Investigating magnetic field dose effects in small animals: a Monte Carlo study

Purpose: In MRI-linac treatments, radiation dose distributions are affected by magnetic fields, especially at high-density/low-density interfaces. Radiobiological consequences of magnetic field dose effects are presently unknown and preclinical studies are desirable. This study investigates the optimal combination of beam energy and magnetic field strength needed for preclinical murine studies.Methods: The Monte Carlo code MCNP6 was used to simulate the effects of a magnetic field when irradiating a mouse lung phantom with a 1.0 cm × 1.0 cm photon beam. Magnetic field dose effects were examined using various beam energies (225 kVp, 662 keV [Cs-137], and 1.25MeV [Co-60]) and magnetic field strengths (0.75 T, 1.5 T, and 3 T). The resulting dose distributions were compared to Monte Carlo results for humans with various field sizes and patient geometries using a 6MV/1.5T MRI-linac.Results: In human simulations, the addition of a 1.5 T magnetic field causes an average dose increase of 49% (range: 36% - 60%) to lung at the soft tissue-lung interface and an average dose decrease of 30% (range: 25% - 36%) at the lung-soft tissue interface. In mouse simulations, no magnetic field dose effects were seen with the 225 kVp beam. The dose increase for the Cs-137 beam was 12%, 33%, and 49% for 0.75 T, 1.5 T, and 3.0 T magnetic fields, respectively while the dose decrease was 7%, 23%, and 33%. For the Co-60 beam the dose increase was 14%, 45%, and 41%, and the dose decrease was 18%, 35%, and 35%.Conclusion: The magnetic field dose effects observed in mouse phantoms using a Co-60 beam with 1.5 T or 3 T fields or a Cs-137 beam with a 3T field fall within the range seen in humans treated with an MRI-linac. These irradiator/magnet combinations are therefore suitable for preclinical studies investigating potential biological effects of delivering radiation therapy in the presence of a magnetic field.---------------------------Cite this article as: Rubinstein A, Guindani M, Hazle JD, Court LE. Investigating magnetic field dose effects in small animals: a Monte Carlo study. Int J Cancer Ther Oncol 2014; 2(2):020233. DOI: 10.14319/ijcto.0202.3

Infection Prevention and Control Guideline for Cystic Fibrosis: 2013 Update

The 2013 Infection Prevention and Control (IP&C) Guideline for Cystic Fibrosis (CF) was commissioned by the CF Foundation as an update of the 2003 Infection Control Guideline for CF. During the past decade, new knowledge and new challenges provided the following rationale to develop updated IP&C strategies for this unique population: 1. The need to integrate relevant recommendations from evidence-based guidelines published since 2003 into IP&C practices for CF . These included guidelines from the Centers for Disease Control and Prevention (CDC)/Healthcare Infection Control Practices Advisory Committee (HICPAC), the World Health Organization (WHO), and key professional societies, including the Infectious Diseases Society of America (IDSA) and the Society for Healthcare Epidemiology of America (SHEA). During the past decade, new evidence has led to a renewed emphasis on source containment of potential pathogens and the role played by the contaminated healthcare environment in the transmission of infectious agents. Furthermore, an increased understanding of the importance of the application of implementation science, monitoring adherence, and feedback principles has been shown to increase the effectiveness of IP&C guideline recommendations. 2. Experience with emerging pathogens in the non-CF population has expanded our understanding of droplet transmission of respiratory pathogens and can inform IP&C strategies for CF . These pathogens include severe acute respiratory syndrome coronavirus and the 2009 influenza A H1N1. Lessons learned about preventing transmission of methicillin-resistant Staphylococcus aureus (MRSA) and multidrug-resistant gram-negative pathogens in non-CF patient populations also can inform IP&C strategies for CF

Investigating magnetic field dose effects in small animals: a Monte Carlo study

Purpose: In MRI-linac treatments, radiation dose distributions are affected by magnetic fields, especially at high-density/low-density interfaces. Radiobiological consequences of magnetic field dose effects are presently unknown and preclinical studies are desirable. This study investigates the optimal combination of beam energy and magnetic field strength needed for preclinical murine studies.Methods: The Monte Carlo code MCNP6 was used to simulate the effects of a magnetic field when irradiating a mouse lung phantom with a 1.0 cm × 1.0 cm photon beam. Magnetic field dose effects were examined using various beam energies (225 kVp, 662 keV [Cs-137], and 1.25MeV [Co-60]) and magnetic field strengths (0.75 T, 1.5 T, and 3 T). The resulting dose distributions were compared to Monte Carlo results for humans with various field sizes and patient geometries using a 6MV/1.5T MRI-linac.Results: In human simulations, the addition of a 1.5 T magnetic field causes an average dose increase of 49% (range: 36% - 60%) to lung at the soft tissue-lung interface and an average dose decrease of 30% (range: 25% - 36%) at the lung-soft tissue interface. In mouse simulations, no magnetic field dose effects were seen with the 225 kVp beam. The dose increase for the Cs-137 beam was 12%, 33%, and 49% for 0.75 T, 1.5 T, and 3.0 T magnetic fields, respectively while the dose decrease was 7%, 23%, and 33%. For the Co-60 beam the dose increase was 14%, 45%, and 41%, and the dose decrease was 18%, 35%, and 35%.Conclusion: The magnetic field dose effects observed in mouse phantoms using a Co-60 beam with 1.5 T or 3 T fields or a Cs-137 beam with a 3T field fall within the range seen in humans treated with an MRI-linac. These irradiator/magnet combinations are therefore suitable for preclinical studies investigating potential biological effects of delivering radiation therapy in the presence of a magnetic field.---------------------------Cite this article as: Rubinstein A, Guindani M, Hazle JD, Court LE. Investigating magnetic field dose effects in small animals: a Monte Carlo study. Int J Cancer Ther Oncol 2014; 2(2):020233. DOI: 10.14319/ijcto.0202.33</p

Theoretical model for laser ablation outcome predictions in brain: calibration and validation on clinical MR thermometry images

<p><b>Purpose:</b> Neurosurgical laser ablation is experiencing a renaissance. Computational tools for ablation planning aim to further improve the intervention. Here, global optimisation and inverse problems are demonstrated to train a model that predicts maximum laser ablation extent.</p> <p><b>Methods:</b> A closed-form steady state model is trained on and then subsequently compared to <i>N</i> = 20 retrospective clinical MR thermometry datasets. Dice similarity coefficient (DSC) is calculated to provide a measure of region overlap between the 57 °C isotherms of the thermometry data and the model-predicted ablation regions; 57 °C is a tissue death surrogate at thermal steady state. A global optimisation scheme samples the dominant model parameter sensitivities, blood perfusion (<i>ω</i>) and optical parameter (<i>μ</i>_eff) values, throughout a parameter space totalling 11 440 value-pairs. This represents a lookup table of <i>μ</i>_eff–<i>ω</i> pairs with the corresponding DSC value for each patient dataset. The <i>μ</i>_eff–<i>ω</i> pair with the maximum DSC calibrates the model parameters, maximising predictive value for each patient. Finally, leave-one-out cross-validation with global optimisation information trains the model on the entire clinical dataset, and compares against the model naïvely using literature values for <i>ω</i> and <i>μ</i>_eff.</p> <p><b>Results:</b> When using naïve literature values, the model’s mean DSC is 0.67 whereas the calibrated model produces 0.82 during cross-validation, an improvement of 0.15 in overlap with the patient data. The 95% confidence interval of the mean difference is 0.083–0.23 (<i>p</i> < 0.001).</p> <p><b>Conclusions:</b> During cross-validation, the calibrated model is superior to the naïve model as measured by DSC, with +22% mean prediction accuracy. Calibration empowers a relatively simple model to become more predictive.</p

Technical Note: A Monte Carlo study of magnetic-field-induced radiation dose effects in mice.

PURPOSE:Magnetic fields are known to alter radiation dose deposition. Before patients receive treatment using an MRI-linear accelerator (MRI-Linac), preclinical studies are needed to understand the biological consequences of magnetic-field-induced dose effects. In the present study, the authors sought to identify a beam energy and magnetic field strength combination suitable for preclinical murine experiments. METHODS:Magnetic field dose effects were simulated in a mouse lung phantom using various beam energies (225 kVp, 350 kVp, 662 keV [Cs-137], 2 MV, and 1.25 MeV [Co-60]) and magnetic field strengths (0.75, 1.5, and 3 T). The resulting dose distributions were compared with those in a simulated human lung phantom irradiated with a 6 or 8 MV beam and orthogonal 1.5 T magnetic field. RESULTS:In the human lung phantom, the authors observed a dose increase of 45% and 54% at the soft-tissue-to-lung interface and a dose decrease of 41% and 48% at the lung-to-soft-tissue interface for the 6 and 8 MV beams, respectively. In the mouse simulations, the magnetic fields had no measurable effect on the 225 or 350 kVp dose distribution. The dose increases with the Cs-137 beam for the 0.75, 1.5, and 3 T magnetic fields were 9%, 29%, and 42%, respectively. The dose decreases were 9%, 21%, and 37%. For the 2 MV beam, the dose increases were 16%, 33%, and 31% and the dose decreases were 9%, 19%, and 30%. For the Co-60 beam, the dose increases were 19%, 54%, and 44%, and the dose decreases were 19%, 42%, and 40%. CONCLUSIONS:The magnetic field dose effects in the mouse phantom using a Cs-137, 3 T combination or a Co-60, 1.5 or 3 T combination most closely resemble those in simulated human treatments with a 6 MV, 1.5 T MRI-Linac. The effects with a Co-60, 1.5 T combination most closely resemble those in simulated human treatments with an 8 MV, 1.5 T MRI-Linac

Prospective analysis of in vivo landmark point-based MRI geometric distortion in head and neck cancer patients scanned in immobilized radiation treatment position: Results of a prospective quality assurance protocol

Purpose: Uncertainties related to geometric distortion are a major obstacle for effectively utilizing MRI in radiation oncology. We aim to quantify the geometric distortion in patient images by comparing their in-treatment position MRIs with the corresponding planning CTs, using CT as the non-distorted gold standard. Methods: Twenty-one head and neck cancer patients were imaged with MRI as part of a prospective Institutional Review Board approved study. MR images were acquired with a T2 SE sequence (0.5 Ã 0.5 Ã 2.5 mm voxel size) in the same immobilization position as in the CTs. MRI to CT rigid registration was then done and geometric distortion comparison was assessed by measuring the corresponding anatomical landmarks on both the MRI and the CT images. Several landmark measurements were obtained including; skin to skin (STS), bone to bone, and soft tissue to soft tissue at specific levels in horizontal and vertical planes of both scans. Inter-observer variability was assessed and interclass correlation (ICC) was calculated. Results: A total of 430 landmark measurements were obtained. The median distortion for all landmarks in all scans was 1.06 mm (IQR 0.6â1.98). For each patient 48% of the measurements were done in the right-left direction and 52% were done in the anteroposterior direction. The measured geometric distortion was not statistically different in the right-left direction compared to the anteroposterior direction (1.5 ± 1.6 vs. 1.6 ± 1.7 mm, respectively, p = 0.4). The magnitude of distortion was higher in the STS peripheral landmarks compared to the more central landmarks (2.0 ± 1.9 vs. 1.2 ± 1.3 mm, p < 0.0001). The mean distortion measured by observer one was not significantly different compared to observer 2, 3, and 4 (1.05, 1.23, 1.06 and 1.05 mm, respectively, p = 0.4) with ICC = 0.84. Conclusion: MRI geometric distortions were quantified in radiotherapy planning applications with a clinically insignificant error of less than 2 mm compared to the gold standard CT. Keywords: MRI, CT, Geometric Distortion, Head and Neck Cancer, Radiation Treatment, Quality Assuranc

Chronic Lymphocytic Leukemia Progression Diagnosis with Intrinsic Cellular Patterns via Unsupervised Clustering

Identifying the progression of chronic lymphocytic leukemia (CLL) to accelerated CLL (aCLL) or transformation to diffuse large B-cell lymphoma (Richter transformation; RT) has significant clinical implications as it prompts a major change in patient management. However, the differentiation between these disease phases may be challenging in routine practice. Unsupervised learning has gained increased attention because of its substantial potential in data intrinsic pattern discovery. Here, we demonstrate that cellular feature engineering, identifying cellular phenotypes via unsupervised clustering, provides the most robust analytic performance in analyzing digitized pathology slides (accuracy = 0.925, AUC = 0.978) when compared to alternative approaches, such as mixed features, supervised features, unsupervised/mixed/supervised feature fusion and selection, as well as patch-based convolutional neural network (CNN) feature extraction. We further validate the reproducibility and robustness of unsupervised feature extraction via stability and repeated splitting analysis, supporting its utility as a diagnostic aid in identifying CLL patients with histologic evidence of disease progression. The outcome of this study serves as proof of principle using an unsupervised machine learning scheme to enhance the diagnostic accuracy of the heterogeneous histology patterns that pathologists might not easily see