Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning ...convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Purpose
Stereotactic radiosurgery (SRS) has become a standard of care for patients' with brain metastases (BMs). However, the manual multiple BMs delineation can be time‐consuming and could create an ...efficiency bottleneck in SRS workflow. There is a clinical need for automatic delineation and quantitative evaluation tools. In this study, building on our previous developed deep learning‐based segmentation algorithms, we developed a web‐based automated BMs segmentation and labeling platform to assist the SRS clinical workflow.
Method
This platform was developed based on the Django framework, including a web client and a back‐end server. The web client enables interactions as database access, data import, and image viewing. The server performs the segmentation and labeling tasks including: skull stripping; deep learning‐based BMs segmentation; and affine registration‐based BMs labeling. Additionally, the client can display BMs contours with corresponding atlas labels, and allows further postprocessing tasks including: (a) adjusting window levels; (b) displaying/hiding specific contours; (c) removing false‐positive contours; (d) exporting contours as DICOM RTStruct files; etc.
Results
We evaluated this platform on 10 clinical cases with BMs number varied from 12‐81 per case. The overall operation took about 4–5 min per patient. The segmentation accuracy was evaluated between the manual contour and automatic segmentation with several metrics. The averaged center of mass shift was 1.55 ± 0.36 mm, the Hausdorff distance was 2.98 ± 0.63 mm, the mean of surface‐to‐surface distance (SSD) was 1.06 ± 0.31 mm, and the standard deviation of SSD was 0.80 ± 0.16 mm. In addition, the initial averaged false‐positive over union (FPoU) and false‐negative rate (FNR) were 0.43 ± 0.19 and 0.15 ± 0.10 respectively. After case‐specific postprocessing, the averaged FPoU and FNR were 0.19 ± 0.10 and 0.15 ± 0.10 respectively.
Conclusion
The evaluated web‐based BMs segmentation and labeling platform can substantially improve the clinical efficiency compared to manual contouring. This platform can be a useful tool for assisting SRS treatment planning and treatment follow‐up.
Treatment regimens for locally advanced non-small cell lung cancer (NSCLC) give suboptimal clinical outcomes. Technological advancements such as radiation therapy, the backbone of most treatment ...regimens, may enable more potent and effective therapies. The objective of this study was to escalate radiation therapy to a tumoricidal hypofractionated dose without exceeding the maximally tolerated dose (MTD) in patients with locally advanced NSCLC.
Patients with stage II to IV or recurrent NSCLC and Eastern Cooperative Oncology Group performance status of 2 or greater and not candidates for surgical resection, stereotactic radiation, or concurrent chemoradiation were eligible. Highly conformal radiation therapy was given to treat intrathoracic disease in 15 fractions to a total of 50, 55, or 60 Gy.
Fifty-five patients were enrolled: 15 at the 50-Gy, 21 at the 55-Gy, and 19 at the 60-Gy dose levels. A 90-day follow-up was completed in each group without exceeding the MTD. With a median follow-up of 12.5 months, there were 93 grade ≥ 3 adverse events (AEs), including 39 deaths, although most AEs were considered related to factors other than radiation therapy. One patient from the 55- and 60-Gy dose groups developed grade ≥ 3 esophagitis, and 5, 4, and 4 patients in the respective dose groups experienced grade ≥ 3 dyspnea, but only 2 of these AEs were considered likely related to therapy. There was no association between fraction size and toxicity (P = .24). The median overall survival was 6 months with no significant differences between dose levels (P = .59).
Precision hypofractionated radiation therapy consisting of 60 Gy in 15 fractions for locally advanced NSCLC is generally well tolerated. This treatment regimen could provide patients with poor performance status a potent alternative to chemoradiation. This study has implications for the cost effectiveness of lung cancer therapy. Additional studies of long-term safety and efficacy of this therapy are warranted.
The goal of this study was to explore conceptual benefits of characterizing delineated target volumes based on surface area and to utilize the concept for assessing risk of therapeutic toxicity in ...radiosurgery.
Four computer-generated targets, a sphere, a cylinder, an ellipsoid and a box, were designed for two distinct scenarios. In the first scenario, all targets had identical volumes, and in the second one, all targets had identical surface areas. High quality stereotactic radiosurgery plans with at least 95% target coverage and selectivity were created for each target in both scenarios. Normal brain volumes V12Gy, V14Gy and V16Gy corresponding to received dose of 12 Gy, 14 Gy and 16 Gy, respectively, were computed and analyzed. Additionally, V12Gy and V14Gy volumes and values for seven prospective toxicity variables were recorded for 100 meningioma patients after Gamma Knife radiosurgery. Multivariable stepwise linear regression and best subset linear regression analyses were performed in two statistical software packages, SAS/STAT and R, respectively.
In a phantom study, for the constant volume targets, the volumes of 12 Gy, 14 Gy and 16 Gy isodose clouds were the lowest for the spherical target as an expected corollary of the isoperimetric inequality. For the constant surface area targets, a conventional wisdom is confirmed, as the target volume increases the corresponding volumes V12Gy, V14Gy and V16Gy also increase. In the 100-meningioma patient cohort, the best univariate model featured tumor surface area as the most significantly associated variable with both V12Gy and V14Gy volumes, corresponding to the adjusted R2 values of 0.82 and 0.77, respectively. Two statistical methods converged to matching multivariable models.
In a univariate model, target surface area is a better predictor of spilled dose to normal tissue than target largest dimension or target volume itself. In complex multivariate models, target surface area is an independent variable for modeling radiosurgical normal tissue toxicity risk.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Introduction
Poor outcomes in glioma patients indicate a need to determine prognostic indicators of survival to better guide patient specific treatment options. While preoperative ...neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) have been suggested as prognostic systemic inflammation markers, the impact of post-radiation changes in these cell types is unclear. We sought to identify which hematologic cell measurements before, during, or after radiation predicted for patient survival.
Methods
A cohort of 182 patients with pathologically confirmed gliomas treated at our institution was retrospectively reviewed. Patient blood samples were collected within one month before, during, or within 3 months after radiation for quantification of hematologic cell counts, for which failure patterns were evaluated. Multivariable cox proportional hazards analysis for overall survival (OS) and progression-free survival (PFS) was performed to control for patient variables.
Results
Multivariable analysis identified pre-radiation NLR > 4.0 (Hazard ratio = 1.847, p = 0.0039) and neutrophilia prior to (Hazard ratio = 1.706, p = 0.0185), during (Hazard ratio = 1.641, p = 0.0277), or after (Hazard ratio = 1.517, p = 0.0879) radiation as significant predictors of worse OS, with similar results for PFS. Post-radiation PLR > 200 (Hazard ratio = 0.587, p = 0.0062) and a percent increase in platelets after radiation (Hazard ratio = 0.387, p = 0.0077) were also associated with improved OS. Patients receiving more than 15 fractions of radiation exhibited greater post-radiation decreases in neutrophil and platelet counts than those receiving fewer. Patients receiving dexamethasone during radiation exhibited greater increases in neutrophil counts than those not receiving steroids. Lymphopenia, changes in lymphocyte counts, monocytosis, MLR, and changes in monocyte counts did not impact patient survival.
Conclusion
Neutrophilia at any time interval surrounding radiotherapy, pre-radiation NLR, and post-radiation thrombocytopenia, but not lymphocytes or monocytes, are predictors of poor patient survival in glioma patients.
Purpose
Poor outcomes in IDH wild-type (IDHwt) glioblastomas indicate the need to determine which genetic alterations can indicate poor survival and guidance of patient specific treatment options. We ...sought to identify the genetic alterations in these patients that predict for survival when adjusting particularly for treatments and other genetic alterations.
Methods
A cohort of 167 patients with pathologically confirmed IDHwt glioblastomas treated at our institution was retrospectively reviewed. Next generation sequencing was performed for each patient to determine tumor genetic alterations. Multivariable cox proportional hazards analysis for overall survival (OS) was performed to control for patient variables.
Results
CDKN2A, CDKN2B, and MTAP deletion predict for worse OS independently of other genetic alterations and patient characteristics (hazard ratio HR 2.192,
p
= 0.0017). Patients with CDKN2A copy loss (HR 2.963,
p
= 0.0037) or TERT mutated (HR 2.815,
p
= 0.0008) glioblastomas exhibited significant associations between radiation dose and OS, while CDKN2A and TERT wild type patients did not. CDKN2A deleted patients with NF1 mutations had worse OS (HR 1.990,
p
= 0.0540), while CDKN2A wild type patients had improved OS (HR 0.229,
p
= 0.0723). Patients with TERT mutated glioblastomas who were treated with radiation doses < 45 Gy (HR 3.019,
p
= 0.0010) but not those treated with ≥ 45 Gy exhibited worse OS compared to those without TERT mutations.
Conclusion
In IDHwt glioblastomas, CDKN2A, CDKN2B, and MTAP predict for poor prognosis. TERT and CDKN2A mutations are associated with worse survival only when treated with lower radiation doses, thus potentially providing a genetic marker that can inform clinicians on proper dose-fractionation schemes.
Purpose
Radiosurgery is an established technique to treat cerebral arteriovenous malformations (AVMs). Obliteration of larger AVMs (> 10–15 cm3 or diameter > 3 cm) in a single session is challenging ...with current radiosurgery platforms due to toxicity. We present a novel technique of multistage stereotactic radiosurgery (SRS) for large intracranial arteriovenous malformations (AVM) using the Gamma Knife system.
Materials/Methods
Eighteen patients with large (> 10–15 cm3 or diameter > 3 cm) AVMs, which were previously treated using a staged SRS technique on the Cyberknife platform, were retrospectively selected for this study. The AVMs were contoured and divided into 3–8 subtargets to be treated sequentially in a staged approach at half to 4 week intervals. The prescription dose ranged from 15 Gy to 20 Gy, depending on the subtarget number, volume, and location. Gamma Knife plans using multiple collimator settings were generated and optimized. The coordinates of each shot from the initial plan covering the total AVM target were extracted based on their relative positions within the frame system. The shots were regrouped based on their location with respect to the subtarget contours to generate subplans for each stage. The delivery time of each shot for a subtarget was decay corrected with 60Co for staging the treatment course to generate the same dose distribution as that planned for the total AVM target. Conformality indices and dose–volume analysis were performed to evaluate treatment plans.
Results
With the shot redistribution technique, the composite dose for the multistaged treatment of multiple subtargets is equivalent to the initial plan for total AVM target. Gamma Knife plans resulted in an average PTV coverage of 96.3 ± 0.9% and a PITV of 1.23 ± 0.1. The resulting Conformality indices, V12Gy and R50 dose spillage values were 0.76 ± 0.05, 3.4 ± 1.8, and 3.1 ± 0.5 respectively.
Conclusion
The Gamma Knife system can deliver a multistaged conformal dose to treat large AVMs when correcting for translational setup errors of each shot at each staged treatment.
The quality of radiation therapy (RT) treatment plans directly affects the outcomes of clinical trials. KBP solutions have been utilized in RT plan quality assurance (QA). In this study, we evaluated ...the quality of RT plans for brain and head/neck cancers enrolled in multi-institutional clinical trials utilizing a KBP approach. The evaluation was conducted on 203 glioblastoma (GBM) patients enrolled in NRG-BN001 and 70 nasopharyngeal carcinoma (NPC) patients enrolled in NRG-HN001. For each trial, fifty high-quality photon plans were utilized to build a KBP photon model. A KBP proton model was generated using intensity-modulated proton therapy (IMPT) plans generated on 50 patients originally treated with photon RT. These models were then applied to generate KBP plans for the remaining patients, which were compared against the submitted plans for quality evaluation, including in terms of protocol compliance, target coverage, and organ-at-risk (OAR) doses. RT plans generated by the KBP models were demonstrated to have superior quality compared to the submitted plans. KBP IMPT plans can decrease the variation of proton plan quality and could possibly be used as a tool for developing improved plans in the future. Additionally, the KBP tool proved to be an effective instrument for RT plan QA in multi-center clinical trials.
Introduction
Poor outcomes in glioblastoma patients, despite advancing treatment paradigms, indicate a need to determine non-physiologic prognostic indicators of patient outcome. The impact of ...specific socioeconomic and demographic patient factors on outcomes is unclear. We sought to identify socioeconomic and demographic patient characteristics associated with patient survival and tumor progression, and to characterize treatment options and healthcare utilization.
Methods
A cohort of 169 patients with pathologically confirmed glioblastomas treated at our institution was retrospectively reviewed. Multivariable cox proportional hazards analysis for overall survival (OS) and cumulative incidence of progression was performed. Differences in treatment regimen, patient characteristics, and neuro-oncology office use between different age and depressive disorder history patient subgroups were calculated two-sample
t-
tests, Fisher's exact tests, or linear regression analysis.
Results
The median age of all patients at the time of initiation of radiation therapy was 60.5 years. The median OS of the cohort was 13.1 months. Multivariable analysis identified age (Hazard Ratio 1.02, 95% CI 1.00–1.04) and total resection (Hazard Ratio 0.52, 95% CI 0.33–0.82) as significant predictors of OS. Increased number of radiation fractions (Hazard Ratio 0.90, 95% CI 0.82–0.98), depressive disorder history (Hazard Ratio 0.59, 95% CI 0.37–0.95), and total resection (Hazard Ratio 0.52, 95% CI 0.31–0.88) were associated with decreased incidence of progression. Notably, patients with depressive disorder history were observed to have more neuro-oncology physician office visits over time (median 12 vs. 16 visits,
p
= 0.0121). Patients older than 60 years and those with Medicare (vs. private) insurance were less likely to receive as many radiation fractions (
p
= 0.0014) or receive temozolomide concurrently with radiation (Odds Ratio 0.46,
p
= 0.0139).
Conclusion
Older glioblastoma patients were less likely to receive as diverse of a treatment regimen as their younger counterparts, which may be partially driven by insurance type. Patients with depressive disorder history exhibited reduced incidence of progression, which may be due to more frequent health care contact during neuro-oncology physician office visits.
Detection and segmentation of brain metastases (BMs) play a pivotal role in diagnosis, treatment planning, and follow-up evaluations for effective BM management. Given the rising prevalence of BM ...cases and its predominantly multiple onsets, automated segmentation is becoming necessary in stereotactic radiosurgery. It not only alleviates the clinician's manual workload and improves clinical workflow efficiency but also ensures treatment safety, ultimately improving patient care. Recent strides in machine learning, particularly in deep learning (DL), have revolutionized medical image segmentation, achieving state-of-the-art results. This review aims to analyze auto-segmentation strategies, characterize the utilized data, and assess the performance of cutting-edge BM segmentation methodologies. Additionally, we delve into the challenges confronting BM segmentation and share insights gleaned from our algorithmic and clinical implementation experiences.
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