Premature Termination Codons Are Recognized in the Nucleus in A Reading-Frame Dependent Manner

mRNAs containing premature termination codons (PTCs) are known to be degraded via nonsense-mediated mRNA decay (NMD). Unexpectedly, we found that mRNAs containing any type of PTC (UAA, UAG, UGA) are detained in the nucleus whereas their wild-type counterparts are rapidly exported. This retention is strictly reading-frame dependent. Strikingly, our data indicate that translating ribosomes in the nucleus proofread the frame and detect the PTCs in the nucleus. Moreover, the shuttling NMD protein Upf1 specifically associates with PTC+ mRNA in the nucleus and is required for nuclear retention of PTC+ mRNA. Together, our data lead to a working model that PTCs are recognized in the nucleus by translating ribosomes, resulting in recruitment of Upf1, which in turn functions in nuclear retention of PTC+ mRNA. Nuclear PTC recognition adds a new layer of proofreading for mRNA and may be vital for ensuring the extraordinary fidelity required for protein production.

Incorporating cancer stem cells in radiation therapy treatment response modeling and the implication in glioblastoma multiforme treatment resistance

PURPOSE

To perform a preliminary exploration with a simplistic mathematical cancer stem cell (CSC) interaction model to determine whether the tumor-intrinsic heterogeneity and dynamic equilibrium between CSCs and differentiated cancer cells (DCCs) can better explain radiation therapy treatment response with a dual-compartment linear-quadratic (DLQ) model.

METHODS AND MATERIALS

The radiosensitivity parameters of CSCs and DCCs for cancer cell lines including glioblastoma multiforme (GBM), non-small cell lung cancer, melanoma, osteosarcoma, and prostate, cervical, and breast cancer were determined by performing robust least-square fitting using the DLQ model on published clonogenic survival data. Fitting performance was compared with the single-compartment LQ (SLQ) and universal survival curve models. The fitting results were then used in an ordinary differential equation describing the kinetics of DCCs and CSCs in response to 2- to 14.3-Gy fractionated treatments. The total dose to achieve tumor control and the fraction size that achieved the least normal biological equivalent dose were calculated.

RESULTS

Smaller cell survival fitting errors were observed using DLQ, with the exception of melanoma, which had a low α/β = 0.16 in SLQ. Ordinary differential equation simulation indicated lower normal tissue biological equivalent dose to achieve the same tumor control with a hypofractionated approach for 4 cell lines for the DLQ model, in contrast to SLQ, which favored 2 Gy per fraction for all cells except melanoma. The DLQ model indicated greater tumor radioresistance than SLQ, but the radioresistance was overcome by hypofractionation, other than the GBM cells, which responded poorly to all fractionations.

CONCLUSION

The distinct radiosensitivity and dynamics between CSCs and DCCs in radiation therapy response could perhaps be one possible explanation for the heterogeneous intertumor response to hypofractionation and in some cases superior outcome from stereotactic ablative radiation therapy. The DLQ model also predicted the remarkable GBM radioresistance, a result that is highly consistent with clinical observations. The radioresistance putatively stemmed from accelerated DCC regrowth that rapidly restored compartmental equilibrium between CSCs and DCCs.

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning

PURPOSE

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing.

METHODS

To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth.

RESULTS

In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth.

CONCLUSIONS

Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.

Near Real-Time Assessment of Anatomic and Dosimetric Variations for Head and Neck Radiation Therapy via Graphics Processing Unit-based Dose Deformation Framework

PURPOSE

The purpose of this study was to systematically monitor anatomic variations and their dosimetric consequences during intensity modulated radiation therapy (IMRT) for head and neck (H&N) cancer by using a graphics processing unit (GPU)-based deformable image registration (DIR) framework.

METHODS AND MATERIALS

Eleven IMRT H&N patients undergoing IMRT with daily megavoltage computed tomography (CT) and weekly kilovoltage CT (kVCT) scans were included in this analysis. Pretreatment kVCTs were automatically registered with their corresponding planning CTs through a GPU-based DIR framework. The deformation of each contoured structure in the H&N region was computed to account for nonrigid change in the patient setup. The Jacobian determinant of the planning target volumes and the surrounding critical structures were used to quantify anatomical volume changes. The actual delivered dose was calculated accounting for the organ deformation. The dose distribution uncertainties due to registration errors were estimated using a landmark-based gamma evaluation.

RESULTS

Dramatic interfractional anatomic changes were observed. During the treatment course of 6 to 7 weeks, the parotid gland volumes changed up to 34.7%, and the center-of-mass displacement of the 2 parotid glands varied in the range of 0.9 to 8.8 mm. For the primary treatment volume, the cumulative minimum and mean and equivalent uniform doses assessed by the weekly kVCTs were lower than the planned doses by up to 14.9% (P=.14), 2% (P=.39), and 7.3% (P=.05), respectively. The cumulative mean doses were significantly higher than the planned dose for the left parotid (P=.03) and right parotid glands (P=.006). The computation including DIR and dose accumulation was ultrafast (∼45 seconds) with registration accuracy at the subvoxel level.

CONCLUSIONS

A systematic analysis of anatomic variations in the H&N region and their dosimetric consequences is critical in improving treatment efficacy. Nearly real-time assessment of anatomic and dosimetric variations is feasible using the GPU-based DIR framework. Clinical implementation of this technology may enable timely plan adaptation and improved outcome.

Feasibility of magnetic resonance imaging-guided liver stereotactic body radiation therapy: A comparison between modulated tri-cobalt-60 teletherapy and linear accelerator-based intensity modulated radiation therapy

PURPOSE

The purpose of this study was to investigate the dosimetric feasibility of liver stereotactic body radiation therapy (SBRT) using a teletherapy system equipped with 3 rotating (60)Co sources (tri-(60)Co system) and a built-in magnetic resonance imager (MRI). We hypothesized tumor size and location would be predictive of favorable dosimetry with tri-(60)Co SBRT.

METHODS AND MATERIALS

The primary study population consisted of 11 patients treated with SBRT for malignant hepatic lesions whose linear accelerator (LINAC)-based SBRT plans met all mandatory Radiation Therapy Oncology Group (RTOG) 1112 organ-at-risk (OAR) constraints. The secondary study population included 5 additional patients whose plans did not meet the mandatory constraints. Patients received 36 to 60 Gy in 3 to 5 fractions. Tri-(60)Co system SBRT plans were planned with ViewRay system software.

RESULTS

All patients in the primary study population had tri-(60)Co SBRT plans that passed all RTOG constraints, with similar planning target volume coverage and OAR doses to LINAC plans. Mean liver doses and V10Gy to the liver, although easily meeting RTOG 1112 guidelines, were significantly higher with tri-(60)Co plans. When the 5 additional patients were included in a univariate analysis, the tri-(60)Co SBRT plans were still equally able to pass RTOG constraints, although they did have inferior ability to pass more stringent liver and kidney constraints (P < .05). A multivariate analysis found the ability of a tri-(60)Co SBRT plan to meet these constraints depended on lesion location and size. Patients with smaller or more peripheral lesions (as defined by distance from the aorta, chest wall, liver dome, and relative lesion volume) were significantly more likely to have tri-(60)Co plans that spared the liver and kidney as well as LINAC plans did (P < .05).

CONCLUSIONS

It is dosimetrically feasible to perform liver SBRT with a tri-(60)Co system with a built-in MRI. Patients with smaller or more peripheral lesions are more likely to have optimal liver and kidney sparing, with the added benefit of MRI guidance, when receiving tri-(60)Co-based SBRT.

Feasibility of using intermediate x-ray energies for highly conformal extracranial radiotherapy

PURPOSE

To investigate the feasibility of using intermediate energy 2 MV x-rays for extracranial robotic intensity modulated radiation therapy.

METHODS

Two megavolts flattening filter free x-rays were simulated using the Monte Carlo code MCNP (v4c). A convolution/superposition dose calculation program was tuned to match the Monte Carlo calculation. The modeled 2 MV x-rays and actual 6 MV flattened x-rays from existing Varian Linacs were used in integrated beam orientation and fluence optimization for a head and neck, a liver, a lung, and a partial breast treatment. A column generation algorithm was used for the intensity modulation and beam orientation optimization. Identical optimization parameters were applied in three different planning modes for each site: 2, 6 MV, and dual energy 2/6 MV.

RESULTS

Excellent agreement was observed between the convolution/superposition and the Monte Carlo calculated percent depth dose profiles. For the patient plans, overall, the 2/6 MV x-ray plans had the best dosimetry followed by 2 MV only and 6 MV only plans. Between the two single energy plans, the PTV coverage was equivalent but 2 MV x-rays improved organs-at-risk sparing. For the head and neck case, the 2 MV plan reduced lips, mandible, tongue, oral cavity, brain, larynx, left and right parotid gland mean doses by 14%, 8%, 4%, 14%, 24%, 6%, 30% and 16%, respectively. For the liver case, the 2 MV plan reduced the liver and body mean doses by 17% and 18%, respectively. For the lung case, lung V 20, V 10, and V5 were reduced by 13%, 25%, and 30%, respectively. V 10 of heart with 2 MV plan was reduced by 59%. For the partial breast treatment, the 2 MV plan reduced the mean dose to the ipsilateral and contralateral lungs by 27% and 47%, respectively. The mean body dose was reduced by 16%.

CONCLUSIONS

The authors showed the feasibility of using flattening filter free 2 MV x-rays for extracranial treatments as evidenced by equivalent or superior dosimetry compared to 6 MV plans using the same inverse noncoplanar intensity modulated planning method.

Feasibility of extreme dose escalation for glioblastoma multiforme using 4π radiotherapy

Background

Glioblastoma multiforme (GBM) frequently recurs at the same location after radiotherapy. Further dose escalation using conventional methods is limited by normal tissue tolerance. 4π non-coplanar radiotherapy has recently emerged as a new potential method to deliver highly conformal radiation dose using the C-arm linacs. We aim to study the feasibility of very substantial GBM dose escalation while maintaining normal tissue tolerance using 4π.

Methods

11 GBM patients previously treated with volumetric modulated arc therapy (VMAT/RapidArc) on the NovalisTx™ platform to a prescription dose of either 59.4 Gy or 60 Gy were included. All patients were replanned with 30 non-coplanar beams using a 4π radiotherapy platform, which inverse optimizes both beam angles and fluence maps. Four different prescriptions were used including original prescription dose and PTV (4πPTV_PD), 100 Gy to the PTV and GTV (4πPTV_100Gy), 100 Gy to the GTV only while maintaining prescription dose to the rest of the PTV (4πGTV_100Gy), and a 5 mm margin expansion plan (4πPTV_PD+5mm). OARs included in the study are the normal brain (brain – PTV), brainstem, chiasm, spinal cord, eyes, lenses, optical nerves, and cochleae.

Results

The 4π plans resulted in superior dose gradient indices, as indicated by >20% reduction in the R50, compared to the clinical plans. Among all of the 4π cases, when compared to the clinical plans, the maximum and mean doses were significantly reduced (p < 0.05) by a range of 47.01-98.82% and 51.87-99.47%, respectively, or unchanged (p > 0.05) for all of the non-brain OARs. Both the 4πPTV_PD and 4π GTV_100GYplans reduced the mean normal brain mean doses.

Conclusions

4π non-coplanar radiotherapy substantially increases the dose gradient outside of the PTV and better spares critical organs. Dose escalation to 100 Gy to the GTV or additional margin expansion while meeting clinical critical organ dose constraints is feasible. 100 Gy to the PTV result in higher normal brain doses but may be tolerated when delivered in proportionally increased treatment fractions. Therefore, 4π non-coplanar radiotherapy on C-arm gantry may provide an accessible tool to improve the outcome of GBM radiotherapy through extreme dose escalation.

Feasibility of automated pancreas segmentation based on dynamic MRI

OBJECTIVE

MRI-guided radiotherapy is particularly attractive for abdominal targets with low CT contrast. To fully utilize this modality for pancreas tracking, automated segmentation tools are needed. A hybrid gradient, region growth and shape constraint (hGReS) method to segment two-dimensional (2D) upper abdominal dynamic MRI (dMRI) is developed for this purpose.

METHODS

2D coronal dynamic MR images of two healthy volunteers were acquired with a frame rate of 5 frames per second. The regions of interest (ROIs) included the liver, pancreas and stomach. The first frame was used as the source where the centres of the ROIs were manually annotated. These centre locations were propagated to the next dMRI frame. Four-neighborhood region transfer growth was performed from these initial seeds before refinement using shape constraints. RESULTS from hGReS and two other automated segmentation methods using integrated edge detection and region growth (IER) and level set, respectively, were compared with manual contours using Dice's index (DI).

RESULTS

For the first patient, the hGReS resulted in the organ segmentation accuracy as a measure by the DI (0.77) for the pancreas, superior to the level set method (0.72) and IER (0.71). The hGReS was shown to be reproducible on the second subject, achieving a DI of 0.82, 0.92 and 0.93 for the pancreas, stomach and liver, respectively. Motion trajectories derived from the hGReS were highly correlated to respiratory motion.

CONCLUSION

We have shown the feasibility of automated segmentation of the pancreas anatomy on dMRI.

ADVANCES IN KNOWLEDGE

Using the hybrid method improves segmentation robustness of low-contrast images.

Correlation of Clinical and Dosimetric Parameters With Radiographic Lung Injury Following Stereotactic Body Radiotherapy

Radiographic changes occur in over half of patients treated with stereotactic body radiotherapy (SBRT) to the lung, correlating histopathologically with injury. We quantified radiographic density changes (ie, fibrosis) at 3, 6, and 12 months and investigated the relationship between these volumes and clinical and dosimetric parameters. The study population consisted of patients treated with SBRT to the lung for stage I primary lung cancers (n = 39) or oligometastatic lesions (n = 17). Fractionation schemes included 3 fractions of 12, 14, or 18 gray (Gy) and 4 fractions of 12 or 12.5 Gy prescribed to cover 95% of the planning target volume (PTV). Planning computed tomography (CT) scans were rigidly registered to follow-up CT scans obtained at intervals of 3, 6, and 12 months. Fibrotic volumes were contoured on the follow-up scans. Associations between the volume of fibrosis and clinical and dosimetric parameters were investigated using univariate linear regression. Scans were available for 65 and 47 lesions at 6 and 12 months, respectively. Age, years since quitting smoking, and GOLD Global Initiative for Chronic Obstructive Lung Disease score were significantly associated with increasing volume of fibrosis (P < .05). Total dose, dose per fraction, PTV, and volumetric parameters (V0-V55) were also significantly associated with increasing volumes of fibrosis (P < .01). For dosimetric parameters, the effect was largest for V55. Age, significant smoking history, and GOLD score were significantly associated with increasing volumes of fibrosis following SBRT. In a multivariate model adjusted for age and smoking history, V10 through V50 and PTV size remained significant predictors of fibrotic volume. Further, there is a strong dose-response relationship between the volume of lung exposed to a certain dose and the fibrotic volume. The predominant kinetic patterns of fibrosis demonstrate peaking fibrotic volumes at 6 and 12 months. These results provide insight for expectations of fibrosis after SBRT.