Shoot-through proton FLASH irradiation lowers linear energy transfer in organs at risk for neurological tumors and is robust against density variations.

Objective. The goal of the study was to test the hypothesis that shoot-through FLASH proton beams would lead to lower dose-averaged LET (LETD) values in critical organs, while providing at least equal normal tissue sparing as clinical proton therapy plans.Approach. For five neurological tumor patients, pencil beam scanning (PBS) shoot-through plans were made, using the maximum energy of 227 MeV and assuming a hypothetical FLASH protective factor (FPF) of 1.5. The effect of different FPF ranging from 1.2 to 1.8 on the clinical goals were also considered. LETDwas calculated for the clinical plan and the shoot-through plan, applying a 2 Gy total dose threshold (RayStation 8 A/9B and 9A-IonRPG). Robust evaluation was performed considering density uncertainty (±3% throughout entire volume).Main results.Clinical plans showed large LETDvariations compared to shoot-through plans and the maximum LETDin OAR is 1.2-8 times lower for the latter. Although less conformal, shoot-through plans met the same clinical goals as the clinical plans, for FLASH protection factors above 1.4. The FLASH shoot-through plans were more robust to density uncertainties with a maximum OAR D2%increase of 0.6 Gy versus 5.7 Gy in the clinical plans.Significance.Shoot-through proton FLASH beams avoid uncertainties in LETDdistributions and proton range, provide adequate target coverage, meet planning constraints and are robust to density variations.

Clinical benefit of range uncertainty reduction in proton treatment planning based on dual-energy CT for neuro-oncological patients.

OBJECTIVE: Several studies have shown that dual-energy CT (DECT) can lead to improved accuracy for proton range estimation. This study investigated the clinical benefit of reduced range uncertainty, enabled by DECT, in robust optimisation for neuro-oncological patients. METHODS: DECT scans for 27 neuro-oncological patients were included. Commercial software was applied to create stopping-power ratio (SPR) maps based on the DECT scan. Two plans were robustly optimised on the SPR map, keeping the beam and plan settings identical to the clinical plan. One plan was robustly optimised and evaluated with a range uncertainty of 3% (as used clinically; denoted 3%-plan); the second plan applied a range uncertainty of 2% (2%-plan). Both plans were clinical acceptable and optimal. The dose-volume histogram parameters were compared between the two plans. Two experienced neuro-radiation oncologists determined the relevant dose difference for each organ-at-risk (OAR). Moreover, the OAR toxicity levels were assessed. RESULTS: For 24 patients, a dose reduction >0.5/1 Gy (relevant dose difference depending on the OAR) was seen in one or more OARs for the 2%-plan; e.g. for brainstem D0.03cc in 10 patients, and hippocampus D40% in 6 patients. Furthermore, 12 patients had a reduction in toxicity level for one or two OARs, showing a clear benefit for the patient. CONCLUSION: Robust optimisation with reduced range uncertainty allows for reduction of OAR toxicity, providing a rationale for clinical implementation. Based on these results, we have clinically introduced DECT-based proton treatment planning for neuro-oncological patients, accompanied with a reduced range uncertainty of 2%. ADVANCES IN KNOWLEDGE: This study shows the clinical benefit of range uncertainty reduction from 3% to 2% in robustly optimised proton plans. A dose reduction to one or more OARs was seen for 89% of the patients, and 44% of the patients had an expected toxicity level decrease.

Clinical evaluation of two AI models for automated breast cancer plan generation.

BACKGROUND: Artificial intelligence (AI) shows great potential to streamline the treatment planning process. However, its clinical adoption is slow due to the limited number of clinical evaluation studies and because often, the translation of the predicted dose distribution to a deliverable plan is lacking. This study evaluates two different, deliverable AI plans in terms of their clinical acceptability based on quantitative parameters and qualitative evaluation by four radiation oncologists. METHODS: For 20 left-sided node-negative breast cancer patients, treated with a prescribed dose of 40.05 Gy, using tangential beam intensity modulated radiotherapy, two model-based treatment plans were evaluated against the corresponding manual plan. The two models used were an in-house developed U-net model and a vendor-developed contextual atlas regression forest model (cARF). Radiation oncologists evaluated the clinical acceptability of each blinded plan and ranked plans according to preference. Furthermore, a comparison with the manual plan was made based on dose volume histogram parameters, clinical evaluation criteria and preparation time. RESULTS: The U-net model resulted in a higher average and maximum dose to the PTV (median difference 0.37 Gy and 0.47 Gy respectively) and a slightly higher mean heart dose (MHD) (0.01 Gy). The cARF model led to higher average and maximum doses to the PTV (0.30 and 0.39 Gy respectively) and a slightly higher MHD (0.02 Gy) and mean lung dose (MLD, 0.04 Gy). The maximum MHD/MLD difference was ≤ 0.5 Gy for both AI plans. Regardless of these dose differences, 90-95% of the AI plans were considered clinically acceptable versus 90% of the manual plans. Preferences varied between the radiation oncologists. Plan preparation time was comparable between the U-net model and the manual plan (287 s vs 253 s) while the cARF model took longer (471 s). When only considering user interaction, plan generation time was 121 s for the cARF model and 137 s for the U-net model. CONCLUSIONS: Two AI models were used to generate deliverable plans for breast cancer patients, in a time-efficient manner, requiring minimal user interaction. Although the AI plans resulted in slightly higher doses overall, radiation oncologists considered 90-95% of the AI plans clinically acceptable.

Artificial intelligence based treatment planning of radiotherapy for locally advanced breast cancer.

BACKGROUND AND PURPOSE: Treatment planning of radiotherapy for locally advanced breast cancer patients can be a time consuming process. Artificial intelligence based treatment planning could be used as a tool to speed up this process and maintain plan quality consistency. The purpose of this study was to create treatment plans for locally advanced breast cancer patients using a Convolutional Neural Network (CNN). MATERIALS AND METHODS: Data of 60 patients treated for left-sided breast cancer was used with a training, validation and test split of 36/12/12, respectively. The in-house built CNN model was a hierarchically densely connected U-net (HD U-net). The inputs for the HD U-net were 2D distance maps of the relevant regions of interest. Dose predictions, generated by the HD U-net, were used for a mimicking algorithm in order to create clinically deliverable plans. RESULTS: Dose predictions were generated by the HD U-net and mimicked using a commercial treatment planning system. The predicted plans fulfilling all clinical goals while showing small (≤0.5 Gy) statistically significant differences (p < 0.05) in the doses compared to the manual plans. The mimicked plans show statistically significant differences in the average doses for the heart and lung of ≤0.5 Gy and a reduced D2% of all PTVs. In total, ten of the twelve mimicked plans were clinically acceptable. CONCLUSIONS: We created a CNN model which can generate clinically acceptable plans for left-sided locally advanced breast cancer patients. This model shows great potential to speed up the treatment planning process while maintaining consistent plan quality.

Interleaved Mapping of Temperature and Longitudinal Relaxation Rate to Monitor Drug Delivery During Magnetic Resonance-Guided High-Intensity Focused Ultrasound-Induced Hyperthermia.

OBJECTIVES: Magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) is a method to heat lesions noninvasively to a stable, elevated temperature and a well-suited method to induce local hyperthermia (41°C-43°C) in deep-seated tissues. Magnetic Resonance (MR) imaging provides therapy planning on anatomical images and offers temperature feedback based on near-real-time MR thermometry. Although constant acquisition of MR thermometry data is crucial to ensure prolonged hyperthermia, it limits the freedom to perform measurements of other MR parameters, which are of interest during hyperthermia treatments. In image-guided drug delivery applications, co-encapsulation of paramagnetic MR contrast agents with a drug inside temperature-sensitive liposomes (TSLs) allows to visualize hyperthermia-triggered drug delivery through changes of the longitudinal relaxation rate R1. While the drug accumulates in the heated tumor tissue, R1 changes can be used for an estimate of the tumor drug concentration. The main objective of this study was to demonstrate that interleaved MR sequences are able to monitor temperature with an adequate temporal resolution and could give a reasonable estimate of the achieved tumor drug concentration through R1 changes. To this aim, in vitro validation tests and an in vivo proof-of-concept study were performed. MATERIALS AND METHODS: All experiments were performed on a clinical 3-T MR-HIFU system adapted with a preclinical setup. The validity of the R1 values and the temperature maps stability were evaluated in phantom experiments and in ex vivo porcine muscle tissue. In vivo experiments were performed on rats bearing a 9L glioma tumor on their hind limb. All animals (n = 4 HIFU-treated, n = 4 no HIFU) were injected intravenously with TSLs co-encapsulating doxorubicin and gadoteridol as contrast agent. The TSL injection was followed by either 2 times 15 minutes of MR-HIFU-induced hyperthermia or a sham treatment. R1 maps were acquired before, during, and after sonication, using a single slice Inversion Recovery Look-Locker (IR-LL) sequence (field of view [FOV], 50 × 69 mm; in-plane resolution, 0.52 × 0.71 mm; slice thickness, 3 mm; 23 phases of 130 milliseconds; 1 full R1 map every 2 minutes). The R1 maps acquired during treatment were interleaved with 2 perpendicular proton resonance frequency shift (PRFS) MR thermometry slices (dynamic repetition time, 8.6 seconds; FOV, 250 × 250 mm; 1.4 × 1.4 mm in-plane resolution; 4 mm slice thickness). Tumor doxorubicin concentrations were determined fluorometrically. RESULTS: In vitro results showed a slight but consistent overestimation of the measured R1 values compared with calibrated R1 values, regardless whether the R1 was acquired with noninterleaved IR-LL or interleaved. The average treatment cell temperature had a slightly higher temporal standard deviation for the interleaved PRFS sequence compared with the noninterleaved PRFS sequence (0.186°C vs 0.101°C, respectively). The prolonged time in between temperature maps due to the interleaved IR-LL sequence did not degrade the temperature stability during MR-HIFU treatment (Taverage = 40.9°C ± 0.3°C). Upon heat treatment, some tumors showed an R1 increase in a large part of the tumor while other tumors hardly showed any ΔR1. The tumor doxorubicin concentration showed a linear correlation with the average ΔR1 during both sonications (n = 8, Radj = 0.933), which was higher than for the ΔR1 measured after tumor cooldown (averaged for both sonications, n = 8, Radj = 0.877). CONCLUSIONS: The new approach of interleaving different MR sequences was applied to simultaneously acquire R1 maps and PRFS thermometry scans during a feedback-controlled MR-HIFU-induced hyperthermia treatment. Interleaved acquisition did not compromise speed or accuracy of each scan. The ΔR1 acquired during treatment was used to visualize and quantify hyperthermia-triggered release of gadoteridol from TSLs and better reflected the intratumoral doxorubicin concentrations than the ΔR1 measured after cooldown of the tumor, exemplifying the benefit of interleaving R1 maps with temperature maps during drug delivery. Our study serves as an example for interleaved MR acquisition schemes, which introduce a higher flexibility in speed, sequence optimization, and timing.

Thermal combination therapies for local drug delivery by magnetic resonance-guided high-intensity focused ultrasound.

Several thermal-therapy strategies such as thermal ablation, hyperthermia-triggered drug delivery from temperature-sensitive liposomes (TSLs), and combinations of the above were investigated in a rhabdomyosarcoma rat tumor model (n = 113). Magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) was used as a noninvasive heating device with precise temperature control for image-guided drug delivery. For the latter, TSLs were prepared, coencapsulating doxorubicin (dox) and [Gd(HPDO3A)(H2O)], and injected in tumor-bearing rats before MR-HIFU treatment. Four treatment groups were defined: hyperthermia, ablation, hyperthermia followed by ablation, or no HIFU. The intratumoral TSL and dox distribution were analyzed by single-photon emission computed tomography (SPECT)/computed tomography (CT), autoradiography, and fluorescence microscopy. Dox biodistribution was quantified and compared with that of nonliposomal dox. Finally, the treatment efficacy of all heating strategies plus additional control groups (saline, free dox, and Caelyx) was assessed by tumor growth measurements. All HIFU heating strategies combined with TSLs resulted in cellular uptake of dox deep into the interstitial space and a significant increase of tumor drug concentrations compared with a treatment with free dox. Ablation after TSL injection showed [Gd(HPDO3A)(H2O)] and dox release along the tumor rim, mirroring the TSL distribution pattern. Hyperthermia either as standalone treatment or before ablation ensured homogeneous TSL, [Gd(HPDO3A)(H2O)], and dox delivery across the tumor. The combination of hyperthermia-triggered drug delivery followed by ablation showed the best therapeutic outcome compared with all other treatment groups due to direct induction of thermal necrosis in the tumor core and efficient drug delivery to the tumor rim.

Iron(III)-Based Magnetic Resonance-Imageable Liposomal T1 Contrast Agent for Monitoring Temperature-Induced Image-Guided Drug Delivery.

OBJECTIVES: Drug-loaded temperature-sensitive liposomes (TSLs) allow heat-triggered local drug delivery to tumors. When magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) is applied to heat up the tumor, corelease of a drug together with an MR contrast agent (CA) from TSLs allows for indirect imaging of the drug release with MR imaging. However, liposomal encapsulation of commonly used gadolinium (Gd)-based MR CAs leads to prolonged retention times in the liver and spleen, which could lead to a transmetallation and redistribution of Gd to other organs. Therefore, an alternative non-Gd-containing T1-MR CA based on encapsulated Fe-succinyl deferoxamine (Fe-SDFO) is proposed as a safe alternative for similar Gd-based systems in image-guided drug delivery applications. MATERIALS AND METHODS: Temperature-sensitive liposomes were loaded with either doxorubicin or Fe-SDFO. Both systems were characterized in vitro with respect to stability, release kinetics, and MR imaging properties. In an in vivo proof-of-concept study, rats bearing a subcutaneous glioma on their hind limb were injected intravenously with a mixture of TSLs encapsulating doxorubicin or Fe-SDFO. Afterwards, the tumors were subjected to an MR-HIFU treatment (2 × 10-15 minutes at 42°C, n = 5) or a control treatment (n = 5). The release of Fe-SDFO from TSLs was quantified in vivo with R1 maps and correlated with the ex vivo determined tumor doxorubicin concentration. RESULTS: Temperature-sensitive liposomes containing doxorubicin or Fe-SDFO were comparable in diameter and phase transition temperature Tm. Both systems showed a fast release at 42°C and good stability at 37°C. Unheated Fe-SDFO-TSLs displayed an r1 of 0.80 ± 0.01 mMs (T = 37°C, B = 3 T), which increased to 1.35 ± 0.02 mMs after release at 42°C. In MR-HIFU studies, tumor R1 maps showed an average relaxation rate change upon heating of ΔR1 = 0.20 ± 0.04 s. The R1 change across the tumor was not always homogeneous. The doxorubicin uptake in the tumor showed a linear correlation with the induced ΔR1 (Radj = 0.41). CONCLUSIONS: Doxorubicin-loaded and Fe-SDFO-loaded TSLs displayed favorable release and stability characteristics in vitro. An in vivo proof-of-concept study showed the feasibility of monitoring drug release using the newly designed iron(III)-based CA loaded TSLs. The measured R1-contrast change correlated with the amount of doxorubicin delivered to the tumor. Moreover, the pattern of R1 change could elucidate the pattern of drug release across the tumor. This new iron(III)-based liposomal MR CA is a promising alternative to comparable Gd-based systems.

In depth study on thermosensitive liposomes: Optimizing formulations for tumor specific therapy and in vitro to in vivo relations.

In numerous studies, thermosensitive liposomes (TSLs) for local heat-triggered delivery of Doxorubicin (Dox) to tumors have been investigated, with TSLs having different lipid formulations, drug loading methodology and testing procedures. To gain more insight in these parameters, we investigated TSLs with four variable DSPC-DPPC lipid ratios (50, 60, 70 or 80% DPPC and 5 mol% of DSPE-PEG2000) using either ammonium sulfate or a citrate buffer for Dox loading. Ammonium sulfate loading of Dox yielded more stable TSLs than citrate loading. At 37 °C, leakage was unnoticeable for all ammonium sulfate TSLs. At 42 °C, complete release occurred within seconds, except for 50% DPPC TSLs, where slow and incomplete release was observed in vitro but also in vivo using a dorsal skinfold window chamber. In contrast to in vitro assays, blood kinetics studies indicated a burst release of Dox upon injection and higher leakage for all TSLs. In therapeutic studies, hyperthermia in combination with TSLs repressed BFS-1 sarcoma growth. Our study shows that prediction of therapeutic efficacy purely based on differences found in vitro is difficult, instead, parameters obtained from pharmacokinetic studies in vivo, and the exact timing of the delivery protocol need to be taken into account.

89 Zr- and Fe-Labeled Polymeric Micelles for Dual Modality PET and T1 -Weighted MR Imaging.

In this study, a new 89 Zr- and Fe3+ -labeled micelle nanoplatform (89 Zr/Fe-DFO-micelles) for dual modality position emission tomography/magnetic resonance (PET/MR) imaging is investigated. The nanoplatform consists of self-assembling amphiphilic diblock copolymers that are functionalized with 89 Zr-deferoxamine (89 Zr-DFO) and Fe3+ -deferoxamine (Fe-DFO) for PET and MR purposes, respectively. 89 Zr displays favorable PET imaging characteristics with a 3.3 d half-life suitable for imaging long circulating nanoparticles. The nanoparticles are modified with Fe-DFO as MR T1 -contrast label instead of commonly used Gd3+ -based chelates. As these micelles are cleared by liver and spleen, any long term Gd- related toxicity such as nephrogenic systemic fibrosis is avoided. As a proof of concept, an in vivo PET/MR study in mice is presented showing tumor targeting of 89 Zr/Fe-DFO-micelles through the enhanced permeability and retention (EPR) effect of tumors, yielding high tumor-to-blood (10.3 ± 3.6) and tumor-to-muscle (15.3 ± 8.1) ratios at 48 h post injection. In vivo PET images clearly delineate the tumor tissue and show good correspondence with ex vivo biodistribution results. In vivo magnetic resonance imaging (MRI) allows visualization of the intratumoral distribution of the 89 Zr/Fe-DFO-micelles at high resolution. In summary, the 89 Zr/Fe-DFO-micelle nanoparticulate platform allows EPR-based tumor PET/MRI, and, furthermore, holds great potential for PET/MR image guided drug delivery.

Quantitative spectral K-edge imaging in preclinical photon-counting x-ray computed tomography.

OBJECTIVES: The objective of this study was to investigate the feasibility and the accuracy of spectral computed tomography (spectral CT) to determine the tissue concentrations and localization of high-attenuation, iodine-based contrast agents in mice. Iodine tissue concentrations determined with spectral CT are compared with concentrations measured with single-photon emission computed tomography (SPECT) and inductively coupled plasma mass spectrometry (ICP-MS). MATERIALS AND METHODS: All animal procedures were performed according to the US National Institutes of Health principles of laboratory animal care and were approved by the ethical review committee of Maastricht, The Netherlands. Healthy Swiss mice (n = 4) were injected with an iodinated emulsion radiolabeled with indium as multimodal contrast agent for CT and SPECT. The CT and SPECT scans were acquired using a dedicated small-animal SPECT/CT system. Subsequently, scans were performed with a preclinical spectral CT scanner equipped with a photon-counting detector and 6 energy threshold levels. Quantitative data analysis of SPECT and spectral CT scans were obtained using 3-dimensional volumes-of-interest drawing methods. The ICP-MS on dissected organs was performed to determine iodine uptake per organ and was compared with the amounts determined from spectral CT and SPECT. RESULTS: Iodine concentrations obtained with image-processed spectral CT data correlated well with data obtained either with noninvasive SPECT imaging (slope = 0.96, r = 0.75) or with ICP-MS (slope = 0.99, r = 0.89) in tissue samples. CONCLUSIONS: This preclinical proof-of-concept study shows the in vivo quantification of iodine concentrations in tissues using spectral CT. Our multimodal imaging approach with spectral CT and SPECT using radiolabeled iodinated emulsions together with ICP-based quantification allows a direct comparison of all methods. Benchmarked against ICP-MS data, spectral CT in the present implementation shows a slight underestimation of organ iodine concentrations compared with SPECT but with a more narrow distribution. This slight deviation is most likely caused by experimental rather than technical issues.