Cystic Brain Metastasis Outcomes After Gamma Knife Radiation Therapy.

Purpose: The response of cystic brain metastases (BMets) to radiation therapy is poorly understood, with conflicting results regarding local control, overall survival, and treatment-related toxicity. This study aims to examine the role of Gamma Knife (GK) in managing cystic BMets. Methods and Materials: Volumetric analysis was conducted to measure tumor and edema volume at the time of GK and follow-up magnetic resonance imaging studies. Survival was described using the Kaplan-Meier method, and the cumulative incidence of progression was described using the Aalen-Johansen estimator. We evaluated the association of 4 variables with survival using Cox regression analysis. Results: Between 2016 and 2021, 54 patients with 83 cystic BMets were treated with GK at our institution. Lung cancer was the most common pathology (51.9%), followed by breast cancer (13.0%). The mean target volume was 2.7 cm3 (range, 0.1-39.0 cm3), and the mean edema volume was 13.9 cm3 (range, 0-165.5 cm3). The median prescription dose of single-fraction and fractionated GK was 20 Gy (range, 14-27.5 Gy). With a median follow-up of 8.9 months, the median survival time (MST) was 11.1 months, and the 1-year local control rate was 75.9%. Gamma Knife was associated with decreased tumor and edema volumes over time, although 68.5% of patients required steroids after GK. Patients whose tumors grew beyond baseline after GK received significantly more whole-brain radiation therapy (WBRT) before GK than those whose tumors declined after GK. Higher age at diagnosis of BMets and pre-GK systemic therapy were associated with worse survival, with an MST of 7.8 months in patients who received it compared with 23.3 months in those who did not. Conclusions: Pre-GK WBRT may select for BMets with increased radioresistance. This study highlights the ability of GK to control cystic BMets with the cost of high posttreatment steroid use.

Symptomatic radionecrosis after postoperative but not preoperative stereotactic radiosurgery in a single patient: illustrative case.

BACKGROUND: Standard of care for brain metastases involves stereotactic radiosurgery (SRS). For cases that also require surgery because of lesion size, edema, or neurological symptoms, whether to provide pre- or postoperative SRS has become a prevalent debate. OBSERVATIONS: Herein, the unique case of a patient with brain metastases of the same pathology and similar size in two different brain locations at two different times is described. The patient underwent surgery with preoperative SRS for the first lesion and surgery with postoperative SRS for the second lesion. Although both treatments resulted in successful local control, the location that received postoperative SRS developed symptomatic and rapidly progressive radiation necrosis (RN) requiring a third craniotomy. LESSONS: Large randomized controlled trials are ongoing to compare pre- versus postoperative SRS for the treatment of symptomatic brain metastases (e.g., study NRG-BN012). Recent interest in preoperative SRS has emerged from its theoretical potential to decrease rates of postoperative RN and leptomeningeal disease. This valuable case in which both therapies were applied in a single patient with a single pathology and similar lesions provides evidence supportive of preoperative SRS.

Predicting Treatment Response From Extracellular Volume Fraction for Chemoradiation Therapy of Pancreatic Cancer.

PURPOSE: Dual-energy computed tomography (DECT) data can be used to calculate the extracellular volume fraction (ECVf) in tumors, which has been correlated with treatment outcome. This study sought to find a correlation between ECVf and treatment response as measured by the change in cancer antigen (CA) 19 to 9 during chemoradiation therapy (CRT) for pancreatic cancer. METHODS AND MATERIALS: Dual-energy CT data acquired during the late arterial contrast phase in the standard radiation therapy simulation on a dual-source DECT simulator for 25 patients with pancreatic cancer, along with their CA19-9 and hematocrit data, were analyzed. Each patient underwent preoperative CRT with a prescription of 50.4 Gy in 28 fractions. The patients were chosen based on the presence of a solid tumor in the pancreas that could be clearly delineated. A region of interest (ROI) was placed in the tumor and in the aorta. From the ratio of the iodine density calculated from the DECT in the ROI and the hematocrit taken at the time of simulation, the ECVf was calculated. The ECVf was then compared with the change in CA19-9 before and after the CRT. Distant metastases as the cause of CA19-9 elevation were ruled out on subsequent restaging images before surgery. The DECT-derived iodine ratio was validated using a phantom study. RESULTS: The DECT-derived iodine concentration agreed with the phantom measurements (R2, 1.0). The average hematocrit, ECVf, and change in CA19-9 during the treatment for the 25 patients was 35.6 ± 5.4%, 7.3 ± 4.9%, and -4.6 ± 21.8 respectively. A linear correlation was found between the ECVf and the change in CA19-9, with an R2 of 0.7: ΔCA19-9 = 3.63 × ECVf - 31.1. The correlation was statistically significant (P = .006). CONCLUSIONS: The calculated ECV fraction based on iodine maps from dual-source DECT may be used to predict treatment response after neoadjuvant chemoradiation therapy for pancreatic cancer.

Technical Note: Using virtual noncontrast images from dual-energy CT to eliminate the need of precontrast CT for x-ray radiation treatment planning of abdominal tumors†.

PURPOSE: Radiation therapy (RT) planning frequently utilizes contrast-enhanced CT. However, dose calculations should not be performed on a contrast-enhanced CT because the patient will not receive bolus during treatment. It is typical to acquire CT twice during RT simulation: once before injection of bolus and once after. The registration between these datasets introduces errors. In this work, we investigate the use of virtual noncontrast images (VNC) derived from dual-energy CT (DECT) to eliminate the precontrast CT and the registration error. METHODS: CT datasets, including conventional 120 kVp pre- and postcontrast CTs and postcontrast DECT, acquired for ten pancreatic cancer patients were evaluated. The DECTs were acquired simultaneously using a dual source (DS) CT simulator. VNC and virtual mono-energetic images (VMI) were derived from DECTs. Gross tumor volumes (GTV), planning target volumes (PTV), and organs at risks (OAR) were delineated on the postcontrast CT and then populated to the precontrast CT and the VNC. An IMRT plan (50.4 Gy in 28 fractions) was then optimized on the precontrast CT. Dose distributions were recalculated on the VNC images. Contours from the pre- and postcontrast CTs and the dose distributions based on both were compared. RESULTS: On average, the distance of centroids of the populated duodenum contours on precontrast CT differed by 6.0 ± 4.0 mm from those on postcontrast CTs. The dose distributions on the precontrast CT and VNC were almost identical. The PTV mean and maximum doses differed by 0.1% and 0.2% between the two plans, respectively. CONCLUSION: The VNC derived from DECT can be used to replace the conventional precontrast CT scan for RT planning, eliminating the need for an additional precontrast CT scan and eliminating the registration errors. Thus, VNC can become an important asset to the future of RT.

Improving Structure Delineation for Radiation Therapy Planning Using Dual-Energy CT.

PURPOSE: We present the advantages of using dual-energy CT (DECT) for radiation therapy (RT) planning based on our clinical experience. METHODS: DECT data acquired for 20 representative patients of different tumor sites and/or clinical situations with dual-source simultaneous scanning (Drive, Siemens) and single-source sequential scanning (Definition, Siemens) using 80 and 140-kVp X-ray beams were analyzed. The data were used to derive iodine maps, fat maps, and mono-energetic images (MEIs) from 40 to 190 keV to exploit the energy dependence of X-ray attenuation. The advantages of using these DECT-derived images for RT planning were investigated. RESULTS: When comparing 40 keV MEIs to conventional 120-kVp CT, soft tissue contrast between the duodenum and pancreatic head was enhanced by a factor of 2.8. For a cholangiocarcinoma patient, contrast between tumor and surrounding tissue was increased by 96 HU and contrast-to-noise ratio was increased by up to 60% for 40 keV MEIs compared to conventional CT. Simultaneous dual-source DECT also preserved spatial resolution in comparison to sequential DECT as evidenced by the identification of vasculature in a pancreas patient. Volume of artifacts for five patients with titanium implants was reduced by over 95% for 190 keV MEIs compared to 120-kVp CT images. A 367-cm3 region of photon starvation was identified by low CT numbers in the soft tissue of a mantle patient in a conventional CT scan but was eliminated in a 190 keV MEI. Fat maps enhanced image contrast as demonstrated by a meningioma patient. CONCLUSION: The use of DECT for RT simulation offers clinically meaningful advantages through improved simulation workflow and enhanced structure delineation for RT planning.

Estimation of changing gross tumor volume from longitudinal CTs during radiation therapy delivery based on a texture analysis with classifier algorithms: a proof-of-concept study.

BACKGROUND: Adaptive radiation therapy (ART) is moving into the clinic rapidly. Capability of delineating the tumor change as a result of treatment response during treatment delivery is essential for ART. During image-guided radiation therapy (IGRT), a CT or cone-beam CT is taken at the time of daily setup and the tumor is not visible by eye in regions of soft tissue due to low contrast. The scope of this paper is to develop a method using a classifier trained on non-contrast CT textures, to estimate the gross tumor volume (GTV) of the day (GTVd) from daily (longitudinal) CTs acquired during the course of IGRT when the tumor is not visible. METHODS: CT textures from daily diagnostic-quality CTs routinely acquired during IGRT using an in-room CT were analyzed. Pretreatment GTV was delineated from pre-RT diagnostic images and populated to the first daily CT. Maps of first-order textures (mean, SD, entropy, skewness and kurtosis) and short-range second-order textures were created from the first daily CT. The classifier was trained to sort voxels into GTV and surrounding tissue on subsequent daily CTs over the course of RT. Optimum combinations of textures was defined by repeating the training process with all possible texture combinations. The trained classifier was used to identify voxels belonging to the GTVd, based on the CT of the day. Posttreatment GTV delineated from the post-RT follow-up images was populated to the last daily CT and used to validate the last GTVd delineated by the classifier. To demonstrate the concept, the method was described using three representative treatment sites, e.g., lung, breast and pancreatic tumors. RESULTS: Comparing the classifier map generated from a new CT to the initial training CT, the dice coefficient (DC) for GTV in lung is 83% on the eighth treatment and 84% on the last. The DC for the breast GTV is 56% mid-treatment and 65% at the last treatment. In the case of the pancreas with the least in organ tissue contrast, the DC for 4 cases ranges from 21% to 77% for the last treatment compared with the post-RT diagnostic CT. The Housdorff distance (HD) ranged from 2.9 to 5.9 mm with the mean GTV RECIST dimension of 22.75 mm long by 14.7 mm short. CONCLUSIONS: It is feasible to estimate the general region of the GTV of the day from the daily CT acquired during RT, based on CT textures, using a trained voxel classifier algorithm. The obtained GTV may be used as a starting point for an accurate GTV delineation in online adaptive replanning. Further study with larger patient datasets is required to improve the robustness of the algorithms.

Serial T2-Weighted Magnetic Resonance Images Acquired on a 1.5 Tesla Magnetic Resonance Linear Accelerator Reveal Radiomic Feature Variation in Organs at Risk: An Exploratory Analysis of Novel Metrics of Tissue Response in Prostate Cancer.

"Delta-radiomics" investigates variations in quantitative image metrics over time and can yield important clinical information. We hypothesized that in patients undergoing active radiation therapy (RT) for prostate cancer (PCa), there would exist observable variation in the quantitative metrics that describe the T2-weighted (T2W) intensity histogram in the prostate and surrounding organs at risk (OAR) over time. We investigated the feasibility of acquisition and subsequent analysis of the delta-radiomic profiles of these regions of interest (ROI) in serial T2W magnetic resonance (MR) images obtained on a 1.5 Tesla (T) Magnetic Resonance Linear Accelerator (MRL). Principally, we sought to illustrate the significance of longitudinal radiomic data acquisition for tissue response monitoring and provide a framework for future hypothesis driven research. Patients with PCa undergoing treatment with RT were compiled from an ongoing prospective observational imaging trial using a 1.5 T MRL (NCT30500081). Contiguous axial slices of prostate parenchyma were contoured and temporally normalized to sections of Sartorius muscle which served as a control. Similarly, contiguous sections of rectal and bladder wall adjacent to the prostate were contoured and temporally normalized to regions of these organs further removed from the planning target volume (PTV). First order statistical descriptors of the T2W intensity histogram were extracted and evaluated for changes over time using linear mixed effects regression modeling and post-hoc contrasts. Benjamini-Hochberg corrections were employed to reduce the effects of multiple testing and control for the false discovery rate (FDR). Four patients with a median age of 69 comprised this exploratory cohort. One patient had low-risk disease, two had intermediate (one favorable, one unfavorable), and one had high risk disease. Three out of four patients underwent definitive radiation to 75.6 Gray (Gy) in 42 fractions and one received hypofractionated therapy to a total dose of 70 Gy over 28 fractions, and all received treatment on a conventional linear accelerator. The most significant acute toxicity event was grade 2 GU dysfunction observed in two patients. Follow up ranged from 1 month to 10 months post treatment, and no long-term complications were reported in patients who completed treatment at least one month prior. Bladder wall adjacent to the prostate demonstrated significant variation in the mean and median metric values after the first week of treatment. In addition, rectal wall adjacent to the prostate exhibited significant variation in the mean, median, and standard deviation metric values by the second week of treatment. No significant variation in any radiomic feature was observed in the Sartorius control. This exploratory study is one of the earliest examining the delta-radiomic characteristics of the T2W intensity histogram in OAR extracted from images acquired on a 1.5 T MRL in patients actively being treated with RT for PCa. We demonstrated a feasible approach to longitudinal radiomic data acquisition providing limitless opportunity for future research. Analysis of the delta-radiomic profiles in OAR revealed significant variation in metrics after only one week of RT in bladder and rectal wall adjacent to the prostate. These findings must be further investigated and validated with expanded data sets with long-term follow up and correlation to clinical outcomes including toxicity and tumor control.

Time stability of delta-radiomics features and the impact on patient analysis in longitudinal CT images.

PURPOSE: This study first aims to show that the values of texture features extracted from phantoms are stable over clinical timescales. Second, that changes in patients' feature values over the course of radiation therapy (RT) are treatment induced and statistically significant. METHODS: The CT datasets of a 3D printed anatomically informed texture phantom containing liver and low-contrast modules, and the homogeneous module of the Catphan 500-Series phantom, were acquired once per week over the course of a 6-week period, to simulate the timescale of conventional RT duration. A Definition AS Open CT scanner on rails (Siemens) and our institution's standard abdominal protocol were used. In each phantom module, 8 regions of interest (20 cm 3 ) were selected and 50 texture features were extracted from each module over the longitudinal dataset. The time stability of each feature was evaluated. The expected variation over the treatment timescale was quantified for each texture (module). Subsequently, the pancreas heads of 10 patients who underwent RT for adenocarcinoma of the pancreas head with a pathologic response of at least "moderate" (grade 2), were contoured on the daily CTs acquired using the same scanner. The pancreas heads were contoured on one image per week. Mean CT number, skewness, kurtosis, and coarseness were extracted from these data. The phantom modules were shown to be accurate representations of these features in the pancreas data. The change in the feature value between fractions 2 and 26 was compared with the phantom data in order to identify significant changes in feature value. RESULTS: Of the 50 features examined in all 3 phantom modules, 47 were found to have zero time-trend when a fit assuming homogeneous variance was used. When a fit allowing for heterogeneous variance was used, 49 features were found to have zero time-trend. Features were stable and repeatable within a feature-specific confidence interval over the 6-week period of acquisition in all three phantom modules. Changes in feature value between fractions 2 and 26 were highly patient specific. Mean CT number was found to decrease significantly in 7 of 10 patients and increase significantly in one patient. Skewness increased significantly in one patient and decreased significantly in one patient. Kurtosis decreased significantly in four patients and increased significantly in one patient. Coarseness increased significantly in seven patients and decreased significantly in one patient. Only one patient experienced no significant changes in feature value. CONCLUSION: The CT texture feature measurements of phantoms are stable and repeatable within a feature-specific confidence interval in all three phantom modules. This suggests that the changes observed in features extracted from longitudinal patient CT data may be treatment induced, and demonstrates their potentiality for early assessment of treatment response.

Technical Note: Enhancing soft tissue contrast and radiation-induced image changes with dual-energy CT for radiation therapy.

PURPOSE: The purpose of this work is to investigate the use of low-energy monoenergetic decompositions obtained from dual-energy CT (DECT) to enhance image contrast and the detection of radiation-induced changes of CT textures in pancreatic cancer. METHODS: The DECT data acquired for 10 consecutive pancreatic cancer patients during routine nongated CT-guided radiation therapy (RT) using an in-room CT (Definition AS Open, Siemens Healthcare, Malvern, PA) were analyzed. With a sequential DE protocol, the scanner rapidly performs two helical acquisitions, the first at a tube voltage of 80 kVp and the second at a tube voltage of 140 kVp. Virtual monoenergetic images across a range of energies from 40 to 140 keV were reconstructed using an image-based material decomposition. Intravenous (IV) bolus-free contrast enhancement in pancreas patient tumors was measured across a spectrum of monoenergies. For treatment response assessment, the changes in CT histogram features (including mean CT number (MCTN), entropy, kurtosis) in pancreas tumors were measured during treatment. The results from the monoenergetic decompositions were compared to those obtained from the standard 120 kVp CT protocol for the same subjects. RESULTS: Data of monoenergetic decompositions of the 10 patients confirmed the expected enhancement of soft tissue contrast as the energy is decreased. The changes in the selected CT histogram features in the pancreas during RT delivery were amplified with the low-energy monoenergetic decompositions, as compared to the changes measured from the 120 kVp CTs. For the patients studied, the average reduction in the MCTN in pancreas from the first to the last (the 28th) treatment fraction was 4.09 HU for the standard 120 kVp and 11.15 HU for the 40 keV monoenergetic decomposition. CONCLUSIONS: Low-energy monoenergetic decompositions from DECT substantially increase soft tissue contrast and increase the magnitude of radiation-induced changes in CT histogram textures during RT delivery for pancreatic cancer. Therefore, quantitative DECT may assist the detection of early RT response.

Reducing radiation dose and enhancing imaging quality of 4DCT for radiation therapy using iterative reconstruction algorithms.

PURPOSE: Four-dimensional computed tomography (CT) images are typically used to quantify the necessary internal target volumes for thoracic and abdominal tumors. However, 4-dimensional CT is typically associated with excessive imaging dose to patients and the situation is exacerbated when using repeat 4-dimensional CT imaging on a weekly or daily basis throughout fractionated therapy. The aim of this work is to evaluate an iterative reconstruction (IR) algorithm that helps reduce the imaging dose to the patient while maintaining imaging quality as quantified by point spread function and contrast-to-noise ratios (CNRs). METHODS AND MATERIALS: An IR algorithm, SAFIRE, was applied to CT data of a phantom and patients with varying CT doses and reconstruction kernels. Phantom data enable measurements of spatial resolution, contrast, and noise. The impact of SAFIRE on 4-dimensional CT was assessed with patient data acquired at 2 different dose levels during image guided radiation therapy with an in-room CT. RESULTS: Phantom data demonstrate that IR reduces noise approximately in proportion to the number of iterations indicated by the strength (SAFIRE 1 to SAFIRE 5). Spatial resolution and contrast are conserved independent of dose and reconstruction parameters. The CNR increases with an increase of imaging dose or an increase in the number of iterations. The use of IR on CT sets confirms the results that were derived from phantom scans. The IR significantly enhances single breathing phase CTs in 4-dimensional CT sets as assessed by CT number discrimination. Furthermore, the IR of the low dose 4-dimensional CT features a 45% increase in the CNR in comparison with the standard dose 4-dimensional CT. CONCLUSIONS: The use of IR algorithms reduces noise while preserving spatial resolution and contrast, as evaluated from both phantom and patient CT data sets. For 4-dimensional CT, the IR can significantly improve image quality and reduce imaging dose without compromising image quality.

Preliminary results on the feasibility of using ultrasound to monitor intrafractional motion during radiation therapy for pancreatic cancer.

PURPOSE: Substantial intrafraction organ motion during radiation therapy (RT) for pancreatic cancer is well recognized as a major limiting factor for accurate delivery of RT. The aim of this work is to determine the feasibility of monitoring the intrafractional motion of the pancreas or surrounding structures using ultrasound for RT delivery. METHODS: Transabdominal ultrasound (TAUS) and 4DCT data were acquired on ten pancreatic cancer patients during radiation therapy process in a prospective study. In addition, TAUS and MRI were collected for five healthy volunteers. The portal vein (PV) and the head of the pancreas (HP) along with other structures were contoured on these images. Volume changes, distance between the HP and PV, and motion difference between the HP and PV were measured to examine whether PV can be used as a motion surrogate for HP. TAUS images were acquired and processed using a research version of the Clarity autoscan ultrasound system (CAUS). Motion monitoring was performed with the ultrasound probe mounted on an arm fixed to the couch. Video segments of the monitoring sessions were captured. RESULTS: On TAUS, PV is better visualized than HP. The measured mean volume deviation for all patients for the HP and PV was 1.4 and 0.6 ml, respectively. The distance between the HP and PV was close to a constant with 0.22 mm mean deviation throughout the ten breathing phases. The mean of the absolute motion difference for all patients was 1.7 ± 0.8 mm in LR, 1.5 ± 0.5 mm in AP, and 2.3 ± 0.7 mm in SI, suggesting that the PV is a good surrogate for HP motion estimation. By using this surrogate, the HP motion tracking using TAUS was demonstrated. CONCLUSIONS: Large intrafractional organ motion due to respiratory and/or bowel motion is a limiting factor in administering curative radiation doses to pancreatic tumors. The authors investigate the use of real-time ultrasound to track pancreas motion. Due to the poor visibility of the pancreas head on an ultrasound image, the portal vein is identified as a surrogate. The authors have demonstrated the feasibility of tracking HP motion through the localization of the PV using TAUS. This will potentially allow real-time tracking of intrafractional motion to justify small PTV-margins and to account for unusual motions, thus, improving normal tissue sparing.