Kujtim Latifi

Experimentally studied dynamic dose interplay does not meaningfully affect target dose in VMAT SBRT lung treatments

PURPOSE The effects of respiratory motion on the tumor dose can be divided into the gradient and interplay effects. While the interplay effect is likely to average out over a large number of fractions, it may play a role in hypofractionated [stereotactic body radiation therapy (SBRT)] treatments. This subject has been extensively studied for intensity modulated radiation therapy but less so for volumetric modulated arc therapy (VMAT), particularly in application to hypofractionated regimens. Also, no experimental study has provided full four-dimensional (4D) dose reconstruction in this scenario. The authors demonstrate how a recently described motion perturbation method, with full 4D dose reconstruction, is applied to describe the gradient and interplay effects during VMAT lung SBRT treatments. METHODS VMAT dose delivered to a moving target in a patient can be reconstructed by applying perturbations to the treatment planning system-calculated static 3D dose. Ten SBRT patients treated with 6 MV VMAT beams in five fractions were selected. The target motion (motion kernel) was approximated by 3D rigid body translation, with the tumor centroids defined on the ten phases of the 4DCT. The motion was assumed to be periodic, with the period T being an average from the empirical 4DCT respiratory trace. The real observed tumor motion (total displacement ≤ 8 mm) was evaluated first. Then, the motion range was artificially increased to 2 or 3 cm. Finally, T was increased to 60 s. While not realistic, making T comparable to the delivery time elucidates if the interplay effect can be observed. For a single fraction, the authors quantified the interplay effect as the maximum difference in the target dosimetric indices, most importantly the near-minimum dose (D99%), between all possible starting phases. For the three- and five-fractions, statistical simulations were performed when substantial interplay was found. RESULTS For the motion amplitudes and periods obtained from the 4DCT, the interplay effect is negligible (<0.2%). It is also small (0.9% average, 2.2% maximum) when the target excursion increased to 2-3 cm. Only with large motion and increased period (60 s) was a significant interplay effect observed, with D99% ranging from 16% low to 17% high. The interplay effect was statistically significantly lower for the three- and five-fraction statistical simulations. Overall, the gradient effect dominates the clinical situation. CONCLUSIONS A novel method was used to reconstruct the volumetric dose to a moving tumor during lung SBRT VMAT deliveries. With the studied planning and treatment technique for realistic motion periods, regardless of the amplitude, the interplay has nearly no impact on the near-minimum dose. The interplay effect was observed, for study purposes only, with the period comparable to the VMAT delivery time.

Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels

Purpose: Many radiomics features were originally developed for non‐medical imaging applications and therefore original assumptions may need to be reexamined. In this study, we investigated the impact of slice thickness and pixel spacing (or pixel size) on radiomics features extracted from Computed Tomography (CT) phantom images acquired with different scanners as well as different acquisition and reconstruction parameters. The dependence of CT texture features on gray‐level discretization was also evaluated. Methods and materials: A texture phantom composed of 10 different cartridges of different materials was scanned on eight different CT scanners from three different manufacturers. The images were reconstructed for various slice thicknesses. For each slice thickness, the reconstruction Field Of View (FOV) was varied to render pixel sizes ranging from 0.39 to 0.98 mm. A fixed spherical region of interest (ROI) was contoured on the images of the shredded rubber cartridge and the 3D printed, 20% fill, acrylonitrile butadiene styrene plastic cartridge (ABS20) for all phantom imaging sets. Radiomic features were extracted from the ROIs using an in‐house program. Features categories were: shape (10), intensity (16), GLCM (24), GLZSM (11), GLRLM (11), and NGTDM (5), fractal dimensions (8) and first‐order wavelets (128), for a total of 213 features. Voxel‐size resampling was performed to investigate the usefulness of extracting features using a suitably chosen voxel size. Acquired phantom image sets were resampled to a voxel size of 1 × 1 × 2 mm3 using linear interpolation. Image features were therefore extracted from resampled and original datasets and the absolute value of the percent coefficient of variation (%COV) for each feature was calculated. Based on the %COV values, features were classified in 3 groups: (1) features with large variations before and after resampling (%COV >50); (2) features with diminished variation (%COV <30) after resampling; and (3) features that had originally moderate variation (%COV <50%) and were negligibly affected by resampling. Group 2 features were further studied by modifying feature definitions to include voxel size. Original and voxel‐size normalized features were used for interscanner comparisons. A subsequent analysis investigated feature dependency on gray‐level discretization by extracting 51 texture features from ROIs from each of the 10 different phantom cartridges using 16, 32, 64, 128, and 256 gray levels. Results: Out of the 213 features extracted, 150 were reproducible across voxel sizes, 42 improved significantly (%COV <30, Group 2) after resampling, and 21 had large variations before and after resampling (Group 1). Ten features improved significantly after definition modification effectively removed their voxel‐size dependency. Interscanner comparison indicated that feature variability among scanners nearly vanished for 8 of these 10 features. Furthermore, 17 out of 51 texture features were found to be dependent on the number of gray levels. These features were redefined to include the number of gray levels which greatly reduced this dependency. Conclusion: Voxel‐size resampling is an appropriate pre‐processing step for image datasets acquired with variable voxel sizes to obtain more reproducible CT features. We found that some of the radiomics features were voxel size and gray‐level discretization‐dependent. The introduction of normalizing factors in their definitions greatly reduced or removed these dependencies.

Study of 201 non-small cell lung cancer patients given stereotactic ablative radiation therapy shows local control dependence on dose calculation algorithm.

PURPOSE Pencil beam (PB) and collapsed cone convolution (CCC) dose calculation algorithms differ significantly when used in the thorax. However, such differences have seldom been previously directly correlated with outcomes of lung stereotactic ablative body radiation (SABR). METHODS AND MATERIALS Data for 201 non-small cell lung cancer patients treated with SABR were analyzed retrospectively. All patients were treated with 50 Gy in 5 fractions of 10 Gy each. The radiation prescription mandated that 95% of the planning target volume (PTV) receive the prescribed dose. One hundred sixteen patients were planned with BrainLab treatment planning software (TPS) with the PB algorithm and treated on a Novalis unit. The other 85 were planned on the Pinnacle TPS with the CCC algorithm and treated on a Varian linac. Treatment planning objectives were numerically identical for both groups. The median follow-up times were 24 and 17 months for the PB and CCC groups, respectively. The primary endpoint was local/marginal control of the irradiated lesion. Grays competing risk method was used to determine the statistical differences in local/marginal control rates between the PB and CCC groups. RESULTS Twenty-five patients planned with PB and 4 patients planned with the CCC algorithms to the same nominal doses experienced local recurrence. There was a statistically significant difference in recurrence rates between the PB and CCC groups (hazard ratio 3.4 [95% confidence interval: 1.18-9.83], Grays test P=.019). The differences (Δ) between the 2 algorithms for target coverage were as follows: ΔD99GITV = 7.4 Gy, ΔD99PTV = 10.4 Gy, ΔV90GITV = 13.7%, ΔV90PTV = 37.6%, ΔD95PTV = 9.8 Gy, and ΔDISO = 3.4 Gy. GITV = gross internal tumor volume. CONCLUSIONS Local control in patients receiving who were planned to the same nominal dose with PB and CCC algorithms were statistically significantly different. Possible alternative explanations are described in the report, although they are not thought likely to explain the difference. We conclude that the difference is due to relative dosimetric underdosing of tumors with the PB algorithm.

Variability of Image Features Computed from Conventional and Respiratory-Gated PET/CT Images of Lung Cancer.

Radiomics is being explored for potential applications in radiation therapy. How various imaging protocols affect quantitative image features is currently a highly active area of research. To assess the variability of image features derived from conventional [three-dimensional (3D)] and respiratory-gated (RG) positron emission tomography (PET)/computed tomography (CT) images of lung cancer patients, image features were computed from 23 lung cancer patients. Both protocols for each patient were acquired during the same imaging session. PET tumor volumes were segmented using an adaptive technique which accounted for background. CT tumor volumes were delineated with a commercial segmentation tool. Using RG PET images, the tumor center of mass motion, length, and rotation were calculated. Fifty-six image features were extracted from all images consisting of shape descriptors, first-order features, and second-order texture features. Overall, 26.6% and 26.2% of total features demonstrated less than 5% difference between 3D and RG protocols for CT and PET, respectively. Between 10 RG phases in PET, 53.4% of features demonstrated percent differences less than 5%. The features with least variability for PET were sphericity, spherical disproportion, entropy (first and second order), sum entropy, information measure of correlation 2, Short Run Emphasis (SRE), Long Run Emphasis (LRE), and Run Percentage (RPC); and those for CT were minimum intensity, mean intensity, Root Mean Square (RMS), Short Run Emphasis (SRE), and RPC. Quantitative analysis using a 3D acquisition versus RG acquisition (to reduce the effects of motion) provided notably different image feature values. This study suggests that the variability between 3D and RG features is mainly due to the impact of respiratory motion.

Validation of three deformable image registration algorithms for the thorax.

Deformable image registration (DIR) has been proposed for lung ventilation calculation using 4D CT. Spatial accuracy of DIR can be evaluated using expert landmark correspondences. Additionally, image differences between the deformed and the target images give a degree of accuracy of DIR algorithms for the same image modality registration. DIR of the normal end‐expiration (50%), end‐ inspiration (0%), midexpiration (30%), and midinspiration image (70%) phases of the 4D CT images was used to correlate the voxels between the respiratory phases. Three DIR algorithms, optical flow (OF), diffeomorphic morphons (DM), and diffeomorphic demons (DD) were validated using a 4D thorax model, consisting of a 4D CT image dataset, along with associated landmarks delineated by a radiologist. Image differences between the deformed and the target images were used to evaluate the degree of registration accuracy of the three DIR algorithms. In the validation of the DIR algorithms, the average target registration error (TRE) for normal end‐expiration‐to‐end‐inspiration registration with one standard deviation (SD) for the DIR algorithms was 1.6±0.9mm (maximum 3.1 mm) for OF, 1.4±0.6mm (maximum 3.3 mm) for DM, and 1.4±0.7mm (maximum 3.3 mm) for DD, indicating registration errors were within two voxels. As a reference, the median value of TRE between 0 and 50% phases with rigid registration only was 5.0 mm with one SD of 2.5 mm and the maximum value of 12.0 mm. For the OF algorithm, 81% of voxels were within a difference of 50 HU, and 93% of the voxels were within 100 HU. For the DM algorithm, 69% of voxels were within 50 HU, and 87% within 100 HU. For the DD algorithm, 71% of the voxels were within 50 HU, and 87% within a difference of 100 HU. These data suggest that the three DIR methods perform accurate registrations in the thorax region. The mean TRE for all three DIR methods was less than two voxels suggesting that the registration performed by all methods are equally accurate in the thorax. PACS number:89.90

Initial evaluation of automated treatment planning software

Even with advanced inverse‐planning techniques, radiation treatment plan optimization remains a very time‐consuming task with great output variability, which prompted the development of more automated approaches. One commercially available technique mimics the actions of experienced human operators to progressively guide the traditional optimization process with automatically created regions of interest and associated dose‐volume objectives. We report on the initial evaluation of this algorithm on 10 challenging cases of locoreginally advanced head and neck cancer. All patients were treated with VMAT to 70 Gy to the gross disease and 56 Gy to the elective bilateral nodes. The results of post‐treatment autoplanning (AP) were compared to the original human‐driven plans (HDP). We used an objective scoring system based on defining a collection of specific dosimetric metrics and corresponding numeric score functions for each. Five AP techniques with different input dose goals were applied to all patients. The best of them averaged the composite score 8% lower than the HDP, across the patient population. The difference in median values was statistically significant at the 95% confidence level (Wilcoxon paired signed‐rank test p=0.027). This result reflects the premium the institution places on dose homogeneity, which was consistently higher with the HDPs. The OAR sparing was consistently better with the APs, the differences reaching statistical significance for the mean doses to the parotid glands (p<0.001) and the inferior pharyngeal constrictor (p=0.016), as well as for the maximum doses to the spinal cord (p=0.018) and brainstem (p=0.040). If one is prepared to accept less stringent dose homogeneity criteria from the RTOG 1016 protocol, nine APs would comply with the protocol, while providing lower OAR doses than the HDPs. Overall, AP is a promising clinical tool, but it could benefit from a better process for shifting the balance between the target dose coverage/homogeneity and OAR sparing. PACS number(s): 87.55.DEven with advanced inverse-planning techniques, radiation treatment plan optimization remains a very time-consuming task with great output variability, which prompted the development of more automated approaches. One commercially available technique mimics the actions of experienced human operators to progressively guide the traditional optimization process with automatically created regions of interest and associated dose-volume objectives. We report on the initial evaluation of this algorithm on 10 challenging cases of locoreginally advanced head and neck cancer. All patients were treated with VMAT to 70 Gy to the gross disease and 56 Gy to the elective bilateral nodes. The results of post-treatment autoplanning (AP) were compared to the original human-driven plans (HDP). We used an objective scoring system based on defining a collection of specific dosimetric metrics and corresponding numeric score functions for each. Five AP techniques with different input dose goals were applied to all patients. The best of them averaged the composite score 8% lower than the HDP, across the patient population. The difference in median values was statistically significant at the 95% confidence level (Wilcoxon paired signed-rank test p=0.027). This result reflects the premium the institution places on dose homogeneity, which was consistently higher with the HDPs. The OAR sparing was consistently better with the APs, the differences reaching statistical significance for the mean doses to the parotid glands (p<0.001) and the inferior pharyngeal constrictor (p=0.016), as well as for the maximum doses to the spinal cord (p=0.018) and brainstem (p=0.040). If one is prepared to accept less stringent dose homogeneity criteria from the RTOG 1016 protocol, nine APs would comply with the protocol, while providing lower OAR doses than the HDPs. Overall, AP is a promising clinical tool, but it could benefit from a better process for shifting the balance between the target dose coverage/homogeneity and OAR sparing. PACS number(s): 87.55.D.

Combining radiomic features with a miRNA classifier may improve prediction of malignant pathology for pancreatic intraductal papillary mucinous neoplasms

Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic cancer precursors incidentally discovered by cross-sectional imaging. Consensus guidelines for IPMN management rely on standard radiologic features to predict pathology, but they lack accuracy. Using a retrospective cohort of 38 surgically-resected, pathologically-confirmed IPMNs (20 benign; 18 malignant) with preoperative computed tomography (CT) images and matched plasma-based ‘miRNA genomic classifier (MGC)’ data, we determined whether quantitative ‘radiomic’ CT features (+/- the MGC) can more accurately predict IPMN pathology than standard radiologic features ‘high-risk’ or ‘worrisome’ for malignancy. Logistic regression, principal component analyses, and cross-validation were used to examine associations. Sensitivity, specificity, positive and negative predictive value (PPV, NPV) were estimated. The MGC, ‘high-risk,’ and ‘worrisome’ radiologic features had area under the receiver operating characteristic curve (AUC) values of 0.83, 0.84, and 0.54, respectively. Fourteen radiomic features differentiated malignant from benign IPMNs (p<0.05) and collectively had an AUC=0.77. Combining radiomic features with the MGC revealed an AUC=0.92 and superior sensitivity (83%), specificity (89%), PPV (88%), and NPV (85%) than other models. Evaluation of uncertainty by 10-fold cross-validation retained an AUC>0.80 (0.87 (95% CI:0.84-0.89)). This proof-of-concept study suggests a noninvasive radiogenomic approach may more accurately predict IPMN pathology than ‘worrisome’ radiologic features considered in consensus guidelines.

Potential role for LINAC-based stereotactic radiosurgery for the treatment of 5 or more radioresistant melanoma brain metastases

OBJECT Linear accelerator (LINAC)-based stereotactic radiosurgery (SRS) is a treatment option for patients with melanoma in whom brain metastases have developed. Very limited data are available on treating patients with ≥5 lesions. The authors sought to determine the effectiveness of SRS in patients with ≥5 melanoma brain metastases. METHODS A retrospective analysis of metastatic melanoma treated with SRS in a single treatment session for ≥5 lesions was performed. Magnetic resonance imaging studies were reviewed post-SRS to evaluate local control (LC). Disease progression on imaging was defined using the 2009 Response Evaluation Criteria in Solid Tumors (RECIST). Survival curves were calculated from the date of brain metastases diagnosis or the date of SRS by using the Kaplan-Meier (KM) method. Univariate and multivariate analysis (UVA and MVA, respectively) were performed using the Cox proportional-hazards model. RESULTS The authors identified 149 metastatic brain lesions treated in 28 patients. The median patient age was 60.5 years (range 38-83 years), and the majority of patients (24 [85.7%]) had extracranial metastases. Four patients (14.3%) had received previous whole-brain radiotherapy (WBRT), and 11 (39.3%) had undergone previous SRS. The median planning target volume (PTV) was 0.34 cm3 (range 0.01-12.5 cm3). Median follow-up was 6.3 months (range 1-46 months). At the time of treatment, 7% of patients were categorized as recursive partitioning analysis (RPA) Class I, 89% as RPA Class II, and 4% as RPA Class III. The rate of local failure was 11.4%. Kaplan-Meier LC estimates at 6 and 12 months were 91.3% and 82.2%, respectively. A PTV volume≥0.34 cm3 was a significant predictor of local failure on UVA (HR 16.1, 95% CI 3.2-292.6, p<0.0001) and MVA (HR 14.8, 95% CI 3.0-268.5, p=0.0002). Sixteen patients (57.1%) were noted to have distant failure in the brain with a median time to failure of 3 months (range 1-15 months). Nine patients with distant failures received WBRT, and 7 received additional SRS. Median overall survival (OS) was 9.4 and 7.6 months from the date of brain metastases diagnosis and the date of SRS, respectively. The KM OS estimates at 6 and 12 months were 57.8% and 28.2%, respectively, from the time of SRS treatment. The RPA class was a significant predictor of KM OS estimates from the date of treatment (p=0.02). Patients who did not receive WBRT after SRS treatment had decreased OS on MVA (HR 3.5, 95% CI 1.1-12.0, p=0.03), and patients who did not receive WBRT prior to SRS had improved OS (HR 0.11, 95% CI 0.02-0.53, p=0.007). CONCLUSIONS Stereotactic radiosurgery for ≥5 lesions appears to be effective for selected patients with metastatic melanoma, offering excellent LC. This is particularly important for patients as new targeted systemic agents are improving outcomes but still have limited efficacy within the central nervous system.

Imaging features from pretreatment CT scans are associated with clinical outcomes in nonsmall-cell lung cancer patients treated with stereotactic body radiotherapy

Purpose: To investigate whether imaging features from pretreatment planning CT scans are associated with overall survival (OS), recurrence‐free survival (RFS), and loco‐regional recurrence‐free survival (LR‐RFS) after stereotactic body radiotherapy (SBRT) among nonsmall‐cell lung cancer (NSCLC) patients. Patients and methods: A total of 92 patients (median age: 73 yr) with stage I or IIA NSCLC were qualified for this study. A total dose of 50 Gy in five fractions was the standard treatment. Besides clinical characteristics, 24 “semantic” image features were manually scored based on a point scale (up to 5) and 219 computer‐derived “radiomic” features were extracted based on whole tumor segmentation. Statistical analysis was performed using Cox proportional hazards model and Harrells C‐index, and the robustness of final prognostic model was assessed using tenfold cross validation by dichotomizing patients according to the survival or recurrence status at 24 months. Results: Two‐year OS, RFS and LR‐RFS were 69.95%, 41.3%, and 51.85%, respectively. There was an improvement of Harrells C‐index when adding imaging features to a clinical model. The model for OS contained the Eastern Cooperative Oncology Group (ECOG) performance status [Hazard Ratio (HR) = 2.78, 95% Confidence Interval (CI): 1.37–5.65], pleural retraction (HR = 0.27, 95% CI: 0.08–0.92), F2 (short axis × longest diameter, HR = 1.72, 95% CI: 1.21–2.44) and F186 (Hist‐Energy‐L1, HR = 1.27, 95% CI: 1.00–1.61); The prognostic model for RFS contained vessel attachment (HR = 2.13, 95% CI: 1.24–3.64) and F2 (HR = 1.69, 95% CI: 1.33–2.15); and the model for LR‐RFS contained the ECOG performance status (HR = 2.01, 95% CI: 1.12–3.60) and F2 (HR = 1.67, 95% CI: 1.29–2.18). Conclusions: Imaging features derived from planning CT demonstrate prognostic value for recurrence following SBRT treatment, and might be helpful in patient stratification.

Monte Carlo Study of Radiation Dose Enhancement by Gadolinium in Megavoltage and High Dose Rate Radiotherapy

MRI is often used in tumor localization for radiotherapy treatment planning, with gadolinium (Gd)-containing materials often introduced as a contrast agent. Motexafin gadolinium is a novel radiosensitizer currently being studied in clinical trials. The nanoparticle technologies can target tumors with high concentration of high-Z materials. This Monte Carlo study is the first detailed quantitative investigation of high-Z material Gd-induced dose enhancement in megavoltage external beam photon therapy. BEAMnrc, a radiotherapy Monte Carlo simulation package, was used to calculate dose enhancement as a function of Gd concentration. Published phase space files for the TrueBeam flattening filter free (FFF) and conventional flattened 6MV photon beams were used. High dose rate (HDR) brachytherapy with Ir-192 source was also investigated as a reference. The energy spectra difference caused a dose enhancement difference between the two beams. Since the Ir-192 photons have lower energy yet, the photoelectric effect in the presence of Gd leads to even higher dose enhancement in HDR. At depth of 1.8 cm, the percent mean dose enhancement for the FFF beam was 0.38±0.12, 1.39±0.21, 2.51±0.34, 3.59±0.26, and 4.59±0.34 for Gd concentrations of 1, 5, 10, 15, and 20 mg/mL, respectively. The corresponding values for the flattened beam were 0.09±0.14, 0.50±0.28, 1.19±0.29, 1.68±0.39, and 2.34±0.24. For Ir-192 with direct contact, the enhanced were 0.50±0.14, 2.79±0.17, 5.49±0.12, 8.19±0.14, and 10.80±0.13. Gd-containing materials used in MRI as contrast agents can also potentially serve as radiosensitizers in radiotherapy. This study demonstrates that Gd can be used to enhance radiation dose in target volumes not only in HDR brachytherapy, but also in 6 MV FFF external beam radiotherapy, but higher than the currently used clinical concentration (>5 mg/mL) would be needed.