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SummarySuccess of any needle-based medical procedures depends on accurate placement of the needle at the target location. However, accurate targeting and control of flexible self-actuating (active) needle are challenging. We have developed a shape memory alloy-actuated flexible needle steered by a 3D Cartesian robot and performed a comparative study of four, non-model-based, coordinated control methodologies for the combined robot steering and flexible-needle insertion process for surgical interventions. Investigated four controllers are: proportional–integral–derivative (PID), PID with the cubic of positional error term (PID-P3), static PID sliding mode controller, and robust adaptive PID sliding mode controller (RAPID-SMC). Relative efficacies of these controllers are demonstrated by performing experiements using a tissue-mimicking soft material phantom. Results from experiments have reavealed that RAPID-SMC is superior to other three controllers.

Background: In this study, the utilization rates and survival outcomes of different radiotherapy techniques are compared in prostate cancer (PCa) patients stratified by risk group. Methods: We analyzed an extensive data set of N0, M0, non-surgical PCa patients diagnosed between 2004 and 2015 from the National Cancer Database (NCDB). Patients were grouped into six categories based on RT modality: an intensity-modulated radiation therapy (IMRT) group with brachytherapy (BT) boost, IMRT with/without IMRT boost, proton therapy, stereotactic body radiation therapy (SBRT), low-dose-rate brachytherapy (BT LDR), and high-dose-rate brachytherapy (BT HDR). Patients were also stratified by the National Comprehensive Cancer Network (NCCN) guidelines: low-risk (clinical stage T1–T2a, Gleason Score (GS) ≤ 6, and Prostate-Specific Antigen (PSA) < 10), intermediate-risk (clinical stage T2b or T2c, GS of 7, or PSA of 10–20), and high-risk (clinical stage T3–T4, or GS of 8–10, or PSA > 20). Overall survival (OS) probability was determined using a Kaplan–Meier estimator. Univariate and multivariate analyses were performed by risk group for the six treatment modalities. Results: The most utilized treatment modality for all PCa patients was IMRT (53.1%). Over the years, a steady increase in SBRT utilization was observed, whereas BT HDR usage declined. IMRT-treated patient groups exhibited relatively lower survival probability in all risk categories. A slightly better survival probability was observed for the proton therapy group. Hormonal therapy was used for a large number of patients in all risk groups. Conclusion: This study revealed that IMRT was the most common treatment modality for PCa patients. Brachytherapy, SBRT, and IMRT+BT exhibited similar survival rates, whereas proton showed slightly better overall survival across the three risk groups. However, analysis of the demographics indicates that these differences are at least in part due to selection bias.

Purpose The in vivo dosimetric monitoring in HDR brachytherapy is important for improving patient safety. However, there are very limited options available for clinical application. In this study, we present a new in vivo dose measurement system with a plastic scintillating detector (PSD) for GYN HDR brachytherapy. Methods An FDA approved PSD system, called OARtrac (AngioDynamics, Latham, NY), was used with various applicators for in vivo dose measurements for GYN patients. An institutional workflow was established for the clinical implementation of the dosimetric system. Action levels were proposed based on the measurement and system uncertainty for measurement deviations. From October 2018 to September 2019, a total of 75 measurements (48 fractions) were acquired from 14 patients who underwent HDR brachytherapy using either a multichannel cylinder, Venezia applicator, or Syed-Neblett template. The PSDs were placed in predetermined catheters/channels. A planning CT was acquired for treatment planning in Oncentra (Elekta, Version-4.5.2) TPS. The PSDs were contoured on the CT images, and the PSD D90% values were used as the expected doses for comparison with the measured doses. Results The mean difference from patient measurements was −0.22% ± 5.98%, with 26% being the largest deviation from the expected value (Syed case). Large deviations were observed when detectors were placed in the area where dose rates were less than 1 cGy/s. Conclusions The establishment of clinical workflow for the in vivo dosimetry for both the intracavitary and interstitial GYN HDR brachytherapy will potentially improve the safety of the patient treatment.

We previously demonstrated the safety of doses up to 48 Gy in 4 fractions with stereotactic body radiotherapy (SBRT) in poor surgical candidates with localized renal cell carcinoma (RCC). In an additional expansion cohort, we aimed to assess the safety of further dose escalation to 48-60 Gy in 3 fractions.Patients were required to have localized RCC and be poor surgical candidates due to medical comorbidities. Dose-limiting toxicity (DLT) was defined as acute (180 days) grade ≥3 gastrointestinal/genitourinary toxicity by CTCAEv4. Tumor response was assessed using RECIST 1.1 criteria measurements every 6 months for 3 years and optional percutaneous biopsy.Groups of 4, 4, and 3 patients received 48, 54, and 60 Gy in 3 fractions, respectively from 2012 to 2016. Median follow-up was 34.3 months. Zero DLTs were observed. Acute toxicities were limited to grade 1 fatigue and nausea in 45.5% and 18.1%. Late grade 2+ and grade 3+ possibly treatment-related events occurred in 18.1% and 9.1%, respectively. Three-year local control was 90% by RECIST 1.1 criteria. Five of 5 post-treatment biopsies in the expansion cohort were positive by Hematoxylin and Eosin staining. Three of the 5 patients with positive biopsies have been observed for 1.2-3.9 years without evidence of progression.Dose escalation to 60 Gy in 3 fractions was achieved without DLTs. Favorable local control rates were observed, and the interpretation of post-SBRT biopsies remains uncertain. Further studies comparing SBRT to percutaneous ablation for poor surgical candidates with RCC are warranted.

Multi-modality imaging constitutes a foundation of precision medicine, especially in oncology where reliable and rapid imaging techniques are needed in order to insure adequate diagnosis and treatment. In cervical cancer, precision oncology requires the acquisition of 18F-labelled 2-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET), magnetic resonance (MR), and computed tomography (CT) images. Thereafter, images are co-registered to derive electron density attributes required for FDG-PET attenuation correction and radiation therapy planning. Nevertheless, this traditional approach is subject to MR-CT registration defects, expands treatment expenses, and increases the patient's radiation exposure. To overcome these disadvantages, we propose a new framework for cross-modality image synthesis which we apply on MR-CT image translation for cervical cancer diagnosis and treatment. The framework is based on a conditional generative adversarial network (cGAN) and illustrates a novel tactic that addresses, simplistically but efficiently, the paradigm of vanishing gradient vs. feature extraction in deep learning. Its contributions are summarized as follows: 1) The approach-termed sU-cGAN- uses, for the first time, a shallow U-Net (sU-Net) with an encoder/decoder depth of 2 as generator; 2) sU-cGAN's input is the same MR sequence that is used for radiological diagnosis, i.e. T2-weighted, Turbo Spin Echo Single Shot (TSE-SSH) MR images; 3) Despite limited training data and a single input channel approach, sU-cGAN outperforms other state of the art deep learning methods and enables accurate synthetic CT (sCT) generation. In conclusion, the suggested framework should be studied further in the clinical settings. Moreover, the sU-Net model is worth exploring in other computer vision tasks.

Computed tomography (CT) provides information for diagnosis, PET attenuation correction (AC), and radiation treatment planning (RTP). Disadvantages of CT include poor soft tissue contrast and exposure to ionizing radiation. While MRI can overcome these disadvantages, it lacks the photon absorption information needed for PET AC and RTP. Thus, an intelligent transformation from MR to CT, i.e., the MR-based synthetic CT generation, is of great interest as it would support PET/MR AC and MR-only RTP. Using an MR pulse sequence that combines ultra-short echo time (UTE) and modified Dixon (mDixon), we propose a novel method for synthetic CT generation jointly leveraging prior knowledge as well as partial supervision (SCT-PK-PS for short) on large-field-of-view images that span abdomen and pelvis. Two key machine learning techniques, i.e., the knowledge-leveraged transfer fuzzy c-means (KL-TFCM) and the Laplacian support vector machine (LapSVM), are used in SCT-PK-PS. The significance of our effort is threefold: 1) Using the prior knowledge-referenced KL-TFCM clustering, SCT-PK-PS is able to group the feature data of MR images into five initial clusters of fat, soft tissue, air, bone, and bone marrow. Via these initial partitions, clusters needing to be refined are observed and for each of them a few additionally labeled examples are given as the partial supervision for the subsequent semi-supervised classification using LapSVM; 2) Partial supervision is usually insufficient for conventional algorithms to learn the insightful classifier. Instead, exploiting not only the given supervision but also the manifold structure embedded primarily in numerous unlabeled data, LapSVM is capable of training multiple desired tissue-recognizers; 3) Benefiting from the joint use of KL-TFCM and LapSVM, and assisted by the edge detector filter based feature extraction, the proposed SCT-PK-PS method features good recognition accuracy of tissue types, which ultimately facilitates the good transformation from MR images to CT images of the abdomen-pelvis. Applying the method on twenty subjects' feature data of UTE-mDixon MR images, the average score of the mean absolute prediction deviation (MAPD) of all subjects is 140.72 ± 30.60 HU which is statistically significantly better than the 241.36 ± 21.79 HU obtained using the all-water method, the 262.77 ± 42.22 HU obtained using the four-cluster-partitioning (FCP, i.e., external-air, internal-air, fat, and soft tissue) method, and the 197.05 ± 76.53 HU obtained via the conventional SVM method. These results demonstrate the effectiveness of our method for the intelligent transformation from MR to CT on the body section of abdomen-pelvis.

We propose a practicable method for generating synthetic CT images from modified Dixon (mDixon) MR data for the challenging body section of the abdomen and extending into the pelvis. Attenuation correction is necessary to make quantitatively accurate PET but is problematic withPET/MR scanning as MR data lack the information of photon attenuation. Multiple methods were proposed to generate synthetic CT from MR images. However, due to the challenge to distinguish bone and air in MR signals, most existing methods require advanced MR sequences that entail long acquisition time and have limited availablity. To address this problem, we propose a voxel-oriented method for synthetic CT generation using both the transfer and patch learning (SCG-TPL). The overall framework of SCG-TPL includes three stages. Stage I extracts seven-dimensional texture features from mDixon MR images using the weighted convolutional sum; Stage II enlists the knowledge-leveraged transfer fuzzy c-means (KL-TFCM) clustering as well as the patch learning-oriented semi-supervised LapSVM classification to train multiple candidate four-tissue-type-identifiers (FTTIs); Stage III synthesizes CT for new patients’ mDixon images using the candidate FTTIs and voting principle. The significance of our method is threefold: (1) As the global model for patch learning, guiding by the referenced knowledge, KL-TFCM can credibly initialize MR data with overcoming the individual diversity. As the local complement, LapSVM can adaptively model each patch with low time and labor costs. (2) Jointly using the transfer KL-TFCM clustering and patch learning-oriented LapSVM classification, SCG-TPL is able to output accurate synthetic CT in the abdomen. (3) SCG-TPL synthesizes CT only using easily-obtainable mDixon MR images, which greatly facilitates its clinical practicability. Experimental studies on ten subjects’ mDixon MR data verified the superiority of our proposed method.

Computed tomography (CT) plays key roles in radiotherapy treatment planning and PET attenuation correction (AC). Magnetic resonance (MR) imaging has better soft tissue contrast than CT and has no ionizing radiation but cannot directly provide information about photon interactions with tissue that is needed for radiation treatment planning and AC. Therefore, estimating synthetic CT (sCT) images from corresponding MR images and obviating CT scanning is of great interest, but can be particularly challenging in the abdomen owing to a range of tissue types and physiologic motion. For this purpose, inspired by deep learning, we design a novel generative adversarial network (GAN) model that organically combines ResNet, U-net, and auxiliary classifier-augmented GAN (RU-ACGAN for short). The significance of our effort is three-fold: 1) The combination of ResNet and U-net, instead of only the U-net which was commonly used in existing conditional GAN, is enlisted to constitute the generative network in RU-ACGAN. This has the potential to generate more accurate CT than existing methods. 2) Adding the classifier to the discriminant network makes the training process of the proposed model more stable, and thereby benefits the robustness of sCT estimation. 3) Owing to the delicate architecture, RU-ACGAN is capable of estimating superior sCT using only a limited quantity of training data. The experimental studies on ten subjects’ MR-CT pair images indicate that the proposed RU-ACGAN model can capture the potential, non-linear matching between the MR and CT images, and thus achieves the better performance for sCT estimation for the abdomen than many other existing methods.

IntroductionAdvances in multiparametric MRI (mpMRI) combining anatomic and functional imaging can accurately identify foci of adenocarcinoma within the prostate, offering the possibility of partial gland therapy. We performed tandem prospective pilot trials to investigate the feasibility of focal prostate SBRT (f-SBRT) based on correlating diagnostic mpMRI and biopsies with confirmatory pathology in treatment planning.Materials and MethodsPatients with pathologic focal Gleason 6–7 disease and a corresponding PIRADS 4–5 lesion on mpMRI underwent targeted and comprehensive biopsies using MRI/ultrasound fusion under electromagnetic sensor navigation. After rigorous analysis for imaging biopsy concordance, five of 18 patients were eligible to proceed to f-SBRT. Chi-squared test was used for differences from expected outcomes, and concordance was estimated with binomial distribution theory and Wilson’s method.ResultsSix patients had Gleason 6 and 12 had Gleason 3 + 4 disease (mean PSA: 5.8 ng/ml, range: 2.2–8.4). Absolute concordance was 43.8% (95% CI: 0.20, 0.64). Patterns of discordance included additional sites of ipsilateral disease, bilateral disease, and negative target. Five were upstaged to a new NCCN risk category necessitating treatment escalation. The five patients with concordant pathology completed three-fraction f-SBRT with sparing of the surrounding normal structures (including contralateral neurovascular bundle), with no reported grade 2+ toxicities and favorable PSA responses (mean: 41% decrease).ConclusionsOn our pilot trials of f-SBRT planning using rigorous imaging and pathology concordance, image-guided confirmatory biopsies frequently revealed additional disease, suggesting the need for caution in partial-gland therapy. For truly focal disease, f-SBRT provided excellent dosimetry, minimal toxicity, and encouraging biochemical response. Clinical Trial Registration: www.clinicaltrials.gov, NCT02681614; NCT02163317.

Purpose This study assessed the appropriateness of full parameter addition (FPA) methods with respect to the 3-dimensional deformable dose composite method for evaluating combined external beam radiation therapy (EBRT) and intracavitary brachytherapy (ICBT). Methods and Materials A total of 22 patients who received EBRT and high-dose-rate ICBT were retrospectively evaluated. Split-ring and tandem applicators were used for all patients. Additional interstitial needles were used for 5 patients to supplement the implant. Deformable image registrations were performed to deform the secondary EBRT and ICBT planning computed tomography (CT) images onto the reference CT from the third fraction of ICBT. The Dice similarity coefficient was used to evaluate the quality of deformable registration. Doses were transferred to the reference CT, scaled to the equivalent dose in 2-Gy fractions and combined to create the dose composite. Eight dose-accumulation methods were evaluated and compared. D2cc and D0.1cc for organs at risk were investigated. Results The differences in D2cc for rectum, bladder, sigmoid, and bowel between the FPA method for whole-pelvis EBRT and ICBT, calculated using an old American Brachytherapy Society worksheet (FPA_Eh + I_old) and deformable composite for EBRT with boosts and ICBT (Def_E + B + I) were –2.19 ± 1.37 Gyα/β = 3, –0.64 ± 1.13 Gyα/β = 3, –2.06 ± 2.71 Gyα/β = 3, and –1.59 ± 0.89 Gyα/β = 3, respectively. The differences in D2cc for rectum, bladder, sigmoid, and bowel between the new ABS worksheet (FPA_Eh + B + I_abs) and the Def_E + B + I method were 1.21 ± 1.22 Gy α/β = 3, 1.93 ± 1.38 Gyα/β = 3, 0.72 ± 1.12 Gyα/β = 3, and 1.19 ± 1.46 Gyα/β = 3, respectively. Differences in dose-volume histogram parameter values among Def_E + B + I and other FPA methods were not statistically significant (P > .05). Conclusions Compared with the FPA-based method, deformable registration–based dose composites demonstrated lower OAR D2cc and D0.1cc values; however, the differences were not statistically significant. The current ABS-recommended FPA-based sheet can serve as an acceptable plan evaluation tool for clinical purposes.

PURPOSE: Accurate photon attenuation assessment from MR data remains an unmet challenge in the thorax due to tissue heterogeneity and the difficulty of MR lung imaging. As thoracic tissues encompass the whole physiologic range of photon absorption, large errors can occur when using, for example, a uniform, water‐equivalent or a soft‐tissue‐only approximation. The purpose of this study was to introduce a method for voxel‐wise thoracic synthetic CT (sCT) generation from MR data attenuation correction (AC) for PET/MR or for MR‐only radiation treatment planning (RTP). METHODS: Acquisition: A radial stack‐of‐stars combining ultra‐short‐echo time (UTE) and modified Dixon (mDixon) sequence was optimized for thoracic imaging. The UTE‐mDixon pulse sequence collects MR signals at three TE times denoted as UTE, Echo1, and Echo2. Three‐point mDixon processing was used to reconstruct water and fat images. Bias field correction was applied in order to avoid artifacts caused by inhomogeneity of the MR magnetic field. Analysis: Water fraction and R2* maps were estimated using the UTE‐mDixon data to produce a total of seven MR features, that is UTE, Echo1, Echo2, Dixon water, Dixon fat, Water fraction, and R2*. A feature selection process was performed to determine the optimal feature combination for the proposed automatic, 6‐tissue classification for sCT generation. Fuzzy c‐means was used for the automatic classification which was followed by voxel‐wise attenuation coefficient assignment as a weighted sum of those of the component tissues. Performance evaluation: MR data collected using the proposed pulse sequence were compared to those using a traditional two‐point Dixon approach. Image quality measures, including image resolution and uniformity, were evaluated using an MR ACR phantom. Data collected from 25 normal volunteers were used to evaluate the accuracy of the proposed method compared to the template‐based approach. Notably, the template approach is applicable here, that is normal volunteers, but may not be robust enough for patients with pathologies. RESULTS: The free breathing UTE‐mDixon pulse sequence yielded images with quality comparable to those using the traditional breath holding mDixon sequence. Furthermore, by capturing the signal before T2* decay, the UTE‐mDixon image provided lung and bone information which the mDixon image did not. The combination of Dixon water, Dixon fat, and the Water fraction was the most robust for tissue clustering and supported the classification of six tissues, that is, air, lung, fat, soft tissue, low‐density bone, and dense bone, used to generate the sCT. The thoracic sCT had a mean absolute difference from the template‐based (reference) CT of less than 50 HU and which was better agreement with the reference CT than the results produced using the traditional Dixon‐based data. CONCLUSION: MR thoracic acquisition and analyses have been established to automatically provide six distinguishable tissue types to generate sCT for MR‐based AC of PET/MR and for MR‐only RTP.

Purpose Transrectal ultrasound images are routinely acquired for low dose rate (LDR) prostate brachytherapy dosimetric preplanning (pTRUS), although diagnostic multiparametric magnetic resonance imaging (mpMRI) may serve this purpose as well. We compared the predictive abilities of TRUS vs MRI relative to intraoperative TRUS (iTRUS) to assess the role of mpMRI in brachytherapy preplanning. Materials and methods Retrospective analysis was performed on 32 patients who underwent iTRUS‐guided prostate LDR brachytherapy as either mono‐ or combination therapy. 56.3% had pTRUS‐only volume studies and 43.7% had both 3T‐mpMRI and pTRUS preplanning. MRI was used for preplanning and its image fusion with iTRUS was also used for intraoperative guidance of seed placement. Differences in gland volume, seed number, and activity and procedure time were examined, as well as the identification of lesions suspicious for tumor foci. Pearson correlation coefficient and Fisher's Z test were used to estimate associations between continuous measures. Results There was good correlation of planning volumes between iTRUS and either pTRUS or MRI (r = 0.89, r = 0.77), not impacted by the addition of hormonal therapy (P = 0.65, P = 0.33). Both consistently predicted intraoperative seed number (r = 0.87, r = 0.86). MRI/TRUS fusion did not significantly increase surgical or anesthesia time (P = 0.10, P = 0.46). mpMRI revealed suspicious focal lesions in 11 of 14 cases not visible on pTRUS, that when correlated with histopathology, were incorporated into the plan. Conclusions Relative to pTRUS, MRI yielded reliable preplanning measures, supporting the role of MRI‐only LDR treatment planning. mpMRI carries numerous diagnostic, staging and preplanning advantages that facilitate better patient selection and delivery of novel dose escalation and targeted therapy, with no additional surgical or anesthesia time. Prospective studies assessing its impact on treatment planning and delivery can serve to establish mpMRI as the standard of care in LDR prostate brachytherapy planning.

Background Manual contouring remains the most laborious task in radiation therapy planning and is a major barrier to implementing routine Magnetic Resonance Imaging (MRI) Guided Adaptive Radiation Therapy (MR-ART). To address this, we propose a new artificial intelligence-based, auto-contouring method for abdominal MR-ART modeled after human brain cognition for manual contouring. Methods/Materials Our algorithm is based on two types of information flow, i.e. top-down and bottom-up. Top-down information is derived from simulation MR images. It grossly delineates the object based on its high-level information class by transferring the initial planning contours onto daily images. Bottom-up information is derived from pixel data by a supervised, self-adaptive, active learning based support vector machine. It uses low-level pixel features, such as intensity and location, to distinguish each target boundary from the background. The final result is obtained by fusing top-down and bottom-up outputs in a unified framework through artificial intelligence fusion. For evaluation, we used a dataset of four patients with locally advanced pancreatic cancer treated with MR-ART using a clinical system (MRIdian, Viewray, Oakwood Village, OH, USA). Each set included the simulation MRI and onboard T1 MRI corresponding to a randomly selected treatment session. Each MRI had 144 axial slices of 266 × 266 pixels. Using the Dice Similarity Index (DSI) and the Hausdorff Distance Index (HDI), we compared the manual and automated contours for the liver, left and right kidneys, and the spinal cord. Results The average auto-segmentation time was two minutes per set. Visually, the automatic and manual contours were similar. Fused results achieved better accuracy than either the bottom-up or top-down method alone. The DSI values were above 0.86. The spinal canal contours yielded a low HDI value. Conclusion With a DSI significantly higher than the usually reported 0.7, our novel algorithm yields a high segmentation accuracy. To our knowledge, this is the first fully automated contouring approach using T1 MRI images for adaptive radiotherapy.

Aim: This systematic review summarizes the clinical data on focal therapy (FT) when used alone as definitive therapy for primary prostate cancer (PCa). Methods: The protocol is detailed in the online PROSPERO database, registration No. CRD42014014765. Articles evaluating any form of FT alone as a definitive treatment for PCa in adult male patients were included. Results: Of 10,419 identified articles, 10,401 were excluded, and thus leaving 18 for analysis. In total, 2288 patients were treated using seven modalities. The outcomes of FT in PCa seem to be similar to those observed with whole gland therapy and with fewer side effects. Conclusion: Further research, including prospective randomized trials, is warranted to elucidate the potential advantages of focal radiation techniques for treating PCa. Prospero Registration Number: CRD42014014765.

We propose a new method for generating synthetic CT images from modified Dixon (mDixon) MR data. The synthetic CT is used for attenuation correction (AC) when reconstructing PET data on abdomen and pelvis. While MR does not intrinsically contain any information about photon attenuation, AC is needed in PET/MR systems in order to be quantitatively accurate and to meet qualification standards required for use in many multi-center trials. Existing MR-based synthetic CT generation methods either use advanced MR sequences that have long acquisition time and limited clinical availability or use matching of the MR images from a newly scanned subject to images in a library of MR-CT pairs which has difficulty in accounting for the diversity of human anatomy especially in patients that have pathologies. To address these deficiencies, we present a five-phase interlinked method that uses mDixon MR acquisition and advanced machine learning methods for synthetic CT generation. Both transfer fuzzy clustering and active learning-based classification (TFC-ALC) are used. The significance of our efforts is fourfold: 1) TFC-ALC is capable of better synthetic CT generation than methods currently in use on the challenging abdomen using only common Dixon-based scanning. 2) TFC partitions MR voxels initially into the four groups regarding fat, bone, air, and soft tissue via transfer learning; ALC can learn insightful classifiers, using as few but informative labeled examples as possible to precisely distinguish bone, air, and soft tissue. Combining them, the TFC-ALC method successfully overcomes the inherent imperfection and potential uncertainty regarding the co-registration between CT and MR images. 3) Compared with existing methods, TFC-ALC features not only preferable synthetic CT generation but also improved parameter robustness, which facilitates its clinical practicability. Applying the proposed approach on mDixon-MR data from ten subjects, the average score of the mean absolute prediction deviation (MAPD) was 89.78±8.76 which is significantly better than the 133.17±9.67 obtained using the all-water (AW) method (p=4.11E-9) and the 104.97±10.03 obtained using the four-cluster-partitioning (FCP, i.e., external-air, internal-air, fat, and soft tissue) method (p=0.002). 4) Experiments in the PET SUV errors of these approaches show that TFC-ALC achieves the highest SUV accuracy and can generally reduce the SUV errors to 5% or less. These experimental results distinctively demonstrate the effectiveness of our proposed TFC-ALC method for the synthetic CT generation on abdomen and pelvis using only the commonly-available Dixon pulse sequence.

A novel FDA approved in vivo dosimetry device system using plastic scintillating detectors placed in an endorectal balloon to provide real‐time in vivo dosimetry for prostatic rectal interface was tested for use with stereotactic body radiotherapy (SBRT). The system was used for the first time ever to measure dose during linear accelerator based SBRT. A single patient was treated with a total dose of 36.25 Gy given in 5 fractions. Delivered dose was measured for each treatment with the detectors placed against the anterior rectal wall near the prostate rectal interface. Measured doses showed varying degrees of agreement with computed/ planned doses, with average combined dose found to be within 6% of the expected dose. The variance between measurements is most likely due to uncertainty of the detector location, as well as variation in the placement of a new balloon prior to each fraction. Distance to agreement for the detectors was generally found to be within a few millimeters, which also suggested that the differences in measured and calculated doses were due to positional uncertainty of the detectors during the SBRT, which had sharp dose falloff near the penumbra along the rectal wall. Overall, the use of a real time in vivo dosimeter provided a level of safety and improved confidence in treatment delivery. We are evaluating the device further in an IRB‐approved prospective partial prostate SBRT trial, and believe further clinical investigations are warranted. PACS number(s): 87.53.Bn, 87.53.Ly, 87.55.km

Background Manual contouring for radiation therapy planning remains the most laborious and time consuming part in the radiation therapy workflow. Particularly for cervical cancer, this task is complicated by the complex female pelvic anatomy and the concomitant dependence on 18F-labeled Fluorodeoxyglucose (FDG) positron emission tomography (PET) and magnetic resonance (MR) images. Using deep learning, we propose a new auto-contouring method for FDG-PET/MR based cervical cancer radiation therapy by combining the high level anatomical topography and radiological properties, to the low-level pixel wise deep-learning based semantic segmentation. Materials/methods The proposed method: 1) takes advantage of PET data and left/right anatomical symmetry, creating sub-volumes that are centered on the structures to be contoured. 2) Uses a 3D shallow U-Net (sU-Net) model with an encoder depth of 2.3) Applies the successive training of 3 consecutive sU-Nets in a feed forward strategy. 4) Employs, instead of the usual generalized dice loss function (GDL), a patch dice loss function (PDL) that takes into account the Dice similarity index (DSI) at the level of each training patch. Experimental analysis was conducted on a set of 13 PET/MR images was using a leave-one-out strategy. Results Despite the limited data availability, 5 anatomical structures - the gross tumor volume, bladder, anorectum, and bilateral femurs - were accurately (DSI ​= ​0.78), rapidly (1.9 ​s/structure), and automatically delineated by our algorithm. Overall, PDL achieved a better performance than GDL and DSI was higher for organs at risk (OARs) with solid tissue (e.g. femurs) than for OARs with air-filled soft tissues (e.g. anorectum). Conclusion The presented workflow successfully addresses the challenge of auto-contouring in FDG-PET/MR based cervical cancer. It is expected to expedite the cervical cancer radiation therapy workflow in both, conventional and adaptive radiation therapy settings.

Purpose Generation of synthetic Computed Tomography (sCT) images from Magnetic Resonance (MR) is an imperative, yet not fully resolved task for attenuation correction in Positron Emission Tomography (PET)/MR and treatment planning in MR-only radiation therapy. Herein, we propose a Generative Adversarial Networks (GAN) model to generate quantitatively accurate sCT from Dixon thorax MR data. Materials/methods Paired image sets of Dixon MR and corresponding CT volumes from fourteen subjects were used. In-phase (IP) MR images were registered to the CT images using REGGUI. The resulting deformation field was applied to the three other [opposed-phase (OP), fat, water] MR images. Image processing was implemented in MATLAB 2016b (MathWorks) using COMKAT Image Tool. Manual contouring was performed on the CT images using MIM (version 6.6.10, MIM Software Inc., Cleveland, OH) software, to delineate the left lung, right lung, vertebral body, and spinal cord. The proposed RU-cGAN model incorporates R esNet and U-Net in the generator of a c onditional G AN. Results from Vgg16, Vgg19, and ResNet were used as references for comparison. The four networks were trained using two strategies. In the first, the four Dixon MR images were used as input features. In the second strategy, only fat and water images were used. Results Regardless of whether the input consists of two or four images types, sCT generated using RU- cGAN had the best agreement with the measured CT for all the metrics, having Mean Absolute Prediction Error (MAPE) ​ Conclusion RU-cGAN provides a rapid and accurate method for thorax sCT generation while obviating the bone-specific UTE pulse sequence and only requiring limited training data.

Purpose: MR-based pseudo-CT has an important role in MR-based radiation therapy planning and PET attenuation correction. The purpose of this study is to establish a clinically feasible approach, including image acquisition, correction, and CT formation, for pseudo-CT generation of the brain using a single-acquisition, undersampled ultrashort echo time (UTE)-mDixon pulse sequence. Methods: Nine patients were recruited for this study. For each patient, a 190-s, undersampled, single acquisition UTE-mDixon sequence of the brain was acquired (TE = 0.1, 1.5, and 2.8 ms). A novel method of retrospective trajectory correction of the free induction decay (FID) signal was performed based on point-spread functions of three external MR markers. Two-point Dixon images were reconstructed using the first and second echo data (TE = 1.5 and 2.8 ms). R2∗ images (1/T2∗) were then estimated and were used to provide bone information. Three image features, i.e., Dixon-fat, Dixon-water, and R2∗, were used for unsupervised clustering. Five tissue clusters, i.e., air, brain, fat, fluid, and bone, were estimated using the fuzzy c-means (FCM) algorithm. A two-step, automatic tissue-assignment approach was proposed and designed according to the prior information of the given feature space. Pseudo-CTs were generated by a voxelwise linear combination of the membership functions of the FCM. A low-dose CT was acquired for each patient and was used as the gold standard for comparison. Results: The contrast and sharpness of the FID images were improved after trajectory correction was applied. The mean of the estimated trajectory delay was 0.774 μs (max: 1.350 μs; min: 0.180 μs). The FCM-estimated centroids of different tissue types showed a distinguishable pattern for different tissues, and significant differences were found between the centroid locations of different tissue types. Pseudo-CT can provide additional skull detail and has low bias and absolute error of estimated CT numbers of voxels (−22 ± 29 HU and 130 ± 16 HU) when compared to low-dose CT. Conclusions: The MR features generated by the proposed acquisition, correction, and processing methods may provide representative clustering information and could thus be used for clinical pseudo-CT generation.

Purpose A meta-analysis is presented comparing the overall survival (OS) and local control (LC) rates between penectomy and brachytherapy for penile cancer. Methods and materials A PUBMED search was conducted with the MeSH terms, “penis, penile, cancer, brachytherapy, penectomy, surgery, treatment” in various combinations. Nineteen retrospective studies published between the years 1984–2012, detailing OS and LC were included. Data were collected per Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results A total of 2178 males, median age 61 years, were included with 1505 in the surgery group and 673 in the brachytherapy group. The 5-year OS with surgery was 76% compared with 73% with brachytherapy, odds ratio = 1.17 (0.95–1.44, p = 0.128). Penectomy was associated with a higher 5-year LC rate of 84% compared with 79% with brachytherapy, odds ratio = 1.45 (1.09–1.92, p = 0.009). The organ preservation rate for brachytherapy treatment was 74%. Among the surgery patients in a Stage I/II subset, the 5-year OS and LC was 80% (n = 659) and 86% (n = 390), respectively. Of the 209 early stage patients who received brachytherapy, the 5-year OS was 79% and LC was 84%. Chi-square testing demonstrated no difference for either OS or LC for early stage disease. Conclusions This meta-analysis is limited by the retrospective nature and inherent selection bias of the data. While penectomy provided better control, there was no survival benefit, implying that in most cases failed brachytherapy could be salvaged with surgery. Additionally, in early stage tumors there was no survival or control difference.

Bone metastases are a common clinical problem, affecting many types of cancer patients. The presence of tumor in bone can cause significant morbidity including pain, neurological dysfunction, hypercalcemia, and pathological fracture leading to functional loss. The optimal treatment of a patient with bone metastases depends on many factors, including evaluation of the patient's goals of care, performance status, mechanical stability of the affected bone, life expectancy, and overall extent of disease. Treatment options may include radiotherapy, systemic therapies, surgical stabilization, medical pain management, and radiopharmaceuticals. Ideal management of bone metastases requires a coordinated multidisciplinary approach among diagnostic radiologists, radiation oncologists, medical oncologists, orthopedic surgeons, pain specialists, physiatrists, and palliative care specialists. The American College of Radiology Appropriateness Criteria(®) are evidence-based guidelines for specific clinical conditions that are reviewed every 3 years by a multidisciplinary expert panel. The guidelines development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

Special attention is required in planning and administering radiation therapy to patients with cardiac implantable electronic devices (CIEDs), such as pacemaker and defibrillator. The range of dose to CIEDs that can induce malfunction is large among CIEDs. Clinically significant defects have been reported at dose as low as 0.15 Gy. Therefore, accurate estimation of dose to CIED and dose reduction are both important even if the dose is expected to be less than the often‐used 2‐Gy limit. We investigated the use of bolus in in vivo dosimetry for CIEDs. Solid water phantom measurements of out‐of‐field dose for a 6‐MV beam were performed using parallel plate chamber with and without 1‐ to 2‐cm bolus covering the chamber. In vivo dosimetry at skin surface above the CIED was performed with and without bolus covering the CIED for three patients with the CIED

Purpose To evaluate the role of 3T-MRI–guided adaptive high-dose-rate (HDR) combined intracavitary and interstitial brachytherapy for cervical cancer using a novel intracavitary split-ring (ICSR) applicator adapter. Methods and Materials We retrospectively reviewed all HDR brachytherapy cases from 2013 to 2015 using an ICSR applicator. Initial optimization was performed using 3T multiparametric MRI (mpMRI) series with an applicator in place. The mpMRI series were discretionarily acquired before subsequent fractions for possible target adaptation. When necessary, interstitial needles (ISNs) were inserted through a novel ICSR adapter or freehand. Dosimetric parameters, clinical outcomes, and toxicities were compared between groups. Results Seventeen patients were included, with a mean followup of 32 months. An mpMRI series preceded each initial fraction and 52.9% of patients underwent ≥1 additional pretreatment mpMRI. Among these subsequent fractions, the high-risk clinical target volume was reduced in 80% vs. 41% without pretreatment mpMRI. Five patients had ISN placement (seven insertions) to improve extracervical target coverage. Mean D90 (Gy) per fraction to the high-risk clinical target volume and intermediate-risk clinical target volume with and without an ISN were 7.51 ± 1.07 vs. 6.14 ± 0.52 (p = 0.028) and 6.35 ± 0.75 vs. 5.21 ± 0.49 (p = 0.007), respectively. Mean fractional D2cc (Gy) for organs at risk was comparable. No Grades 3–4 toxicity was reported. Disease-free survival and local control for the ICSR-ISN and ICSR-alone groups were 29.8 months/80.0% and 31.2 months/83.3%, respectively. Conclusions The mpMRI acquisition with ICSR applicator in place immediately before HDR brachytherapy for cervical cancer guided successful adaptive treatment optimization and delivery. Our initial experience with a novel interstitial adapter for the split-ring applicator demonstrated excellent target coverage without compromising organs at risk, resulting in good local control and disease-free survival.

Brachytherapy is one the most effective treatment modalities for both gynecological (GYN) cancer and prostate cancer. The clinical outcome of brachytherapy, both high-dose-rate (HDR) and low-dose-rate (LDR), depends on the precision of the desired or planned dose distribution and delivery. In HDR procedure, the accuracy of reconstruction of catheters or needles (e.g. Syed catheter or Simon-Heyman capsule for GYN or needles for prostate) from CT images can significantly affect the accuracy of dose distribution in the treatment (dosimetric) plan, which can result in unwanted clinical outcome. In current practice, an authorized medical physicist manually reconstructs the catheters or needles for dosimetric plan, which determines the position and dwell time for the radiation source for delivering the prescription dose to the target volume sparing organs at risk (OARs) as much as possible. It is not only challenging but also time consuming for reconstructing all the catheters or needles (ranging 15–20) manually, slice-by-slice in CT images. As shown in Fig. 1, the needles on the right (HDR catheters) have created so much artifacts in CT images that it is almost impossible to reconstruct those applicators (catheters/ needles) manually. Additionally, the reconstruction can be operator dependent and can be inaccurate and inconsistent. In this study, we have investigated the applicability of electromagnetic (EM) sensor-based navigation for fast and accurate reconstruction of HDR catheters and needles.

Purpose To investigate the dosimetric effects due to interfractional changes in catheter position and variation in patient's anatomy during the course of interstitial high-dose-rate (HDR) brachytherapy. Methods and Materials A total of 15 patients with either cervical or vaginal cancer underwent interstitial HDR brachytherapy. Interstitial catheters and fiducials were placed under fluoroscopy and intraoperative 3T MRI to confirm the desired catheter placement for adequate target volume coverage. Single plan was generated from first-fraction CT fused with the MRI and used for all fractions of treatment. CT image was acquired before each treatment and registered to the first-fraction CT. Displacement of fiducials and catheters was calculated for each fraction and its effects on dosimetric parameters such as dose covering 90% for high-risk clinical target volume and intermediate-risk clinical target volume and dose to the 2 cm3 of the volume for bladder, rectum, sigmoid, and bowel were studied. Results Average movements of fiducials and catheters were 1.6 mm (range: 0.1–7.1 mm) and 1.7 mm (range: 0.1–4.5 mm), respectively. Overall, deviation of the delivered dose to the target in each fraction was insignificant for all patients (p-value: 0.66 for high-risk clinical target volume and 0.87 for intermediate-risk clinical target volume). The mean dose to organs at risk showed maximum difference up to 0.9, 2.7, 1.6, and 2.1 Gy for bladder, rectum, sigmoid, and bowel, respectively (p-value: 0.88, 0.34, 0.68, and 0.85 for bladder, rectum, sigmoid, and bowel, respectively). Conclusions The interfractional dosimetric variation for both target and organs at risk was within clinically acceptable limit throughout the entire course of interstitial HDR-Syed brachytherapy. Only 6% of cases performed replanning, which could be readily identified using CT imaging.

This article proposes quantitative analysis tools and digital phantoms to quantify intrinsic errors of deformable image registration (DIR) systems and establish quality assurance (QA) procedures for clinical use of DIR systems utilizing local and global error analysis methods with clinically realistic digital image phantoms. Landmark-based image registration verifications are suitable only for images with significant feature points. To address this shortfall, we adapted a deformation vector field (DVF) comparison approach with new analysis techniques to quantify the results. Digital image phantoms are derived from data sets of actual patient images (a reference image set, R, a test image set, T). Image sets from the same patient taken at different times are registered with deformable methods producing a reference DVFref. Applying DVFref to the original reference image deforms T into a new image R'. The data set, R', T, and DVFref, is from a realistic truth set and therefore can be used to analyze any DIR system and expose intrinsic errors by comparing DVFref and DVFtest. For quantitative error analysis, calculating and delineating differences between DVFs, 2 methods were used, (1) a local error analysis tool that displays deformation error magnitudes with color mapping on each image slice and (2) a global error analysis tool that calculates a deformation error histogram, which describes a cumulative probability function of errors for each anatomical structure. Three digital image phantoms were generated from three patients with a head and neck, a lung and a liver cancer. The DIR QA was evaluated using the case with head and neck.

The purpose of this study was to compare and correlate standardized uptake values (SUV) derived from magnetic resonance attenuation correction (MRAC) with those derived from computed tomography attenuation correction (CTAC) in an oncology patient population.The HIPAA-compliant study was approved by the Internal Review Board and all subjects gave written informed consent prior to inclusion in the study. Forty patients (mean age 61 ± 15.1; 20 male) referred for clinically indicated 2-deoxy-2-[(18)F]fluoro-D-glucose (FDG) positron emission tomography/computed tomography (PET/CT) scans also underwent a PET/magnetic resonance imaging (MRI) examination. MRAC was performed using an automatic three-segment model. Regions of interest were drawn over eight normal structures in order to obtain SUVmax and SUVmean values. Spearman rank correlation coefficients (r) were calculated and two-tailed paired t tests were performed to compare the SUVmax and SUVmean values obtained from CTAC with those from MRAC.The mean time after FDG injection was 66 ± 7 min for PET/CT and 117 ± 15 min for PET/MRI examination. MRAC SUV values were significantly lower than the CTAC SUV values in mediastinal blood pool (p 0.001 for both SUVmax and SUVmean) and liver (p = 0.01 for SUVmean). The MRAC SUV values were significantly higher in bone marrow (p 0.001 for both SUVmax and SUVmean), psoas major muscle (p 0.001 for SUVmax), and left ventricular myocardium (p 0.001 for SUVmax and p = 0.01 for SUVmean). For the other normal structures, no significant difference was observed. When comparing SUV values generated from CTAC versus MRAC, high correlations between CTAC and MRAC were observed in myocardium (r = 0.96/0.97 for SUVmax/mean), liver (r = 0.68 for SUVmax), bone marrow (r = 0.80/0.83 for SUVmax/mean), lung tissue (r = 0.70 for SUVmax), and mediastinal blood pool (r = 0.0.68/.069 for SUVmax/mean). Moderate correlations were found in lung tissue (r = 0.67 for SUV mean), liver (r = 0.66 for SUVmean), fat (r = 0.48/0.53 for SUVmax/mean), psoas major muscle (r = 0.54/0.58 for SUVmax/mean), and iliacus muscle (r = 0.41 for SUVmax). Low correlation was found in iliacus muscle (r = 0.32 for SUVmean).Using the automatic three-segment model, our study showed high correlation for measurement of SUV values obtained from MRAC compared to those from CTAC, as the reference standard. Differences observed between MRAC and CTAC derived SUV values may be attributed to the time-delay between the PET/CT and PET/MRI scans or biologic clearance of radiotracer. Further studies are required to assess SUV measurements when performing different MR attenuation correction techniques.

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Zeff), relative electron density (ρ e), mean excitation energy (I x ), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 s. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency.

To investigate whether combining pulsed high-intensity focused ultrasound (HIFU) with the chemotherapeutic drug bortezomib could improve antitumor activity against murine squamous cell carcinoma (SCC) tumors.All experiments were conducted with animal care and use committee approval. Murine SCC cells were implanted subcutaneously in C3H mice. When tumors reached 100 mm(3), mice were randomized to one of three groups for twice weekly intraperitoneal injections of 1.5 mg of bortezomib per kilogram of body weight, a proteasome inhibitor (n = 10); 1.0 mg/kg bortezomib (n = 11); or a control vehicle (n = 12). Within each group, half of the mice received pulsed HIFU exposure to their tumors immediately prior to each injection. The time for tumors to reach 650 mm(3) was compared among groups. Additional tumors were stained with terminal deoxynucledotidyl transferase-mediated dUTP nick end labeling and CD31 to assess apoptotic index and blood vessel density, respectively.Tumors in the control group, pulsed HIFU and control group, and 1.0 mg/kg of bortezomib alone group reached the size end point in 5.2 days +/- 0.8 (standard deviation), 5.3 days +/- 0.8, and 5.6 days +/- 1.1, respectively. However, pulsed HIFU and 1.0 mg/kg bortezomib increased the time to end point to 9.8 days +/- 2.9 (P.02), not significantly different from the 8.8 days +/- 2.1 in tumors treated with 1.5 mg/kg bortezomib alone (P.05). Combination therapy was also associated with a significantly higher apoptotic index (P.05).Treatment of tumors with pulsed HIFU lowered the threshold level for efficacy of bortezomib, resulting in significant tumor cytotoxicity and growth inhibition at lower dose levels.

Purpose: To determine if pulsed-high intensity focused ultrasound (HIFU) could effectively serve as a source of hyperthermia with thermosensitive liposomes to enhance delivery and efficacy of doxorubicin in tumors. Experimental Design: Comparisons in vitro and in vivo were carried out between non–thermosensitive liposomes (NTSL) and low temperature–sensitive liposomes (LTSL). Liposomes were incubated in vitro over a range of temperatures and durations, and the amount of doxorubicin released was measured. For in vivo experiments, liposomes and free doxorubicin were injected i.v. in mice followed by pulsed-HIFU exposures in s.c. murine adenocarcinoma tumors at 0 and 24 h after administration. Combinations of the exposures and drug formulations were evaluated for doxorubicin concentration and growth inhibition in the tumors. Results: In vitro incubations simulating the pulsed-HIFU thermal dose (42°C for 2 min) triggered release of 50% of doxorubicin from the LTSLs; however, no detectable release from the NTSLs was observed. Similarly, in vivo experiments showed that pulsed-HIFU exposures combined with the LTSLs resulted in more rapid delivery of doxorubicin as well as significantly higher i.t. concentration when compared with LTSLs alone or NTSLs, with or without exposures. Combining the exposures with the LTSLs also significantly reduced tumor growth compared with all other groups. Conclusions: Combining low-temperature heat-sensitive liposomes with noninvasive and nondestructive pulsed-HIFU exposures enhanced the delivery of doxorubicin and, consequently, its antitumor effects. This combination therapy could potentially produce viable clinical strategies for improved targeting and delivery of drugs for treatment of cancer and other diseases.

Metastatic epidural spinal cord compression (MESCC) is an oncologic emergency and if left untreated, permanent paralysis will ensue. The treatment of MESCC is governed by disease, patient, and treatment factors. Patient's preferences and goals of care are to be weighed into the treatment plan. Ideally, a patient with MESCC is evaluated by an interdisciplinary team promptly to determine the urgency of the clinical scenario. Treatment recommendations must take into consideration the risk-benefit profiles of surgical intervention and radiotherapy for the particular individual's circumstance, including neurologic status, performance status, extent of epidural disease, stability of the spine, extra-spinal disease status, and life expectancy. In patients with high spinal instability neoplastic score (SINS) or retropulsion of bone fragments in the spinal canal, surgical intervention should be strongly considered. The rate of development of motor deficits from spinal cord compression may be a prognostic factor for ultimate functional outcome, and should be taken into account when a treatment recommendation is made. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed every three years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.

Imaging purine receptors and adenylate biodistribution in vivo may be of clinical importance not only for the investigation of normal adenylate metabolism but also in pathological conditions where adenylate uptake and/or release from certain tissues and organs may be altered, such as some types of cancer. In order to develop a tracer for positron emission tomography (PET) that would not be subject to loss of its radioisotope, adenosine 5'-monophosphate (AMP) was intrinsically labeled at the C-8 position with carbon-11.[11C]AMP was synthesized by reacting 5-amino-1-beta-D-ribofuranosylimidazole-4-carboxamidine-5'-phosphate with [11C]formaldehyde. The metabolism of [11C]AMP in human blood was determined in vitro both in the presence and absence of dipyridamole. The ex vivo biodistribution of [11C]AMP and its in vivo dosimetry were determined in normal mice. The effect of dipyridamole on the distribution of [11C]AMP in mice was also determined.[11C]AMP was reliably synthesized in 34 minutes (n = 7) with an average radiochemical yield of 2.4% and an average specific activity of 90.10 GBq/micromol (2435 mCi/micromol) at end of synthesis. In normal mice, the highest uptake of [11C]AMP was in the lungs, blood, and heart. The ex vivo mouse experiments showed that the uptake of 11C radiotracer in the lungs at 60 minutes postinjection was significantly lower for dipyridamole-treated animals than controls. Dosimetry showed that the critical organs for radiation dose burden are kidneys and bladder.Treatment with dipyridamole blocked the red blood cell uptake of extracellular adenosine and therefore its subsequent intracellular conversion to ATP. The biodistribution studies indicate that the tracer has substantial accumulation in the kidneys, lungs, heart, and blood. [11C]AMP is promising as a PET-imaging agent to trace adenylate biology in vivo.

Pluronic block copolymers are non-ionic surfactants with demonstrated sensitizing activity in chemotherapy and hyperthermia in various tumor cell lines. In the current study we investigated the potential activity of Pluronic as a radiosensitizing agent.As a possible mechanism, the effect of Pluronic on Hsp70 and Hsp90 was examined. Gli36 human glioma cells were treated with radiation alone as well as with a combination treatment of Pluronic and radiation.Clonogenic cell survival assays show that Pluronic has an elevated effect on radiosensitization (50% high, p0.01), even with radiation doses as low as 2 Gy. The Hsp90 level was reduced 24 h after the combined treatment in both in vitro and in vivo. Similarly, Hsp70 levels were also decreased 24 h post treatment. When Gli36 cells were exposed to Pluronic before and during irradiation, DNA DSB: double-strand breaks repair was reduced, and elevated apoptosis was also seen in tumor xenografts.Data suggest the potential use of L10 as a radiosensitizer. While the mechanism of sensitization requires additional investigation, the presented results indicate that the effect may be due, in part, to a decrease in Hsp90 and 70 levels and increased DNA damage.