle, technical innovation is necessary. Biology-guided radiotherapy (BgRT) is a new external beam radiotherapy delivery modality combining positron emission tomography-computed tomography (PET-CT) with a 6 MV linear accelerator. The key innovation is continuous response of the linear accelerator to outgoing tumor PET emissions with beamlets of radiotherapy at subsecond latency. This allows the deposited dose to track tumors in real time. Multiple new hardware and algorithmic advances further facilitate this low-latency feedback process. By transforming tumors into their own fiducials after intravenous injection of a radiotracer, BgRT has the potential to enable complete metastatic ablation in a manner efficient for a single patient and scalable to entire populations with metastatic disease. Future trends may further enhance the utility of BgRT in the clinic as this technology dovetails with other innovations in radiotherapy, including novel dose painting and fractionation schemes, radiomics, and new radiotracers.

Radiomics for radiation oncologists: are we ready to go?

Radiomics have emerged as an exciting field of research over the past few years, with very wide potential applications in personalised and precision medicine of the future. Radiomics-based approaches are still however limited in daily clinical practice in oncology. This review focus on how radiomics could be incorporated into the radiation therapy pipeline, and globally help the radiation oncologist, from the tumour diagnosis to follow-up after treatment. Radiomics could impact on all steps of the treatment pipeline, once the limitations in terms of robustness and reproducibility are overcome. Major ongoing efforts should be made to collect and share data in the most standardised manner possible.

Effect of uncertainties in quantitative 18 F-FDG PET/CT imaging feedback for intratumoral dose-response assessment and dose painting by number

PURPOSE

Intratumoral dose response can be detected using serial fluoro-2-deoxyglucose-(FDG) positron emission tomography (PET)/computed tomography (CT) imaging feedback during treatment and used to guide adaptive dose painting by number (DPbN). However, to reliably implement this technique, the effect of uncertainties in quantitative PET/CT imaging feedback on tumor voxel dose-response assessment and DPbN needs to be determined and reduced.

METHODS

Three major uncertainties, induced by (a) PET imaging partial volume effect (PVE) and (b) tumor deformable image registration (DIR), and (c) variation of the time interval between FDG injection and PET image acquisition (TI), were determined using serial FDG-PET/CT images acquired during chemoradiotherapy of 18 head and neck cancer patients. PET imaging PVE was simulated using the discrepancy between with and without iterative deconvolution-based PVE corrections. Effect of tumor DIR uncertainty was simulated using the discrepancy between two DIR algorithms, including one with and one without soft-tissue mechanical correction for the voxel displacement. The effect of TI variation was simulated using linear interpolation on the dual-point PET/CT images. Tumor voxel pretreatment metabolic activity (SUV₀ ) and dose-response matrix (DRM) discrepancies induced by each of the three uncertainties were quantified, respectively. Adverse effects of tumor voxel SUV₀ and DRM discrepancies on tumor control probability (TCP) in DPbN were assessed.

RESULTS

Partial volume effect and TI variations of 10 mins induced a mean ± standard deviation (SD) of tumor voxel SUV₀ discrepancies to be -0.7% ± 9.2% and 0% ± 4.8%, respectively. Tumor voxel DRM discrepancies induced by PVE, tumor DIR discrepancy, and TI variations were 0.6% ± 8.9%, 1.7% ± 9.1%, and 0% ± 7%, respectively. Partial volume effect induced SUV₀ and DRM discrepancies correlated significantly with the tumor shape and FDG uptake heterogeneity. Tumor DIR uncertainty-induced DRM discrepancy correlated significantly with the tumor volume and shrinkage during treatment. Among the three uncertainties, PVE dominated the adverse effects on the TCP, with a mean ± SD of TCP reduction to be 12.7% ± 9.8% for all tumors if no compensation was applied for.

CONCLUSIONS

Effect of uncertainties in quantitative FDG-PET/CT imaging feedback on intratumoral dose-response quantification was not negligible. These uncertainties primarily caused by PVE and tumor DIR were highly dependent on individual tumor shape, volume, shrinkage during treatment, and pretreatment SUV heterogeneity, which can be managed individually. The adverse effects of these uncertainties could be minimized by using proper PVE corrections and DIR methods and compensated for in the clinical implementation of DPbN.

Sensitivity analysis of FDG PET tumor voxel cluster radiomics and dosimetry for predicting mid-chemoradiation regional response of locally advanced lung cancer

We investigated the sensitivity of regional tumor response prediction to variability in voxel clustering techniques, imaging features, and machine learning algorithms in 25 patients with locally advanced non-small cell lung cancer (LA-NSCLC) enrolled on the FLARE-RT clinical trial. Metabolic tumor volumes (MTV) from pre-chemoradiation (PETpre) and mid-chemoradiation fluorodeoxyglucose-positron emission tomography (FDG PET) images (PETmid) were subdivided into K-means or hierarchical voxel clusters by standardized uptake values (SUV) and 3D-positions. MTV cluster separability was evaluated by CH index, and morphologic changes were captured by Dice similarity and centroid Euclidean distance. PETpre conventional features included SUVmean, MTV/MTV cluster size, and mean radiation dose. PETpre radiomics consisted of 41 intensity histogram and 3D texture features (PET Oncology Radiomics Test Suite) extracted from MTV or MTV clusters. Machine learning models (multiple linear regression, support vector regression, logistic regression, support vector machines) of conventional features or radiomic features were constructed to predict PETmid response. Leave-one-out-cross-validated root-mean-squared-error (RMSE) for continuous response regression (ΔSUVmean) and area-under-receiver-operating-characteristic-curve (AUC) for binary response classification were calculated. K-means MTV 2-clusters (MTVhi, MTVlo) achieved maximum CH index separability (Friedman p < 0.001). Between PETpre and PETmid, MTV cluster pairs overlapped (Dice 0.70-0.87) and migrated 0.6-1.1 cm. PETmid ΔSUVmean response prediction was superior in MTV and MTVlo (RMSE = 0.17-0.21) compared to MTVhi (RMSE = 0.42-0.52, Friedman p < 0.001). PETmid ΔSUVmean response class prediction performance trended higher in MTVlo (AUC = 0.83-0.88) compared to MTVhi (AUC = 0.44-0.58, Friedman p = 0.052). Models were more sensitive to MTV/MTV cluster regions (Friedman p = 0.026) than feature sets/algorithms (Wilcoxon signed-rank p = 0.36). Top-ranked radiomic features included GLZSM-LZHGE (large-zone-high-SUV), GTSDM-CP (cluster-prominence), GTSDM-CS (cluster-shade) and NGTDM-CNT (contrast). Top-ranked features were consistent between MTVhi and MTVlo cluster pairs but varied between MTVhi-MTVlo clusters, reflecting distinct regional radiomic phenotypes. Variability in tumor voxel cluster response prediction can inform robust radiomic target definition for risk-adaptive chemoradiation in patients with LA-NSCLC. FLARE-RT trial: NCT02773238.

Inter/intra-tumoral dose response variations assessed using FDG-PET/CT feedback images: Impact on tumor control and treatment dose prescription

PURPOSE

To quantify inter/intra-tumoral variations of baseline metabolic activity and dose response. To evaluate their impact on tumor control and treatment dose prescription strategies.

METHODS AND MATERIALS

Tumor voxel baseline metabolic activity, SUV₀, and dose response matrix, DRM, quantified using the pre-treatment and weekly FDG-PET/CT imaging feedback for each of 34 HNSCC patients (25 HPV+ and 9 HVP-) were evaluated. Inter/intra-tumoral variations of tumor voxel (SUV₀, DRM) for each of the HPV- and HPV+ tumor groups were quantified and used to evaluate the variations of individual tumor control probabilities and the efficiency of uniform vs non-uniform treatment dose prescription strategies.

RESULTS

Tumor voxel dose response variation of all tumor voxels assessed using FDG-PET/CT imaging feedback had the mean(CV) = 0.47(47%), which was consistent with those of previously published in vitro tumor clonogenic assay. The HPV- tumors had the mean(CV) dose response, 0.53(49%), significantly larger than those of the HPV+ tumors, 0.45(43%). However, their baseline SUVs were opposite, 6.5(56%) vs 7.7(65%). Comparing to the inter-tumoral variations, both HPV-/+ tumor groups showed larger intra-tumoral variations, (53%, 58%) vs (20%, 31%) for the baseline SUV and (38%, 37%) vs (31%, 21%) for the dose response. Due to the large dose response variations, treatment dose to control the tumor voxels has very broad range with CV of TCD₅₀ = 97% for the HPV- and 67% for the HPV+ tumor group respectively. As a consequence, heterogeneous prescription dose could potentially reduce the treatment integral dose for 92% of the HPV+ tumors and 78% of the HPV- tumors.

CONCLUSIONS

The study demonstrates that tumor dose response assessed using FDG-PET/CT feedback images had a similar distribution to those assessed conventionally using in vitro tumor clonogenic assay. Inter-tumoral dose response variation seems larger for HPV- tumors, but intra-tumoral dose response variations are similar for both HPV groups. These variations cause very large variation on the individual tumor control probability and limit the efficacy of dose escalation and de-escalation in conventional clinical practice. On the other hand, heterogeneous dose prescription guided by metabolic imaging feedback has a potential advantage in radiotherapy.

Application of Radiomics for the Prediction of Radiation-Induced Toxicity in the IMRT Era: Current State-of-the-Art

Normal tissue complication probability (NTCP) models that were formulated in the Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) are one of the pillars in support of everyday’s clinical radiation oncology. Because of steady therapeutic refinements and the availability of cutting-edge technical solutions, the ceiling of organs-at-risk-sparing has been reached for photon-based intensity modulated radiotherapy (IMRT). The possibility to capture heterogeneity of patients and tissues in the prediction of toxicity is still an unmet need in modern radiation therapy. Potentially, a major step towards a wider therapeutic index could be obtained from refined assessment of radiation-induced morbidity at an individual level. The rising integration of quantitative imaging and machine learning applications into radiation oncology workflow offers an unprecedented opportunity to further explore the biologic interplay underlying the normal tissue response to radiation. Based on these premises, in this review we focused on the current-state-of-the-art on the use of radiomics for the prediction of toxicity in the field of head and neck, lung, breast and prostate radiotherapy.

Cherenkov emissions for studying tumor changes during radiation therapy: An exploratory study in domesticated dogs with naturally-occurring cancer

PURPOSE

Real-time monitoring of physiological changes of tumor tissue during radiation therapy (RT) could improve therapeutic efficacy and predict therapeutic outcomes. Cherenkov radiation is a normal byproduct of radiation deposited in tissue. Previous studies in rat tumors have confirmed a correlation between Cherenkov emission spectra and optical measurements of blood-oxygen saturation based on the tissue absorption coefficients. The purpose of this study is to determine if it is feasible to image Cherenkov emissions during radiation therapy in larger human-sized tumors of pet dogs with cancer. We also wished to validate the prior work in rats, to determine if Cherenkov emissions have the potential to act an indicator of blood-oxygen saturation or water-content changes in the tumor tissue-both of which have been correlated with patient prognosis.

METHODS

A DoseOptics camera, built to image the low-intensity emission of Cherenkov radiation, was used to measure Cherenkov intensities in a cohort of cancer-bearing pet dogs during clinical irradiation. Tumor type and location varied, as did the radiation fractionation scheme and beam arrangement, each planned according to institutional standard-of-care. Unmodulated radiation was delivered using multiple 6 MV X-ray beams from a clinical linear accelerator. Each dog was treated with a minimum of 16 Gy total, in ≥3 fractions. Each fraction was split into at least three subfractions per gantry angle. During each subfraction, Cherenkov emissions were imaged.

RESULTS

We documented significant intra-subfraction differences between the Cherenkov intensities for normal tissue, whole-tumor tissue, tissue at the edge of the tumor and tissue at the center of the tumor (p<0.05). Additionally, intra-subfraction changes suggest that Cherenkov emissions may have captured fluctuating absorption properties within the tumor.

CONCLUSION

Here we demonstrate that it is possible to obtain Cherenkov emissions from canine cancers within a fraction of radiotherapy. The entire optical spectrum was obtained which includes the window for imaging changes in water and hemoglobin saturation. This lends credence to the goal of using this method during radiotherapy in human patients and client-owned pets.

PET and MRI guided adaptive radiotherapy: Rational, feasibility and benefit

Adaptive radiotherapy (ART) corresponds to various replanning strategies aiming to correct for anatomical variations occurring during the course of radiotherapy. The goal of the article was to report the rational, feasibility and benefit of using PET and/or MRI to guide this ART strategy in various tumor localizations. The anatomical modifications defined by scanner taking into account tumour mobility and volume variation are not always sufficient to optimise treatment. The contribution of functional imaging by PET or the precision of soft tissue by MRI makes it possible to consider optimized ART. Today, the most important data for both PET and MRI are for lung, head and neck, cervical and prostate cancers. PET and MRI guided ART appears feasible and safe, however in a very limited clinical experience. Phase I/II studies should be therefore performed, before proposing cost-effectiveness comparisons in randomized trials and before using the approach in routine practice.

Quantification and correction of distortion in diffusion-weighted MRI at 1.5 and 3 T in a muscle-invasive bladder cancer phantom for radiotherapy planning

OBJECTIVE

Limited visibility of post-resection muscle-invasive bladder cancer (MIBC) on CT hinders radiotherapy dose escalation of the residual tumour. Diffusion-weighted MRI (DW-MRI) visualises areas of high tumour burden and is increasingly used within diagnosis and as a biomarker for cancer. DW-MRI could, therefore, facilitate dose escalation, potentially via dose-painting and/or accommodating response. However, the distortion inherent in DW-MRI could limit geometric accuracy. Therefore, this study aims to quantify DW-MRI distortion via imaging of a bladder phantom.

METHODS

A phantom was designed to mimic MIBC and imaged using CT, DW-MRI and T2W-MRI. Fiducial marker locations were compared across modalities and publicly available software was assessed for correction of magnetic susceptibility-related distortion.

RESULTS

Fiducial marker locations on CT and T2W-MRI agreed within 1.2 mm at 3 T and 1.8 mm at 1.5 T. The greatest discrepancy between CT and apparent diffusion coefficient (ADC) maps was 6.3 mm at 3 T, reducing to 1.8 mm when corrected for distortion. At 1.5 T, these values were 3.9 mm and 1.7 mm, respectively.

CONCLUSIONS

Geometric distortion in DW-MRI of a model bladder was initially >6 mm at 3 T and >3 mm at 1.5 T; however, established correction methods reduced this to <2 mm in both cases.

ADVANCES IN KNOWLEDGE

A phantom designed to mimic MIBC has been produced and used to show distortion in DW-MRI can be sufficiently mitigated for incorporation into the radiotherapy pathway. Further investigation is therefore warranted to enable individually adaptive image-guided radiotherapy of MIBC based upon DW-MRI.

Radiotheranostics: a roadmap for future development

Radiotheranostics, injectable radiopharmaceuticals with antitumour effects, have seen rapid development over the past decade. Although some formulations are already approved for human use, more radiopharmaceuticals will enter clinical practice in the next 5 years, potentially introducing new therapeutic choices for patients. Despite these advances, several challenges remain, including logistics, supply chain, regulatory issues, and education and training. By highlighting active developments in the field, this Review aims to alert practitioners to the value of radiotheranostics and to outline a roadmap for future development. Multidisciplinary approaches in clinical trial design and therapeutic administration will become essential to the continued progress of this evolving therapeutic approach.

18F-FDG PET/CT Quantitative Parameters and Texture Analysis Effectively Differentiate Endometrial Precancerous Lesion and Early-Stage Carcinoma

Objective:

This study evaluated the metabolic parameters and texture features of fluorodeoxyglucose positron emission tomography–computed tomography (PET/CT) for the diagnosis and differentiation of endometrial atypical hyperplasia (EAH), EAH with field cancerization (FC), and stage 1A endometrial carcinoma (EC 1a).

Materials and Methods:

We retrospectively analyzed the metabolic parameters of PET/CT in 170 patients with diagnoses confirmed by pathology, including 57 cases of EAH (57/170, 33.53%), 45 cases of FC (45/170, 26.47%), and 68 cases of EC 1a (68/170, 40.0%). Then, the texture features of each tumor were extracted and compared with the metabolic parameters and pathological results using nonparametric tests and linear regression analysis. The diagnostic performance was assessed by the area under the curve (AUC) values obtained from receiver operating characteristic analysis.

Results:

There were moderate positive correlations between the PET standardized uptake values (SUVpeak, SUVmax, and SUVmean) and postoperative pathological features with correlation coefficients (r_s) of 0.663, 0.651, and 0.651, respectively (P < .001). Total lesion glycolysis showed relatively low correlation with pathological characteristics (r_s = 0.476), whereas metabolic tumor volume and age showed the weakest correlations (r_s = 0.186 and 0.232, respectively). To differentiate between the diagnosis of EAH and FC, SUVmax displayed the largest AUC of 0.857 (sensitivity, 82.2%; specificity, 84.2%). Five texture features were screened out as Percentile 40, Percentile 45, InverseDifferenceMoment_AllDirection_offset 1, InverseDifferenceMoment_angle 45_offset 4, and ClusterProminence_angle 135_offset 7 (P < .001) by linear model of texture analysis (AUC = 0.851; specificity = 0.692; sensitivity = 0.871). To differentiate between the diagnoses of FC and EC 1a, SUVpeak displayed the largest AUC of 0.715 (sensitivity, 67.6%; specificity, 77.8%), and 2 texture features were identified as Percentile 10 and CP_angle 135_offset 7 (AUC = 0.819; specificity = 0.871; sensitivity = 0.766; P < .001).

Conclusions:

SUVmax and SUVpeak had the highest diagnostic values for EAH, FC, and EC 1a compared with the other tested parameters. SUVmax, Percentile 40, Percentile 45, InverseDifferenceMoment_AllDirection_offset 1, InverseDifferenceMoment_angle 45_offset 4, and ClusterProminence_angle 135_offset 7 distinguished EAH from FC. SUVpeak, Percentile 10, and ClusterProminence_angle 135_offset 7 distinguished FC from EC 1a. This study showed that the addition of texture features provides valuable information for differentiating EAH, FC, and EC 1a diagnoses.

The utility of multiparametric MRI to characterize hypoxic tumor subvolumes in comparison to FMISO PET/CT. Consequences for diagnosis and chemoradiation treatment planning in head and neck cancer

BACKGROUND AND PURPOSE

Hypoxia is an essential metabolic marker that determines chemo- and radiation resistance in head-and-neck squamous cell carcinoma (HNSCC) patients. Our exploratory analysis aimed to identify multiparametric MRI (mpMRI) parameters linked to hypoxia that might be used as surrogate for [¹⁸F]FMISO-PET in diagnosis and chemoradiation treatment (CRT) of HNSCC.

MATERIALS AND METHODS

21 patients undergoing definitive CRT for HNSCC were prospectively imaged with serial [¹⁸F]FMISO-PET and 3 Tesla mpMRI for T1- and T2-weighted and dynamic contrast-enhanced perfusion and diffusion-weighted measurements (k^trans, v_e, k_ep, ADC) in weeks 0, 2 and 5 and FDG-PET in week 0. [¹⁸F]FMISO-PET-derived hypoxic subvolumes (HSV) and complementary non-hypoxic subvolumes (nonHSV) were created for tumor and lymph nodes and projected on the mpMRI scans after PET/MRI co-registration. MpMRI and [¹⁸F]FMISO-PET parameters within HSVs and nonHSVs were statistically compared.

RESULTS

FMISO-PET-based HSVs of the primary tumors on MRI were characterized by lower ADC at all time points (p = 0.012 at baseline; p = 0.015 in week 2) and reduced interstitial space volume fraction v_e and perfusion k^trans at baseline (p = 0.006, p = 0.047) compared to nonHSVs. Hypoxic lymph nodes were characterized by significantly lower ADC values at baseline (p = 0.039), but not at later time points and a reduction in k^trans-based perfusion at week 2 (p = 0.018).

CONCLUSION

MpMRI parameters differ significantly between hypoxic and non-hypoxic tumor regions, defined on FMISO-PET/CT as gold standard and might represent surrogate markers for tumor hypoxia. These findings suggest that mpMRI may be useful in the future as a surrogate modality for hypoxia imaging in order to personalize CRT.

Harnessing data science to advance radiation oncology

Radiation oncology, a major treatment modality in the care of patients with malignant disease, is a technology‐ and computer‐intensive medical specialty. As such, it should lend itself ideally to data science methods, where computer science, statistics, and clinical knowledge are combined to advance state‐of‐the‐art care. Nevertheless, data science methods in radiation oncology research are still in their infancy and successful applications leading to improved patient care remain scarce. Here, we discuss data interoperability issues within and across organizational boundaries that hamper the introduction of big data and data science techniques in radiation oncology. At the semantic level, creating common underlying models and codification of the data, including the use of data elements with standardized definitions, an ontology, remains a work in progress. Methodological issues in data science and in the use of large population‐based health data registries are identified. We show that data science methods and big data cannot replace randomized clinical trials in comparative effectiveness research by reviewing a series of instances where the outcomes of big data analyses and randomized trials are at odds. We also discuss the modern wave of machine learning and artificial intelligence as represented by deep learning and convolutional neural networks. Finally, we identify promising research avenues and remain optimistic that the data sources in radiation oncology can be linked to yield important insights in the near future. We argue that data science will be a valuable complement to, but not a replacement of, the traditional hypothesis‐driven translational research chain and the randomized clinical trials that form the backbone of evidence‐based medicine.

Does multiparametric imaging with 18F-FDG-PET/MRI capture spatial variation in immunohistochemical cancer biomarkers in head and neck squamous cell carcinoma?

Background

The purpose of this study is to test if functional multiparametric imaging with ¹⁸F-FDG-PET/MRI correlates spatially with immunohistochemical biomarker status within a lesion of head and neck squamous cell carcinoma (HNSCC), and also whether a biopsy with the highest FDG uptake was more likely to have the highest PD-L1 expression or the highest percentage of vital tumour cells (VTC) compared with a random biopsy.

Methods

Thirty-one patients with HNSCC were scanned on an integrated PET/MRI scanner with FDG prior to surgery in this prospective study. Imaging was quantified with SUV, ADC and K^trans. A 3D-morphometric MRI scan of the specimen was used to co-register the patient and the specimen scans. All specimens were sectioned in consecutive slices, and slices from six different locations were selected randomly from each tumour. Core biopsies were performed to construct TMA blocks for IHC staining with the ten predefined biomarkers. The spatial correlation was assessed with a partial correlation analysis.

Results

Twenty-eight patients with a total of 33 lesions were eligible for further analysis. There were significant correlations between the three imaging biomarkers and some of the IHC biomarkers. Moreover, a biopsy taken from the most FDG-avid part of the tumour did not have a statistically significantly higher probability of higher PD-L1 expression or VTC, compared with a random biopsy.

Conclusion

We found statistically significant correlations between functional imaging parameters and key molecular cancer markers.

Radiation dose-painting with protons vs. photons for head-and-neck cancer

Background: Dose-painting has recently been investigated in early-phase trials in head-and-neck cancer (HNC) with the aim of improving local tumor control. At the same time proton therapy has been reported as potentially capable of decreasing toxicity. Here, we investigate whether protons could be applied in a dose-painting setting by comparing proton dose distributions with delivered photon plans from a phase-I trial of FDG-PET based dose-painting at our institution.Material and methods: Eleven oropharynx (5), hypopharynx (2) and larynx cancer (4) patients from the recently conducted phase I trial were used for comparison of proton and photon dose-painting techniques. Robust optimization (3.5%/3 mm) was used for proton plans. Plan robustness and difference in dose metrics to targets and organs at risk were evaluated.Results: The proton plans met target dose constraints, while having lower non-target dose than photon plans (body-minus-CTV, mean dose 3.9 Gy vs 7.2 Gy, p = .004). Despite the use of robust proton planning for plan max dose, photon plan max doses were more robust (p = .006). Max dose to medulla, brainstem and mandible were lower in the proton plans, while there was no significant difference in mean dose to submandibular- and parotid glands.Conclusion: Proton dose-painting for HNC seems feasible and can reduce the non-target dose overall, however not significantly to certain organs close to the target, such as the salivary glands. Max dose in proton plans had a lower robustness compared to photons, requiring caution to avoid unintended hot spots in consideration of the risk of mucosal toxicity.

Recent advances of PET imaging in clinical radiation oncology

Radiotherapy and radiation oncology play a key role in the clinical management of patients suffering from oncological diseases. In clinical routine, anatomic imaging such as contrast-enhanced CT and MRI are widely available and are usually used to improve the target volume delineation for subsequent radiotherapy. Moreover, these modalities are also used for treatment monitoring after radiotherapy. However, some diagnostic questions cannot be sufficiently addressed by the mere use standard morphological imaging. Therefore, positron emission tomography (PET) imaging gains increasing clinical significance in the management of oncological patients undergoing radiotherapy, as PET allows the visualization and quantification of tumoral features on a molecular level beyond the mere morphological extent shown by conventional imaging, such as tumor metabolism or receptor expression. The tumor metabolism or receptor expression information derived from PET can be used as tool for visualization of tumor extent, for assessing response during and after therapy, for prediction of patterns of failure and for definition of the volume in need of dose-escalation. This review focuses on recent and current advances of PET imaging within the field of clinical radiotherapy / radiation oncology in several oncological entities (neuro-oncology, head & neck cancer, lung cancer, gastrointestinal tumors and prostate cancer) with particular emphasis on radiotherapy planning, response assessment after radiotherapy and prognostication.

Progress towards Patient-Specific, Spatially-Continuous Radiobiological Dose Prescription and Planning in Prostate Cancer IMRT: An Overview

Advances in imaging have enabled the identification of prostate cancer foci with an initial application to focal dose escalation, with subvolumes created with image intensity thresholds. Through quantitative imaging techniques, correlations between image parameters and tumour characteristics have been identified. Mathematical functions are typically used to relate image parameters to prescription dose to improve the clinical relevance of the resulting dose distribution. However, these relationships have remained speculative or invalidated. In contrast, the use of radiobiological models during treatment planning optimisation, termed biological optimisation, has the advantage of directly considering the biological effect of the resulting dose distribution. This has led to an increased interest in the accurate derivation of radiobiological parameters from quantitative imaging to inform the models. This article reviews the progress in treatment planning using image-informed tumour biology, from focal dose escalation to the current trend of individualised biological treatment planning using image-derived radiobiological parameters, with the focus on prostate intensity-modulated radiotherapy (IMRT).

Adaptive radiotherapy for head and neck cancer

Background

Although there have been dramatic improvements in radiotherapy for head and neck squamous cell carcinoma (HNSCC), including robust intensity modulation and daily image guidance, these advances are not able to account for inherent structural and spatial changes that may occur during treatment. Many sources have reported volume reductions in the primary target, nodal volumes, and parotid glands over treatment, which may result in unintended dosimetric changes affecting the side effect profile and even efficacy of the treatment. Adaptive radiotherapy (ART) is an exciting treatment paradigm that has been developed to directly adjust for these changes.

Main body

Adaptive radiotherapy may be divided into two categories: anatomy-adapted (A-ART) and response-adapted ART (R-ART). Anatomy-adapted ART is the process of re-planning patients based on structural and spatial changes occurring over treatment, with the intent of reducing overdosage of sensitive structures such as the parotids, improving dose homogeneity, and preserving coverage of the target. In contrast, response-adapted ART is the process of re-planning patients based on response to treatment, such that the target and/or dose changes as a function of interim imaging during treatment, with the intent of dose escalating persistent disease and/or de-escalating surrounding normal tissue. The impact of R-ART on local control and toxicity outcomes is actively being investigated in several currently accruing trials.

Conclusions

Anatomy-adapted ART is a promising modality to improve rates of xerostomia and coverage in individuals who experience significant volumetric changes during radiation, while R-ART is currently being studied to assess its utility in either dose escalation of radioresistant disease, or de-intensification of surrounding normal tissue following treatment response. In this paper, we will review the existing literature and recent advances regarding A-ART and R-ART.