Automatic metastatic brain tumor segmentation for stereotactic radiosurgery applications

The objective of this study is to develop an automatic segmentation strategy for efficient and accurate metastatic brain tumor delineation on contrast-enhanced T1-weighted (T1c) magnetic resonance images (MRI) for stereotactic radiosurgery (SRS) applications. The proposed four-step automatic brain metastases segmentation strategy is comprised of pre-processing, initial contouring, contour evolution, and contour triage. First, T1c brain images are preprocessed to remove the skull. Second, an initial tumor contour is created using a multi-scaled adaptive threshold-based bounding box and a super-voxel clustering technique. Third, the initial contours are evolved to the tumor boundary using a regional active contour technique. Fourth, all detected false-positive contours are removed with geometric characterization. The segmentation process was validated on a realistic virtual phantom containing Gaussian or Rician noise. For each type of noise distribution, five different noise levels were tested. Twenty-one cases from the multimodal brain tumor image segmentation (BRATS) challenge dataset and fifteen clinical metastases cases were also included in validation. Segmentation performance was quantified by the Dice coefficient (DC), normalized mutual information (NMI), structural similarity (SSIM), Hausdorff distance (HD), mean value of surface-to-surface distance (MSSD) and standard deviation of surface-to-surface distance (SDSSD). In the numerical phantom study, the evaluation yielded a DC of 0.98  ±  0.01, an NMI of 0.97  ±  0.01, an SSIM of 0.999  ±  0.001, an HD of 2.2  ±  0.8 mm, an MSSD of 0.1  ±  0.1 mm, and an SDSSD of 0.3  ±  0.1 mm. The validation on the BRATS data resulted in a DC of 0.89  ±  0.08, which outperform the BRATS challenge algorithms. Evaluation on clinical datasets gave a DC of 0.86  ±  0.09, an NMI of 0.80  ±  0.11, an SSIM of 0.999  ±  0.001, an HD of 8.8  ±  12.6 mm, an MSSD of 1.5  ±  3.2 mm, and an SDSSD of 1.8  ±  3.4 mm when comparing to the physician drawn ground truth. The result indicated that the developed automatic segmentation strategy yielded accurate brain tumor delineation and presented as a useful clinical tool for SRS applications.

The step-and-shoot IMRT overshooting phenomenon: a novel method to mitigate patient overdosage

The goal of this work is to evaluate the dosimetric impact of an overshooting phenomenon in step‐and‐shoot IMRT delivery, and to demonstrate a novel method to mitigate the issue. Five pelvis IMRT patients treated on Varian 2100C EX linacs with larger than +4.5% phantom ion chamber point‐dose difference relative to planned dose were investigated. For each patient plan, 5 fractions were delivered. DynaLog files were recorded and centi‐MU pulses from dose integrator board for every control point (CP) were counted using a commercial pulse counter. The counter recorded CP MU agrees with DynaLog records, both showing an ~0.6 MU overshoot of the first segment of every beam. The 3D patient dose was recalculated from the counter records and compared to the planned dose, showing that the overshoot resulted in on average 2.05% of PTV D95 error, and 2.49%, 2.61% and 2.45% of D1cc error for rectum, bladder, and bowel, respectively. The initial plans were then modified by inserting a specially designed MLC segment to the start of every beam. The modified plans were also delivered five times. The dose from the modified delivery was calculated using counter recorded CP MU. The corresponding Dx parameters were all within 0.31% from the original plan. IMRT QA results also show a 2.2% improvement in ion chamber point‐dose agreement. The results demonstrate that the proposed plan modification method effectively eliminates the overdosage from the overshooting phenomenon.

PACS number(s): 87.55.Qr, 87.55.km

Developing oxygen-enhanced magnetic resonance imaging as a prognostic biomarker of radiation response

Oxygen-Enhanced Magnetic Resonance Imaging (OE-MRI) techniques were evaluated as potential non-invasive predictive biomarkers of radiation response. Semi quantitative blood-oxygen level dependent (BOLD) and tissue oxygen level dependent (TOLD) contrast, and quantitative responses of relaxation rates (ΔR1 and ΔR2*) to an oxygen breathing challenge during hypofractionated radiotherapy were applied. OE-MRI was performed on subcutaneous Dunning R3327-AT1 rat prostate tumors (n=25) at 4.7 T prior to each irradiation (2F × 15 Gy) to the gross tumor volume. Response to radiation, while inhaling air or oxygen, was assessed by tumor growth delay measured up to four times the initial irradiated tumor volume (VQT). Radiation-induced hypoxia changes were confirmed using a double hypoxia marker assay. Inhaling oxygen during hypofractionated radiotherapy significantly improved radiation response. A correlation was observed between the difference in the 2nd and 1st ΔR1 (ΔΔR1) and VQT for air breathing rats. The TOLD response before the 2nd fraction showed a moderate correlation with VQT for oxygen breathing rats. The correlations indicate useful prognostic factors to predict tumor response to hypofractionation and could readily be applied for patient stratification and personalized radiotherapy treatment planning.

Effective Rat Lung Tumor Model for Stereotactic Body Radiation Therapy

Stereotactic body radiation therapy (SBRT) has found an important role in the treatment of patients with non-small cell lung cancer, demonstrating improvements in dose distribution and even tumor cure rates, particularly for early-stage disease. Despite its emerging clinical efficacy, SBRT has primarily evolved due to advances in medical imaging and more accurate dose delivery, leaving a void in knowledge of the fundamental biological mechanisms underlying its activity. Thus, there is a critical need for the development of orthotropic animal models to further probe the biology associated with high-dose-per-fraction treatment typical of SBRT. We report here on an improved surgically based methodology for generating solitary intrapulmonary nodule tumors, which can be treated with simulated SBRT using the X-RAD 225Cx small animal irradiator and Small Animal RadioTherapy (SmART) Plan treatment system. Over 90% of rats developed solitary tumors in the right lung. Furthermore, the tumor response to radiation was monitored noninvasively via bioluminescence imaging (BLI), and complete ablation of tumor growth was achieved with 36 Gy (3 fractions of 12 Gy each). We report a reproducible, orthotopic, clinically relevant lung tumor model, which better mimics patient treatment regimens. This system can be utilized to further explore the underlying biological mechanisms relevant to SBRT and high-dose-per-fraction radiation exposure and to provide a useful model to explore the efficacy of radiation modifiers in the treatment of non-small cell lung cancer.

Tumor radio-sensitivity assessment by means of volume data and magnetic resonance indices measured on prostate tumor bearing rats

PURPOSE

Radiation therapy is one of the most common treatments in the fight against prostate cancer, since it is used to control the tumor (early stages), to slow its progression, and even to control pain (metastasis). Although many factors (e.g., tumor oxygenation) are known to influence treatment efficacy, radiotherapy doses and fractionation schedules are often prescribed according to the principle "one-fits-all," with little personalization. Therefore, the authors aim at predicting the outcome of radiation therapy a priori starting from morphologic and functional information to move a step forward in the treatment customization.

METHODS

The authors propose a two-step protocol to predict the effects of radiation therapy on individual basis. First, one macroscopic mathematical model of tumor evolution was trained on tumor volume progression, measured by caliper, of eighteen Dunning R3327-AT1 bearing rats. Nine rats inhaled 100% O2 during irradiation (oxy), while the others were allowed to breathe air. Second, a supervised learning of the weight and biases of two feedforward neural networks was performed to predict the radio-sensitivity (target) from the initial volume and oxygenation-related information (inputs) for each rat group (air and oxygen breathing). To this purpose, four MRI-based indices related to blood and tissue oxygenation were computed, namely, the variation of signal intensity ΔSI in interleaved blood oxygen level dependent and tissue oxygen level dependent (IBT) sequences as well as changes in longitudinal ΔR1 and transverse ΔR2(*) relaxation rates.

RESULTS

An inverse correlation of the radio-sensitivity parameter, assessed by the model, was found with respect the ΔR2(*) (-0.65) for the oxy group. A further subdivision according to positive and negative values of ΔR2(*) showed a larger average radio-sensitivity for the oxy rats with ΔR2(*)<0 and a significant difference in the two distributions (p < 0.05). Finally, a leave-one-out procedure yielded a radio-sensitivity error lower than 20% in both neural networks.

CONCLUSIONS

While preliminary, these specific results suggest that subjects affected by the same pathology can benefit differently from the same irradiation modalities and support the usefulness of IBT in discriminating between different responses.

Dosimetric comparison of Acuros XB with collapsed cone convolution/superposition and anisotropic analytic algorithm for stereotactic ablative radiotherapy of thoracic spinal metastases

The aim of this study is to compare the recent Eclipse Acuros XB (AXB) dose calculation engine with the Pinnacle collapsed cone convolution/superposition (CCC) dose calculation algorithm and the Eclipse anisotropic analytic algorithm (AAA) for stereotactic ablative radiotherapy (SAbR) treatment planning of thoracic spinal (T‐spine) metastases using IMRT and VMAT delivery techniques. The three commissioned dose engines (CCC, AAA, and AXB) were validated with ion chamber and EBT2 film measurements utilizing a heterogeneous slab‐geometry water phantom and an anthropomorphic phantom. Step‐and‐shoot IMRT and VMAT treatment plans were developed and optimized for eight patients in Pinnacle, following our institutional SAbR protocol for spinal metastases. The CCC algorithm, with heterogeneity corrections, was used for dose calculations. These plans were then exported to Eclipse and recalculated using the AAA and AXB dose calculation algorithms. Various dosimetric parameters calculated with CCC and AAA were compared to that of the AXB calculations. In regions receiving above 50% of prescription dose, the calculated CCC mean dose is 3.1%–4.1% higher than that of AXB calculations for IMRT plans and 2.8%–3.5% higher for VMAT plans, while the calculated AAA mean dose is 1.5%–2.4% lower for IMRT and 1.2%–1.6% lower for VMAT. Statistically significant differences (p<0.05) were observed for most GTV and PTV indices between the CCC and AXB calculations for IMRT and VMAT, while differences between the AAA and AXB calculations were not statistically significant. For T‐spine SAbR treatment planning, the CCC calculations give a statistically significant overestimation of target dose compared to AXB. AAA underestimates target dose with no statistical significance compared to AXB. Further study is needed to determine the clinical impact of these findings.

PACS number: 87.55.D‐, 87.53.Ly

Breaking bad IMRT QA practice

Agreement between planned and delivered dose distributions for patient-specific quality assurance in routine clinical practice is predominantly assessed utilizing the gamma index method. Several reports, however, fundamentally question current IMRT QA practice due to poor sensitivity and specificity of the standard gamma index implementation. An alternative is to employ dose volume histogram (DVH)-based metrics. An analysis based on the AAPM TG 53 and ESTRO booklet No.7 recommendations for QA of treatment planning systems reveals deficiencies in the current "state of the art" IMRT QA, no matter which metric is selected. The set of IMRT benchmark plans were planned, delivered, and analyzed by following guidance of the AAPM TG 119 report. The recommended point dose and planar dose measurements were obtained using a PinPoint ionization chamber, EDR2 radiographic film, and a 2D ionization chamber array. Gamma index criteria {3% (global), 3 mm} and {3% (local), 3 mm} were used to assess the agreement between calculated and delivered planar dose distributions. Next, the AAPM TG 53 and ESTRO booklet No.7 recommendations were followed by dividing dose distributions into four distinct regions: the high-dose (HD) or umbra region, the high-gradient (HG) or penumbra region, the medium-dose (MD) region, and the low-dose (LD) region. A different gamma passing criteria was defined for each region, i.e., a "divide and conquer" (D&amp;C) gamma method was utilized. The D&amp;C gamma analysis was subsequently tested on 50 datasets of previously treated patients. Measured point dose and planar dose distributions compared favorably with TG 119 benchmark data. For all complex tests, the percentage of points passing the conventional {3% (global), 3 mm} gamma criteria was 97.2% ± 3.2% and 95.7% ± 1.2% for film and 2D ionization chamber array, respectively. By dividing 2D ionization chamber array dose measurements into regions and applying 3mm isodose point distance and variable local point dose difference criteria of 7%, 15%, 25%, and 40% for HD, HG, MD, and LD regions, respectively, a 93.4% ± 2.3% gamma passing rate was obtained. Identical criteria applied using the D&amp;C gamma technique on 50 clinical treatment plans resulted in a 97.9% ± 2.3% gamma passing score. Based on the TG 119 standard, meeting or exceeding the benchmark results would indicate an exemplary IMRT QA program. In contrast to TG 119 analysis, a different scrutiny on the same set of data, which follows the AAPM TG 53 and ESTRO booklet No.7 guidelines, reveals a much poorer agreement between calculated and measured dose distributions with large local point dose differences within different dose regions. This observation may challenge the conventional wisdom that an IMRT QA program is producing acceptable results.

Genome-wide association analysis of radiation resistance in Drosophila melanogaster

Background

Ionizing radiation is genotoxic to cells. Healthy tissue toxicity in patients and radiation resistance in tumors present common clinical challenges in delivering effective radiation therapies. Radiation response is a complex, polygenic trait with unknown genetic determinants. The Drosophila Genetic Reference Panel (DGRP) provides a model to investigate the genetics of natural variation for sensitivity to radiation.

Methods and Findings

Radiation response was quantified in 154 inbred DGRP lines, among which 92 radiosensitive lines and 62 radioresistant lines were classified as controls and cases, respectively. A case-control genome-wide association screen for radioresistance was performed. There are 32 single nucleotide polymorphisms (SNPs) associated with radio resistance at a nominal p<10⁻⁵; all had modest effect sizes and were common variants with the minor allele frequency >5%. All the genes implicated by those SNP hits were novel, many without a known role in radiation resistance and some with unknown function. Variants in known DNA damage and repair genes associated with radiation response were below the significance threshold of p<10⁻⁵ and were not present among the significant hits. No SNP met the genome-wide significance threshold (p = 1.49×10⁻⁷), indicating a necessity for a larger sample size.

Conclusions

Several genes not previously associated with variation in radiation resistance were identified. These genes, especially the ones with human homologs, form the basis for exploring new pathways involved in radiation resistance in novel functional studies. An improved DGRP model with a sample size of at least 265 lines and ideally up to 793 lines is recommended for future studies of complex traits.

Correlations of noninvasive BOLD and TOLD MRI with pO2 and relevance to tumor radiation response

PURPOSE

To examine the potential use of blood oxygenation level dependent (BOLD) and tissue oxygenation level dependent (TOLD) contrast MRI to assess tumor oxygenation and predict radiation response.

METHODS

BOLD and TOLD MRI were performed on Dunning R3327-AT1 rat prostate tumors during hyperoxic gas breathing challenge at 4.7 T. Animals were divided into two groups. In Group 1 (n = 9), subsequent (19) F MRI based on spin lattice relaxation of hexafluorobenzene reporter molecule provided quantitative oximetry for comparison. For Group 2 rats (n = 13) growth delay following a single dose of 30 Gy was compared with preirradiation BOLD and TOLD assessments.

RESULTS

Oxygen (100%O2 ) and carbogen (95%O2 /5%CO2 ) challenge elicited similar BOLD, TOLD and pO2 responses. Strong correlations were observed between BOLD or R2* response and quantitative (19) F pO2 measurements. TOLD response showed a general trend with weaker correlation. Irradiation caused a significant tumor growth delay and tumors with larger changes in TOLD and R1 values upon oxygen breathing exhibited significantly increased tumor growth delay.

CONCLUSION

These results provide further insight into the relationships between oxygen sensitive (BOLD/TOLD) MRI and tumor pO2 . Moreover, a larger increase in R1 response to hyperoxic gas challenge coincided with greater tumor growth delay following irradiation.