ABSTRACT
PURPOSE: Pelvic recurrence of rectal or anal cancers is associated with considerable morbidity and mortality. We report our initial experience with an aggressive intra-operative radiotherapy (IORT) program. METHODS: Patients with locally advanced or recurrent rectal or anal cancers considered to have a high likelihood of R1 or R2 resection after multi-disciplinary review underwent surgical excision and IORT using a high-dose-rate afterloader (Ir-192) and HAM applicator. Endpoints included local or distant recurrence, and acute and late toxicity graded using the American College of Surgeons (ACS) NSQIP and the LENT-SOMA scale. RESULTS: Twenty-one patients, largely with prior history of both pelvic external beam radiotherapy (EBRT, median 50.4 Gy) and surgical resection, underwent excision with IORT (median dose 12.5 Gy, range 10-15). Median follow-up was 20 months. Twelve (57%) patients had failure at the IORT site. Freedom from failure (FFF) within the IORT field was associated with resection status (FFF at 1 year 75% for R0 vs 15% for R1/2, p = 0.0065) but not re-irradiation EBRT or IORT dose (p > 0.05). Twelve, 5, and 13 patients experienced local, regional, and distant failure, respectively; 3 (14%) patients were disease-free at last follow-up. The most frequent acute toxicity was sepsis/abscess (24%). One patient (5%) required a ureteral stent; no patients developed neuropathy attributable to IORT. CONCLUSIONS: In patients treated with excision and IORT for locally recurrent cancer, R0 resection is a critical determinant of local control. For patients with R1/2 resection, poor disease-free outcomes warrant consideration of a different treatment strategy.
Subject(s)
Anus Neoplasms , Humans , Anus Neoplasms/radiotherapy , Anus Neoplasms/surgeryABSTRACT
The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education and professional practice of medical physics. The AAPM has more than 8,000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines will be reviewed for the purpose of revision or renewal, as appropriate, on their fifth anniversary or sooner. Each medical physics practice guideline represents a policy statement by the AAPM, has undergone a thorough consensus process in which it has been subjected to extensive review, and requires the approval of the Professional Council. The medical physics practice guidelines recognize that the safe and effective use of diagnostic and therapeutic radiology requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guidelines and technical standards by those entities not providing these services is not authorized. The following terms are used in the AAPM practice guidelines: (1) Must and Must Not: Used to indicate that adherence to the recommendation is considered necessary to conform to this practice guideline. (2) Should and Should Not: Used to indicate a prudent practice to which exceptions may occasionally be made in appropriate circumstances.
Subject(s)
Health Physics , Radiation Oncology , Humans , Societies , United StatesABSTRACT
PURPOSE: To evaluate the dosimetric impact of daily positioning variations measured with cone-beam computed tomography (CBCT) on whole-breast radiotherapy patients treated in the prone position. METHODS: Daily CBCT was prospectively acquired for 30 consecutive patients positioned prone. Treatment for early-stage (≤II) breast cancer was prescribed with standard dose (50 Gy/25 fractions) or hypofractionation (42.56 Gy/16 fractions) for 13 and 17 patients, respectively. Systematic and random errors were calculated from the translational CBCT shifts and used to determine population-based setup margins. Mean translations (±one standard deviation) for each patient were used to simulate the dosimetric impact on targets (PTV_eval and lumpectomy cavity), heart, and lung. Paired Student's t tests at α = 0.01 were used to compare dose metrics after correction for multiple testing (P < 0.002). Significant correlation coefficients were used to identify associations (P < 0.01). RESULTS: Of 597 total fractions, 20 ± 13% required patient rotation. Mean translations were 0.29 ± 0.27 cm, 0.41 ± 0.34 cm, and 0.48 ± 0.33 cm in the anterior-posterior, superior-inferior, and lateral directions leading to calculated setup margins of 0.63, 0.88, and 1.10 cm, respectively. Average three-dimensional (3D) shifts correlated with the maximum distance of breast tissue from the sternum (r = 0.62) but not with body-mass index. Simulated shifts showed significant, but minor, changes in dose metrics for PTV_eval, lung, and heart. For left-sided treatments (n = 18), mean heart dose increased from 109 ± 75 cGy to 148 ± 115 cGy. Shifts from the original plan caused PTV_eval hotspots (V105%) to increase by 5.2% ± 3.8%, which correlated with the total MU of wedged fields (r = 0.59). No significant change in V95% to the cavity was found. CONCLUSIONS: Large translational variations that occur when positioning prone breast patients had small but significant dosimetric effects on 3DCRT plans. Daily CBCT may still be necessary to correct for rotational variations that occur in 20% of treatments. To maintain planned dose metrics, unintended beam shifts toward the heart and the contribution of wedged fields should be minimized.
Subject(s)
Breast Neoplasms , Radiotherapy, Conformal , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/radiotherapy , Cone-Beam Computed Tomography , Female , Humans , Prone Position , Radiotherapy Dosage , Radiotherapy Planning, Computer-AssistedABSTRACT
INTRODUCTION: Image registration and delineation of organs at risk (OARs) are key components of three-dimensional conformal (3DCRT) and intensity-modulated radiotherapy (IMRT) treatment planning. This study hypothesized that image registration and OAR delineation are often performed by medical physicists and/or dosimetrists and are not routinely reviewed by treating physicians. METHODS: An anonymous, internet-based survey of medical physicists and dosimetrists was distributed via the MEDPHYS and MEDDOS listserv groups. Participants were asked to characterize standard practices for completion and review of OAR contouring, target volume contouring, and image registration at their institution along with their personal training in these areas and level of comfort performing these tasks. Likert-type scales are reported as Median [Interquartile range] with scores ranging from 1 = "Extremely/All of the time" to 5 = "Not at all/Never." RESULTS: Two hundred and ninety-seven individuals responded to the survey. Overall, respondents indicated significantly less frequent physician review (3 [2-4] vs 2 [1-3]), and less confidence in the thoroughness of physician review (3 [2-4] vs 2 [1-3], P < 0.01) of OAR contours compared to image registration. Only 19% (95% CI 14-24%) of respondents reported a formal process by which OAR volumes are reviewed by physicians in their clinic. The presence of a formal review process was also associated with significantly higher perceived thoroughness of review of OAR volumes compared to clinics with no formal review process (2 [2-3] vs 3 [2-4], P < 0.01). CONCLUSION: Despite the critical role of OAR delineation and image registration in the 3DCRT and IMRT treatment planning process, physician review of these tasks is not always optimal. Radiotherapy clinics should consider implementation of formal processes to promote adequate physician review of OARs and image registrations to ensure the quality and safety of radiotherapy treatment plans.
Subject(s)
Physicians , Radiotherapy, Conformal , Radiotherapy, Intensity-Modulated , Humans , Organs at Risk , Radiotherapy Dosage , Radiotherapy Planning, Computer-AssistedABSTRACT
Surface imaging (SI) has been rapidly integrated into radiotherapy clinics across the country without specific guidelines and recommendations on its commissioning and use aside from vendor-provided information. A survey was created under the auspices of AAPM TG-302 to assess the current status of SI to identify if there is need for formal guidance. The survey was designed to determine the institutional setting of responders, availability and length of its use, commissioning procedures, and clinical applications. This survey was created in REDCap, and approved as IRB exempt to collect anonymized data. Questions were reviewed by multiple physicists to ensure concept validity and piloted by a small group of independent physicists to ensure process validity. All full members of AAPM self-identified as "therapy" or "other" were sent the survey link by email. The survey was active from February to March 2018. Of 3677 members successfully contacted, 439 completed responses; the summary of these responses provides insight on current surface imaging clinical practices, though they should not be assumed to be representative of radiation oncology as a whole. Results showed that 53.3% of respondents have SI in their clinics, mostly in treatment rooms, rarely in simulation rooms. Half of those without SI plan on purchasing it within 3 years. Over 10% have SI but do not use it clinically, 36.8% classify themselves as "expert" users, and 85.5% agreed/strongly agreed that SI guidelines are needed. Initial positioning with SI is most common for breast/chestwall and SRS/SBRT treatments, least common for pediatrics. Use of SI for intra-fraction monitoring follows a similar distribution. Gating with SI is most prevalent for breast/chestwall (66.0%) but also used in SBRT (33.0%), and non-SBRT lung/abdomen (<30%) treatments. SI is a rapidly growing technology in the field with widespread use for several anatomic sites. Guidelines and recommendations on commissioning and clinical use are warranted.
Subject(s)
Neoplasms/surgery , Particle Accelerators/instrumentation , Radiation Oncology/standards , Radiosurgery/methods , Respiratory-Gated Imaging Techniques/methods , Surveys and Questionnaires/statistics & numerical data , Humans , Image Processing, Computer-Assisted/methods , Neoplasms/diagnostic imaging , Neoplasms/pathology , Radiotherapy Dosage , Radiotherapy, Intensity-Modulated/methods , Tomography, X-Ray Computed/methods , United StatesABSTRACT
BACKGROUND: Some patients cannot be imaged with cone-beam CT for image-guided radiation therapy because their size, pose, or fixation devices cause collisions with the machine. OBJECTIVE: To investigate imaging trajectories that avoid such collisions by using virtual isocenter and variable magnification during acquisition while yielding comparable image quality. METHODS: The machine components most likely to collide are the gantry and kV detector. A virtual isocenter trajectory continuously moves the patient during gantry rotation to maintain an increased separation between the two. With dynamic magnification, the kV detector is dynamically moved to increase clearance for an angular range around the potential collision point while acquiring sufficient data to maintain the field-of-view. Both strategies were used independently and jointly with the resultant image quality evaluated against the standard circular acquisition. RESULTS: Collision avoiding trajectories show comparable contrast and resolution to standard techniques. For an anthropomorphic phantom, the RMSE is <7×10- 4, multi-scale structural similarity index is >0.97, and visual image fidelity is >0.96 for all trajectories when compared to a standard circular scan. CONCLUSIONS: The proposed trajectories avoid machine-patient collisions while providing comparable image quality to the current standard thereby enabling CBCT imaging for patients that could not otherwise be scanned.
Subject(s)
Cone-Beam Computed Tomography/methods , Radiotherapy, Image-Guided/methods , Cone-Beam Computed Tomography/instrumentation , Humans , Particle Accelerators/instrumentation , Phantoms, Imaging , Radiotherapy Planning, Computer-Assisted , Radiotherapy, Image-Guided/instrumentationABSTRACT
PURPOSE: We calculated setup margins for whole breast radiotherapy during voluntary deep-inspiration breath-hold (vDIBH) using real-time surface imaging (SI). METHODS AND MATERIALS: Patients (n = 58) with a 27-to-31 split between right- and left-sided cancers were analyzed. Treatment beams were gated using AlignRT by registering the whole breast region-of-interest to the surface generated from the simulation CT scan. AlignRT recorded (three-dimensional) 3D displacements and the beam-on-state every 0.3 s. Means and standard deviations of the displacements during vDIBH for each fraction were used to calculate setup margins. Intra-DIBH stability and the intrafraction reproducibility were estimated from the medians of the 5th to 95th percentile range of the translations in each breath-hold and fraction, respectively. RESULTS: A total of 7269 breath-holds were detected over 1305 fractions in which a median dose of 200 cGy was delivered. Each fraction was monitored for 5.95 ± 2.44 min. Calculated setup margins were 4.8 mm (A/P), 4.9 mm (S/I), and 6.4 mm (L/R). The intra-DIBH stability and the intrafraction reproducibility were ≤0.7 mm and ≤2.2 mm, respectively. The isotropic margin according to SI (9.2 mm) was comparable to other institutions' calculations that relied on x-ray imaging and/or spirometry for patients with left-sided cancer (9.8-11.0 mm). Likewise, intra-DIBH variability and intrafraction reproducibility of breast surface measured with SI agreed with spirometry-based positioning to within 1.2 and 0.36 mm, respectively. CONCLUSIONS: We demonstrated that intra-DIBH variability, intrafraction reproducibility, and setup margins are similar to those reported by peer studies who utilized spirometry-based positioning.
Subject(s)
Breath Holding , Breast Neoplasms , Heart , Humans , Radiotherapy Planning, Computer-Assisted , Reproducibility of Results , Respiration , Retrospective Studies , Spirometry , Tomography, X-Ray ComputedABSTRACT
We performed a dosimetric comparison of sequential IMRT (sIMRT) and simul-taneously integrated boost (SIB) IMRT to boost PET-avid lymph nodes while concurrently treating pelvic targets to determine the potential of SIB IMRT to reduce overall treatment duration in locally advanced cervical cancer. Ten patients receiving definitive radiation therapy were identified retrospectively. RTOG consensus guidelines were followed to delineate the clinical target volume and organs at risk (OAR), which were then expanded per IMRT consortium guidelines to yield the planning target volume (PTV). Dosimetric parameters for PTVs and OAR including conformity (CI95%) were collected and compared using Wilcoxon signed-rank tests with Bonferroni correction. The median PTV volume was 1843 cc (1088-2225 cc) and the median boost volume was 43 cc (15-129 cc). Comparable target volume coverage was achieved with sIMRT and SIB plans, while hot spots were significantly reduced using SIB. SIB plans improved sparing for all OAR, though only rectum and small bowel doses were statistically significant. Comparing sIMRT and SIB plans averaged over all patients, rectal doses were V45: 70.8% vs. 64.5% (p = 0.002) and 0.1 cc: 50.7 Gy vs. 48.7 Gy (p = 0.006). For small bowel, sIMRT and SIB IMRT plans yielded V45: 13.4% vs. 11.4% (p = 0.006) and 1 cc: 54.4 Gy vs. 52.6 Gy (p = 0.006), respectively. Doses to femoral heads and blad-der trended towards significance in favor of SIB plans. The mean treatment time was 25 versus 29 days for SIB and sIMRT plans, respectively. When compared to sIMRT, SIB for treatment of nodal targets provides a significant, but small, dose reduction (3.8%-4.4%) to OAR, which leads to comparable biological dose despite higher fractional doses. Furthermore, SIB IMRT reduces overall treatment time and simplifies the planning process, and should be considered for targeting PET-positive nodal disease in patients with locally advanced cervical cancer.
Subject(s)
Organs at Risk/radiation effects , Patient Care Planning , Radiotherapy Planning, Computer-Assisted/methods , Uterine Cervical Neoplasms/radiotherapy , Adult , Aged , Female , Humans , Lymph Nodes/radiation effects , Middle Aged , Pelvis/radiation effects , Radiotherapy Dosage , Radiotherapy, Intensity-Modulated/methods , Rectum/radiation effects , Retrospective StudiesABSTRACT
We evaluated the image registration accuracy achieved using two deformable registration algorithms when radiation-induced normal tissue changes were present between serial computed tomography (CT) scans. Two thoracic CT scans were collected for each of 24 patients who underwent radiation therapy (RT) treatment for lung cancer, eight of whom experienced radiologically evident normal tissue damage between pre- and post-RT scan acquisition. For each patient, 100 landmark point pairs were manually placed in anatomically corresponding locations between each pre- and post-RT scan. Each post-RT scan was then registered to the pre-RT scan using (1) the Plastimatch demons algorithm and (2) the Fraunhofer MEVIS algorithm. The registration accuracy for each scan pair was evaluated by comparing the distance between landmark points that were manually placed in the post-RT scans and points that were automatically mapped from pre- to post-RT scans using the displacement vector fields output by the two registration algorithms. For both algorithms, the registration accuracy was significantly decreased when normal tissue damage was present in the post-RT scan. Using the Plastimatch algorithm, registration accuracy was 2.4 mm, on average, in the absence of radiation-induced damage and 4.6 mm, on average, in the presence of damage. When the Fraunhofer MEVIS algorithm was instead used, registration errors decreased to 1.3 mm, on average, in the absence of damage and 2.5 mm, on average, when damage was present. This work demonstrated that the presence of lung tissue changes introduced following RT treatment for lung cancer can significantly decrease the registration accuracy achieved using deformable registration.
Subject(s)
Algorithms , Lung Neoplasms/diagnostic imaging , Lung/diagnostic imaging , Radiographic Image Enhancement , Tomography, X-Ray Computed , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Reproducibility of Results , Retrospective StudiesABSTRACT
The purpose of this study was to quantify the variability of the breast surface position when aligning whole-breast patients to bony landmarks based on MV portal films or skin marks alone. Surface imaging was used to assess the breast surface position of 11 whole-breast radiotherapy patients, but was not used for patient positioning. On filmed fractions, AlignRT v5.0 was used to capture the patient's surface after initial positioning based on skin marks (28 "preshifts" surfaces), and after treatment couch shifts based on MV films (41 "postshifts" surfaces). Translations and rotations based on surface captures were recorded, as well as couch shifts based on MV films. For nonfilmed treatments, "daily" surface images were captured following positioning to skin marks alone. Group mean and systematic and random errors were calculated for all datasets. Pearson correlation coefficients, setup margins, and 95% limits of agreement (LOA) were calculated for preshifts translations and MV film shifts. LOA between postshifts surfaces and the filmed treatment positions were also computed. All the surface captures collected were retrospectively compared to both a DICOM reference surface created from the planning CT and to an AlignRT reference surface. All statistical analyses were performed using the DICOM reference surface dataset. AlignRT reference surface data was only used to calculate the LOA with the DICOM reference data. This helped assess any outcome differences between both reference surfaces. Setup margins for preshifts surfaces and MV films range between 8.3-12.0 mm and 5.4-13.4 mm, respectively. The largest margin is along the left-right (LR) direction for preshift surfaces, and along craniocaudal (CC) for films. LOA ranges between the preshifts surfaces and MV film shifts are large (12.6-21.9 mm); these decrease for postshifts surfaces (9.8-18.4 mm), but still show significant disagreements between the two modalities due to their focus on different anatomical landmarks (patient's topography versus bony anatomy). Pearson's correlation coefficients further support this by showing low to moderate correlations in the anterior-posterior (AP) and LR directions (0.47-0.69) and no correlation along CC (< 0.15). The use of an AlignRT reference surface compared to the DICOM reference surface does not significantly affect the LOA. Alignment of breast patients based solely on bony alignment may lead to interfractional inconsistencies in the breast surface position. The use of surface imaging tools highlights these discrepancies, and allows the radiation oncology team to better assess the possible effects on treatment quality.
Subject(s)
Breast Neoplasms/radiotherapy , Data Interpretation, Statistical , Dose Fractionation, Radiation , Patient Positioning/methods , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Conformal/methods , Female , Humans , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
Treatment planning for breast cancer has been traditionally based on clinical landmarks. The Radiation Therapy Oncology Group (RTOG) published consensus guidelines on contouring target volumes (TV) for the breast/chest wall and draining lymphatics. The effect of these guidelines on dosimetric parameters in surrounding organs at risk (OAR) and TVs is unknown. Fourteen patients treated with clinically derived plans from 2007-2011 (Group I) and fourteen patients treated with target volume-based plans from 2011-2012 were selected for comparison (Group II). Treatment plans were constructed based on clinical landmarks (Group I) or TVs (Group II) to a median dose of 50.4 Gy to the breast/chest wall, axilla (Ax), supraclavicular (SCV), and internal mammary (IMN) lymph nodes. The RTOG TVs were then contoured in Group I patients by a single investigator blinded to the dose distributions. Dose-volume histograms (DVH) were computed for the RTOG TVs and OARs in both groups, and DVH parameters were compared. In Group II, coverage improved for the SCV (V90 = 78.0% versus 93.6%, p = 0.02) and intact breast (V95 = 95.6% versus 99.3%, p = 0.007). The dose to the cord, the lung (V20Gy and V30Gy), and contralateral breast (V5Gy) were the same. Finally, the low dose to the heart and lung was decreased in Group II (heart V5Gy= 48.7% versus 27.3%, p= 0.02, heart V10Gy = 33.5% vs. 17.5%, p = 0.01, and ipsilateral lung V5Gy = 84.5% vs. 69.3%, p = 0.001). Overall, our study supports that treatment planning using the RTOG consensus guidelines can improve coverage to certain target volumes compared to treatments based solely on clinical landmarks. Additionally, treatment planning using these target volumes does not increase dose to the contralateral breast, cord, heart, or lungs. Longer follow-up is needed to determine if using these target volumes will affect clinical outcomes.
Subject(s)
Breast Neoplasms/radiotherapy , Lymph Nodes/diagnostic imaging , Radiography, Thoracic/methods , Radiometry/methods , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy/standards , Adult , Aged , Breast Neoplasms/mortality , Equipment Design , Female , Heart/radiation effects , Humans , Imaging, Three-Dimensional , Lung/radiation effects , Middle Aged , Organs at Risk , Practice Guidelines as Topic , Radiotherapy Dosage , Thoracic Wall/diagnostic imaging , Tomography, X-Ray Computed/methods , Treatment OutcomeABSTRACT
Deep learning neural networks (DLNN) in Artificial intelligence (AI) have been extensively explored for automatic segmentation in radiotherapy (RT). In contrast to traditional model-based methods, data-driven AI-based models for auto-segmentation have shown high accuracy in early studies in research settings and controlled environment (single institution). Vendor-provided commercial AI models are made available as part of the integrated treatment planning system (TPS) or as a stand-alone tool that provides streamlined workflow interacting with the main TPS. These commercial tools have drawn clinics' attention thanks to their significant benefit in reducing the workload from manual contouring and shortening the duration of treatment planning. However, challenges occur when applying these commercial AI-based segmentation models to diverse clinical scenarios, particularly in uncontrolled environments. Contouring nomenclature and guideline standardization has been the main task undertaken by the NRG Oncology. AI auto-segmentation holds the potential clinical trial participants to reduce interobserver variations, nomenclature non-compliance, and contouring guideline deviations. Meanwhile, trial reviewers could use AI tools to verify contour accuracy and compliance of those submitted datasets. In recognizing the growing clinical utilization and potential of these commercial AI auto-segmentation tools, NRG Oncology has formed a working group to evaluate the clinical utilization and potential of commercial AI auto-segmentation tools. The group will assess in-house and commercially available AI models, evaluation metrics, clinical challenges, and limitations, as well as future developments in addressing these challenges. General recommendations are made in terms of the implementation of these commercial AI models, as well as precautions in recognizing the challenges and limitations.
Subject(s)
Deep Learning , Radiation Oncology , Humans , Artificial Intelligence , Neural Networks, Computer , Benchmarking , Radiotherapy Planning, Computer-AssistedABSTRACT
Inhomogeneously broadened, non-Lorentzian water resonances have been observed in small image voxels of breast tissue. The non-Lorentzian components of the water resonance are probably produced by bulk magnetic susceptibility shifts caused by dense, deoxygenated tumor blood vessels (the 'blood oxygenation level-dependent' effect), but can also be produced by other characteristics of local anatomy and physiology, including calcifications and interfaces between different types of tissue. Here, we tested the hypothesis that the detection of non-Lorentzian components of the water resonance with high spectral and spatial resolution (HiSS) MRI allows the classification of breast lesions without the need to inject contrast agent. Eighteen malignant lesions and nine benign lesions were imaged with HiSS MRI at 1.5 T. A new algorithm was developed to detect non-Lorentzian (or off-peak) components of the water resonance. After a Lorentzian fit had been subtracted from the data, the largest peak in the residual spectrum in each voxel was identified as the major off-peak component of the water resonance. The difference in frequency between these off-peak components and the main water peaks, and their amplitudes, were measured in malignant lesions, benign lesions and breast fibroglandular tissue. Off-peak component frequencies were significantly different between malignant and benign lesions (p < 0.001). Receiver operating characteristic (ROC) analysis was used to assess the diagnostic performance of HiSS off-peak component analysis compared with dynamic contrast-enhanced (DCE) MRI parameters. The areas under the ROC curves for the 'DCE rapid uptake fraction', 'DCE washout fraction', 'off-peak component amplitude' and 'off-peak component frequency' were 0.75, 0.83, 0.50 and 0.86, respectively. These results suggest that water resonance lineshape analysis performs well in the classification of breast lesions without contrast injection and could improve the diagnostic accuracy of clinical breast MR examinations. In addition, this approach may provide an alternative to DCE MRI in women who are at risk for adverse reactions to contrast media.
Subject(s)
Breast Neoplasms/pathology , Breast/pathology , Contrast Media/adverse effects , Magnetic Resonance Imaging/methods , Adult , Aged , Female , Humans , Middle Aged , ROC Curve , WaterABSTRACT
PURPOSE: Dose accuracy has been shown to vary with dose per segment and dose rate when delivered with static multileaf collimator (SMLC) intensity modulated radiation therapy (IMRT) by Varian C-series MLC controllers. The authors investigated the impact of monitor units (MUs) per segment and dose rate on the dose delivery accuracy of SMLC-IMRT fields on a Varian TrueBeam linear accelerator (LINAC), which delivers dose and manages motion of all components using a single integrated controller. METHODS: An SMLC sequence was created consisting of ten identical 10 × 10 cm(2) segments with identical MUs. Beam holding between segments was achieved by moving one out-of-field MLC leaf pair. Measurements were repeated for various combinations of MU/segment ranging from 1 to 40 and dose rates of 100-600 MU/min for a 6 MV photon beam (6X) and dose rates of 800-2400 MU/min for a 10 MV flattening-filter free photon (10XFFF) beam. All measurements were made with a Farmer (0.6 cm(3)) ionization chamber placed at the isocenter in a solid-water phantom at 10 cm depth. The measurements were performed on two Varian LINACs: C-series Trilogy and TrueBeam. Each sequence was delivered three times and the dose readings for the corresponding segments were averaged. The effects of MU/segment, dose rate, and LINAC type on the relative dose variation (Δ(i)) were compared using F-tests (α = 0.05). RESULTS: On the Trilogy, large Δ(i) was observed in small MU segments: at 1 MU/segment, the maximum Δ(i) was 10.1% and 57.9% at 100 MU/min and 600 MU/min, respectively. Also, the first segment of each sequence consistently overshot (Δ(i) > 0), while the last segment consistently undershot (Δ(i) < 0). On the TrueBeam, at 1 MU/segment, Δ(i) ranged from 3.0% to 4.5% at 100 and 600 MU/min; no obvious overshoot/undershoot trend was observed. F-tests showed statistically significant difference [(1 - ß) =1.0000] between the Trilogy and the TrueBeam up to 10 MU/segment, at all dose rates greater than 100 MU/min. The linear trend of decreasing dose accuracy as a function of increasing dose rate on the Trilogy is no longer apparent on TrueBeam, even for dose rates as high as 2400 MU/min. Dose inaccuracy averaged over all ten segments in each beam delivery sequence was larger for Trilogy than TrueBeam, with the largest discrepancy (0.2% vs 3%) occurring for 1 MU/segment beams at both 300 and 600 MU/min. CONCLUSIONS: Earlier generations of Varian LINACs exhibited large dose variations for small MU segments in SMLC-IMRT delivery. Our results confirmed these findings. The dose delivery accuracy for SMLC-IMRT is significantly improved on TrueBeam compared to Trilogy for every combination of low MU/segment (1-10) and high dose rate (200-600 MU/min), in part due to the faster sampling rate (100 vs 20 Hz) and enhanced electronic integration of the MLC controller with the LINAC. SMLC-IMRT can be implemented on TrueBeam with higher dose accuracy per beam (±0.2% vs ±3%) than previous generations of Varian C-series LINACs for 1 MU/segment delivered at 600 MU/min).
Subject(s)
Particle Accelerators , Radiation Dosage , Radiotherapy, Intensity-Modulated/instrumentation , Humans , Radiometry , Radiotherapy DosageABSTRACT
PURPOSE: The aim of this study was to quantify the effect of four image registration methods on lung texture features extracted from serial computed tomography (CT) scans obtained from healthy human subjects. METHODS: Two chest CT scans acquired at different time points were collected retrospectively for each of 27 patients. Following automated lung segmentation, each follow-up CT scan was registered to the baseline scan using four algorithms: (1) rigid, (2) affine, (3) B-splines deformable, and (4) demons deformable. The registration accuracy for each scan pair was evaluated by measuring the Euclidean distance between 150 identified landmarks. On average, 1432 spatially matched 32 × 32-pixel region-of-interest (ROI) pairs were automatically extracted from each scan pair. First-order, fractal, Fourier, Laws' filter, and gray-level co-occurrence matrix texture features were calculated in each ROI, for a total of 140 features. Agreement between baseline and follow-up scan ROI feature values was assessed by Bland-Altman analysis for each feature; the range spanned by the 95% limits of agreement of feature value differences was calculated and normalized by the average feature value to obtain the normalized range of agreement (nRoA). Features with small nRoA were considered "registration-stable." The normalized bias for each feature was calculated from the feature value differences between baseline and follow-up scans averaged across all ROIs in every patient. Because patients had "normal" chest CT scans, minimal change in texture feature values between scan pairs was anticipated, with the expectation of small bias and narrow limits of agreement. RESULTS: Registration with demons reduced the Euclidean distance between landmarks such that only 9% of landmarks were separated by ≥1 mm, compared with rigid (98%), affine (95%), and B-splines (90%). Ninety-nine of the 140 (71%) features analyzed yielded nRoA > 50% for all registration methods, indicating that the majority of feature values were perturbed following registration. Nineteen of the features (14%) had nRoA < 15% following demons registration, indicating relative feature value stability. Student's t-tests showed that the nRoA of these 19 features was significantly larger when rigid, affine, or B-splines registration methods were used compared with demons registration. Demons registration yielded greater normalized bias in feature value change than B-splines registration, though this difference was not significant (p = 0.15). CONCLUSIONS: Demons registration provided higher spatial accuracy between matched anatomic landmarks in serial CT scans than rigid, affine, or B-splines algorithms. Texture feature changes calculated in healthy lung tissue from serial CT scans were smaller following demons registration compared with all other algorithms. Though registration altered the values of the majority of texture features, 19 features remained relatively stable after demons registration, indicating their potential for detecting pathologic change in serial CT scans. Combined use of accurate deformable registration using demons and texture analysis may allow for quantitative evaluation of local changes in lung tissue due to disease progression or treatment response.
Subject(s)
Lung/diagnostic imaging , Lung/pathology , Radiographic Image Enhancement/methods , Tomography, X-Ray Computed/methods , Adolescent , Adult , Aged , Algorithms , Female , Fourier Analysis , Fractals , Humans , Male , Middle Aged , Reference Standards , Reproducibility of Results , Retrospective Studies , SoftwareABSTRACT
Purpose: Deep learning (DL) applications strongly depend on the training dataset and convolutional neural network architecture; however, it is unclear how to objectively select such parameters. We investigate the classification performance of different DL models and training schemes for the anatomic classification of cone-beam computed tomography (CBCT) projections. Approach: CBCT scans from 1055 patients were collected and manually classified into five anatomic classes and used to develop DL models to predict the anatomic class from single x-ray projections. VGG-16, Xception, and Inception v3 architectures were trained with 75% of the data, and the remaining 25% was used for testing and evaluation. To study the dependence of the classification performance on dataset size, training data was downsampled to various dataset sizes. Gradient-weighted class activation maps (grad-CAM) were generated using the model with highest classification performance, to identify regions with strong influence on CNN decisions. Results: The highest precision and recall values were achieved with VGG-16. One of the best performing combinations was the VGG-16 trained with 90 deg projections (mean class precision = 0.87). The training dataset size could be reduced to â¼ 50 % of its initial size, without compromising the classification performance. For correctly classified cases, Grad-CAM were more heavily weighted for anatomically relevant regions. Conclusions: It was possible to determine those dependencies with a higher influence on the classification performance of DL models for the studied task. Grad-CAM enabled the identification of possible sources of class confusion.
ABSTRACT
PURPOSE: Our purpose was to characterize the radiation doses to organs-at-risk (OAR) in the phase I trial (NCT02608385) that established safety/efficacy of stereotactic body radiation therapy (SBRT) using NRG-BR001 dose constraints combined with programmed cell death protein 1 blockade for metastatic disease. METHODS AND MATERIALS: Between January 2016 and May 2018, 73 patients with advanced solid tumors were treated with SBRT followed by pembrolizumab. Tumor volumes (gross tumor volume/internal tumor volume) were delineated for each metastasis, with planning target volume contraction to limit OAR dose per protocol (n = 54) or when gross tumor volume/internal tumor volume > 65 cm3 (n = 19). For 20 OAR, doses were compared with NRG-BR001 constraints. Protocol constraints were considered challenged when the minimum of the highest dose received by ≥6 patients without dose-limiting toxicities (DLTs) (Dmax6th) was ≥70% of the protocol constraint. RESULTS: A total of 151 metastases were irradiated including 32 peripheral lung, 23 central lung, 13 mediastinal/cervical, 24 liver, 28 abdominal-pelvic, 16 osseous, and 15 spinal metastases. A median of 2 metastases (range, 2-4) with mean volumes of 33.5 cm3 (range, 0.4-391 cm3) were treated using average planning target volumes of 50.7 cm3 (range, 3.2-161 cm3). At least 1 dose constraint from NRG-BR001 was exceeded in 38 of 73 (52%) patients. OAR constraints were challenged in 10 serial organs (gastrointestinal, cardio-pulmonary, musculoskeletal, and nervous systems) and 1 parallel OAR (lung). Grade 3 DLTs occurred in 6 patients, including pneumonitis (n = 3), colitis (n = 2), and hepatic failure (n = 1). In 4 patients, the toxicity could be directly attributed to the planned dose to OAR (ie, pneumonitis due to high lung dose or colitis due to high bowel dose). CONCLUSIONS: Multisite SBRT in combination with programmed cell death protein 1 blockade was safely tolerated when treating critical central, abdominal-pelvic, and peripheral OAR nearing NRG-BR001 constraints with clinically acceptable toxicity in the corresponding organ systems. The observed relationship between dose and DLTs in 4 of 6 patients indicates that NRG-BR001 dose constraints should be respected in subsequent trials to maintain clinical safety.
Subject(s)
Lung Neoplasms , Radiosurgery , Antibodies, Monoclonal, Humanized , Humans , Lung Neoplasms/surgery , Organs at Risk , Prospective Studies , Radiosurgery/adverse effects , Radiotherapy Dosage , Radiotherapy Planning, Computer-AssistedABSTRACT
The clinical use of surface imaging has increased dramatically, with demonstrated utility for initial patient positioning, real-time motion monitoring, and beam gating in a variety of anatomical sites. The Therapy Physics Subcommittee and the Imaging for Treatment Verification Working Group of the American Association of Physicists in Medicine commissioned Task Group 302 to review the current clinical uses of surface imaging and emerging clinical applications. The specific charge of this task group was to provide technical guidelines for clinical indications of use for general positioning, breast deep-inspiration breath hold treatment, and frameless stereotactic radiosurgery. Additionally, the task group was charged with providing commissioning and on-going quality assurance (QA) requirements for surface-guided radiation therapy (SGRT) as part of a comprehensive QA program including risk assessment. Workflow considerations for other anatomic sites and for computed tomography simulation, including motion management, are also discussed. Finally, developing clinical applications, such as stereotactic body radiotherapy (SBRT) or proton radiotherapy, are presented. The recommendations made in this report, which are summarized at the end of the report, are applicable to all video-based SGRT systems available at the time of writing.