Zsolt Gabos

Prognostic Significance of Human Epidermal Growth Factor Receptor Positivity for the Development of Brain Metastasis After Newly Diagnosed Breast Cancer

PURPOSE As survival in breast cancer patients is improving, brain metastases are becoming increasingly prevalent. The risk of brain metastases in newly diagnosed human epidermal growth factor receptor 2 (HER-2) -overexpressing breast cancer patients is not yet fully defined. We aimed to analyze the risk of brain metastasis in newly diagnosed HER-2-positive breast cancer patients in comparison with HER-2-negative patients. PATIENTS AND METHODS To determine the incidence of brain metastases in HER-2-overexpressing patients, we analyzed a cohort of newly diagnosed 301 HER-2-positive and 363 HER-2-negative patients identified between January 1998 and December 2003. The association between histologic features and the occurrence of brain metastases was evaluated with univariate and multivariate Cox regression analysis. RESULTS Median follow-up was 3.9 years. Brain metastases were identified in 9% (27 patients) with HER-2-overexpressing breast cancer compared with only 1.9% (7 patients) in the HER-2 negative patients (hazard ratio 4.23 [1.84-9.74], P = .0007). HER-2 overexpression, tumor size larger than 2 cm, at least one positive node, and grade 2/3 disease were predictors of brain metastases in univariate analysis. In multivariate analysis, HER-2 overexpression, tumor size larger than 2 cm, and hormone-receptor negativity were independent prognostic factors for the development of brain metastases, whereas hormone-receptor expression was protective. CONCLUSION Our study shows that newly diagnosed HER-2-overexpressing breast cancer patients are at increased risk for brain metastases. Because most brain metastases occur after the development of systemic disease, these findings prompt consideration of brain prophylaxis strategies with HER-2-inhibiting small molecules able to cross the blood-brain barrier and/or radiologic screening to detect asymptomatic brain metastases.

Nomogram to Predict Subsequent Brain Metastasis in Patients With Metastatic Breast Cancer

PURPOSE Brain metastasis is usually a fatal event in patients with stage IV breast cancer. We hypothesized that its occurrence can be predicted if a clinical nomogram can be developed, thus allowing for selection of enriched patient populations for prevention trials. PATIENTS AND METHODS Electronic medical records of patients with metastatic breast cancer were retrospectively reviewed for the period between January 2000 and February 2007 under a study approved by the institutional review board. A multivariate logistic regression analysis of selected prognostic features was done. A nomogram to predict brain metastasis was constructed and validated in a cohort of 128 patients with brain metastasis treated at the Cross Cancer Institute (Edmonton, Alberta, Canada). Results Of 2,136 patients with breast cancer, 362 developed subsequent brain metastasis. Age, grade, negative status of estrogen receptor and human epidermal growth factor receptor 2, number of metastatic sites (one v > one), and short disease-free survival were significantly and independently associated with subsequent brain metastasis. The nomogram showed an area under the receiver operating characteristic curve (AUC) of 0.68 (95% CI, 0.66 to 0.69) in the training set. The validation set showed a good discrimination with an AUC of 0.74 (95% CI, 0.70 to 0.79). The nomogram was well calibrated, with no significant difference between the predicted and the observed probabilities. CONCLUSION We have developed a robust tool that is able to predict subsequent brain metastasis in patients with breast cancer with nonbrain metastatic disease. Selection of an enriched patient population at high risk for brain metastasis will facilitate the design of trials aiming at its prevention.

Neural-network based autocontouring algorithm for intrafractional lung-tumor tracking using Linac-MR.

PURPOSE To develop a neural-network based autocontouring algorithm for intrafractional lung-tumor tracking using Linac-MR and evaluate its performance with phantom and in-vivo MR images. METHODS An autocontouring algorithm was developed to determine both the shape and position of a lung tumor from each intrafractional MR image. A pulse-coupled neural network was implemented in the algorithm for contrast improvement of the tumor region. Prior to treatment, to initiate the algorithm, an expert user needs to contour the tumor and its maximum anticipated range of motion in pretreatment MR images. During treatment, however, the algorithm processes each intrafractional MR image and automatically generates a tumor contour without further user input. The algorithm is designed to produce a tumor contour that is the most similar to the experts manual one. To evaluate the autocontouring algorithm in the authors Linac-MR environment which utilizes a 0.5 T MRI, a motion phantom and four lung cancer patients were imaged with 3 T MRI during normal breathing, and the image noise was degraded to reflect the image noise at 0.5 T. Each of the pseudo-0.5 T images was autocontoured using the authors algorithm. In each test image, the Dice similarity index (DSI) and Hausdorff distance (HD) between the experts manual contour and the algorithm generated contour were calculated, and their centroid positions were compared (Δd centroid). RESULTS The algorithm successfully contoured the shape of a moving tumor from dynamic MR images acquired every 275 ms. From the phantom study, mean DSI of 0.95-0.96, mean HD of 2.61-2.82 mm, and mean Δd centroid of 0.68-0.93 mm were achieved. From the in-vivo study, the authors algorithm achieved mean DSI of 0.87-0.92, mean HD of 3.12-4.35 mm, as well as Δd centroid of 1.03-1.35 mm. Autocontouring speed was less than 20 ms for each image. CONCLUSIONS The authors have developed and evaluated a lung tumor autocontouring algorithm for intrafractional tumor tracking using Linac-MR. The autocontouring performance in the Linac-MR environment was evaluated using phantom and in-vivo MR images. From the in-vivo study, the authors algorithm achieved 87%-92% of contouring agreement and centroid tracking accuracy of 1.03-1.35 mm. These results demonstrate the feasibility of lung tumor autocontouring in the authors laboratorys Linac-MR environment.

Outcomes in stage I non-small cell lung cancer following the introduction of stereotactic body radiotherapy in Alberta - A population-based study.

PURPOSE To review outcomes of patients with stage I non-small cell lung cancer (NSCLC) following the introduction of stereotactic body radiation therapy (SBRT). METHODS SBRT cases were linked to the cancer registry database along with clinical, treatment and health service parameters for n=2146 cases of stage I NSCLC diagnosed between 2005 and 2011. The pre-diagnosis Aggregated Clinical Risk Grouping score (ACRG3) was used as a proxy for pre-treatment patient comorbidity. A Cox regression model and the concordance statistic (C-statistic) were used to examine variables predicted for overall survival (OS). RESULTS The SBRT utilization rate increased annually with superior OS to conventional RT (median survival [MS] of 39.4 VS. 23.5months, P<0.001) despite higher ACRG3 scores. Surgical patients were younger, had lower ACRG3, achieving MS of 69.6months. Regression analysis indicated both Surgery (hazard ratio [HR]=0.23, 95% CI: 0.18-0.28) and SBRT (HR=0.33, 95% CI: 0.21-0.51) remained most strongly associated with OS. ACRG3 (HR=0.79, P<0.001) and age (HR=0.83, P=0.03) were independently associated with OS. The OS model was associated with the C-statistic at 0.86, 95% CI: 0.81-0.90. CONCLUSION In stage I NSCLC patients treated with surgery have the best survival. SBRT demonstrates improved OS compared to conventional RT. C-statistic result demonstrates discrimination of treatment selection factors on OS.

Prior data assisted compressed sensing: A novel MR imaging strategy for real time tracking of lung tumors

PURPOSE Hybrid radiotherapy-MRI devices promise real time tracking of moving tumors to focus the radiation portals to the tumor during irradiation. This approach will benefit from the increased temporal resolution of MRIs data acquisition and reconstruction. In this work, the authors propose a novel spatial-temporal compressed sensing (CS) imaging strategy for the real time MRI--prior data assisted compressed sensing (PDACS), which aims to improve the image quality of the conventional CS without significantly increasing reconstruction times. METHODS Conventional 2D CS requires a random sampling of partial k-space data, as well as an iterative reconstruction that simultaneously enforces the images sparsity in a transform domain as well as maintains the fidelity to the acquired k-space. PDACS method requires the additional acquisition of the prior data, and for reconstruction, it additionally enforces fidelity to the prior k-space domain similar to viewsharing. In this work, the authors evaluated the proposed PDACS method by comparing its results to those obtained from the 2D CS and viewsharing methods when performed individually. All three methods are used to reconstruct images from lung cancer patients whose tumors move and who are likely to benefit from lung tumor tracking. The patients are scanned, using a 3T MRI, under free breathing using the fully sampled k-space with 2D dynamic bSSFP sequence in a sagittal plane containing lung tumor. These images form a reference set for the evaluation of the partial k-space methods. To create partial k-space, the fully sampled k-space is retrospectively undersampled to obtain a range of acquisition acceleration factors, and reconstructed with 2D-CS, PDACS, and viewshare methods. For evaluation, metrics assessing global image artifacts as well as tumor contour shape fidelity are determined from the reconstructed images. These analyses are performed both for the original 3T images and those at a simulated 0.5T equivalent noise level. RESULTS In the 3.0T images, the PDACS strategy is shown to give superior results compared to viewshare and conventional 2D CS using all metrics. The 2D-CS tends to perform better than viewshare at the low acceleration factors, while the opposite is true at the high acceleration factors. At simulated 0.5T images, PDACS method performs only marginally better than the viewsharing method, both of which are superior compared to 2D CS. The PDACS image reconstruction time (0.3 s/image) is similar to that of the conventional 2D CS. CONCLUSIONS The PDACS method can potentially improve the real time tracking of moving tumors by significantly increasing MRIs data acquisition speeds. In 3T images, the PDACS method does provide a benefit over the other two methods in terms of both the overall image quality and the ability to accurately and automatically contour the tumor shape. MRIs data acquisition may be accelerated using the simpler viewsharing strategy at the lower, 0.5T magnetic field, as the marginal benefit of the PDACS method may not justify its additional reconstruction times.

Three-Arm Randomized Phase III Trial: Quality Aloe and Placebo Cream Versus Powder as Skin Treatment During Breast Cancer Radiation Therapy

BACKGROUND The efficacy of aloe extract in reducing radiation-induced skin injury is controversial. The purpose of the present 3-arm randomized trial was to test the efficacy of quality-tested aloe extract in reducing the severity of radiation-induced skin injury and, secondarily, to examine the effect of a moist cream versus a dry powder skin care regimen. MATERIALS AND METHODS A total of 248 patients with breast cancer were randomized to powder, aloe cream, or placebo cream. Acute skin toxicity was scored weekly and after treatment at weeks 1, 2, and 4 using a modified 10-point Catterall scale. The patients scored their symptom severity using a 6-point Likert scale and kept an acute phase diary. RESULTS The aloe formulation did not reduce acute skin toxicity or symptom severity. Patients with a greater body mass index were more likely to develop acute skin toxicity. A similar pattern of increased skin reaction toxicity occurred with both study creams compared with the dry powder regimen. CONCLUSION No evidence was found to support prophylactic application of quality aloe extract or cream to improve the symptoms or reduce the skin reaction severity. Our results support a dry skin care regimen of powder during radiation therapy.

Skin-sparing Helical Tomotherapy vs 3D-conformal Radiotherapy for Adjuvant Breast Radiotherapy: In Vivo Skin Dosimetry Study

PURPOSE We investigated whether treatment-planning system (TPS)-calculated dose accurately reflects skin dose received for patients receiving adjuvant breast radiotherapy (RT) with standard three-dimensional conformal RT (3D-CRT) or skin-sparing helical tomotherapy (HT). METHODS AND MATERIALS Fifty patients enrolled in a randomized controlled trial investigating acute skin toxicity from adjuvant breast RT with 3D-CRT compared to skin-sparing HT, where a 5-mm strip of ipsilateral breast skin was spared. Thermoluminescent dosimetry or optically stimulated luminescence measurements were made in multiple locations and were compared to TPS-calculated doses. Skin dosimetric parameters and acute skin toxicity were recorded in these patients. RESULTS With HT there was a significant correlation between calculated and measured dose in the medial and lateral ipsilateral breast (r = 0.67, P<.001; r = 0.44, P=.03, respectively) and the medial and central contralateral breast (r = 0.73, P<.001; r = 0.88, P<.001, respectively). With 3D-CRT there was a significant correlation in the medial and lateral ipsilateral breast (r = 0.45, P=.03; r = 0.68, P<.001, respectively); the medial and central contralateral breast (r = 0.62, P=.001; r = 0.86, P<.001, respectively); and the mid neck (r = 0.42, P=.04, respectively). On average, HT-calculated dose overestimated the measured dose by 14%; 3D-CRT underestimated the dose by 0.4%. There was a borderline association between highest measured skin dose and moist desquamation (P=.05). Skin-sparing HT had greater skin homogeneity (homogeneity index of 1.39 vs 1.65, respectively; P=.005) than 3D-CRT plans. HT plans had a lower skin(V50) (1.4% vs 5.9%, respectively; P=.001) but higher skin(V40) and skin(V30) (71.7% vs 64.0%, P=.02; and 99.0% vs 93.8%, P=.001, respectively) than 3D-CRT plans. CONCLUSION The 3D-CRT TPS more accurately reflected skin dose than the HT TPS, which tended to overestimate dose received by 14% in patients receiving adjuvant breast RT.

Dose-escalated Hypofractionated Intensity-modulated Radiation Therapy With Concurrent Chemotherapy for Inoperable or Unresectable Non-small Cell Lung Cancer

Purpose: The local control of inoperable non-small cell lung cancer (NSCLC) using standard radiotherapy (RT) doses is inadequate. Dose escalation is a potential strategy to improve the local control for patients with NSCLC; however, the optimal dose required for local control in this setting is unknown. Methods and Materials: Patients with unresectable or inoperable stage II/III NSCLC with ECOG⩽1 received 48 Gy in 20 daily fractions using intensity-modulated radiotherapy, followed by 1 of 3 boost dose levels: 16.8 Gy/7 (cumulative 2 Gy equivalent dose [EQD2]≅76 Gy/38), 20.0 Gy/7 (EQD2≅84 Gy/42), and 22.7 Gy/7 (EQD2≅92 Gy/46). Two cycles of cisplatin/etoposide chemotherapy were given concurrent with RT. The maximum tolerated dose was defined as the dose at which ≥30% experienced dose-limiting toxicity (any NCIC Common Terminology for Adverse Events V3.0 grade 3 or higher acute toxicity). Results: Twelve patients completed treatment with a median follow-up of 22 months (range, 7 to 48). The median age was 72 (range, 54 to 80) and 50% of patients had adenocarcinoma. Five, 3, and 4 patients were treated on dose levels 1, 2, and 3, respectively. No dose-limiting toxicity was observed. One-year local progression-free survival and overall survival estimates were 81% and 58%, respectively. Conclusions: Hypofractionated intensity-modulated radiotherapy was well tolerated and provided meaningful local control for patients with locally advanced inoperable NSCLC. The maximum tolerated dose of RT in this setting lies beyond an EQD2 of 92 Gy/46 and further dose escalation in this setting is warranted.

A planning comparison of 3-dimensional conformal multiple static field, conformal arc, and volumetric modulated arc therapy for the delivery of stereotactic body radiotherapy for early stage lung cancer.

The primary objective of this study was to compare dosimetric variables as well as treatment times of multiple static fields (MSFs), conformal arcs (CAs), and volumetric modulated arc therapy (VMAT) techniques for the treatment of early stage lung cancer using stereotactic body radiotherapy (SBRT). Treatments of 23 patients previously treated with MSF of 48Gy to 95% of the planning target volume (PTV) in 4 fractions were replanned using CA and VMAT techniques. Dosimetric parameters of the Radiation Therapy Oncology Group (RTOG) 0915 trial were evaluated, along with the van׳t Riet conformation number (CN), monitor units (MUs), and actual and calculated treatment times. Paired t-tests for noninferiority were used to compare the 3 techniques. CA had significant dosimetric improvements over MSF for the ratio of the prescription isodose volume to PTV (R100%, p < 0.0001), the maximum dose 2cm away from the PTV (D2cm, p = 0.005), and van׳t Riet CN (p < 0.0001). CA was not statistically inferior to MSF for the 50% prescription isodose volume to PTV (R50%, p = 0.05). VMAT was significantly better than CA for R100% (p < 0.0001), R50% (p < 0.0001), D2cm (p = 0.006), and CN (p < 0.0001). CA plans had significantly shorter treatment times than those of VMAT (p < 0.0001). Both CA and VMAT planning showed significant dosimetric improvements and shorter treatment times over those of MSF. VMAT showed the most favorable dosimetry of all 3 techniques; however, the dosimetric effect of tumor motion was not evaluated. CA plans were significantly faster to treat, and minimize the interplay of tumor motion and dynamic multileaf collimator (MLC) motion effects. Given these results, CA has become the treatment technique of choice at our facility.

Improved lung tumor autocontouring algorithm for intrafractional tumor tracking using 0.5 T linac-MR

To add an intelligent parameter optimization capability to our autocontouring algorithm, and evaluate its performance using in-vivo data. Methods An autocontouring algorithm for intrafractional lung-tumor tracking using linac-MR was previously developed based on pulse-coupled neural networks. The algorithms contouring performance is dependent on eight parameters (including four integer parameters). Previously, the parameters were optimized using a time-consuming, exhaustive method. To avoid this inefficiency, adaptive particle swarm optimization (APSO) was adopted in this study, which is a stochastic, non-gradient based optimization algorithm that can handle integer variables. For this study, six non-small cell lung cancer patients were imaged with 3T MRI at ~4 frames per second (2D sagittal plane, free breathing). For each patient, an expert delineated a gold standard contour (ROIstd) of the lung tumor in 130 consecutive images. The first 30 ROIstd were used for parameter optimization, and the rest 100 ROIstd were used to validate autocontours (ROIauto). In each image, Dice similarity index, Hausdorff distance, and centroid position difference (Δdcentroid) were calculated between ROIstd and ROIauto to measure their similarity. Results & Conclusion An efficient, fully automatic parameter optimization was added to our autocontouring algorithm. Using the six patients data, approximately 1/24 time reduction was achieved in parameter optimization (63–125 hrs to 2–4 hrs per patient), while maintaining the same or slightly improved performance.