Understanding entrance-air-kerma as a quality-control metric for dual-energy x-ray absorptiometry.

PURPOSE: The low exposures, unique x-ray beam geometry, and scanning design in dual-energy x-ray absorptiometry (DXA) make measurement and quality-control strategies different from traditional x-ray equipment. This study examines the dependence of measured entrance-air-kerma (EAK) on both dose sensor type and scan length. The feasibility of using EAK to compare scanner output between different scan modes, individual scanners, and scanner platforms was also established. Finally, the congruence between measured and vendor-reported EAK was analyzed. METHODS: Four Hologic DXA scanners at two institutions and all four available scan modes were tested. EAK was measured directly by three types of Radcal dose sensors: 60-cc pancake ion-chamber (IC), 180-cc pancake IC, and solid-state detector. The coefficient of variation (COV) was used to assess the dependence of EAK on scan length. Variations in EAK between the types of dose sensors as well as measured versus vendor-reported values were evaluated using Bland-Altman analysis: mean ±95% prediction interval (PI): 1.96σ. RESULTS: Dose sensor variations in EAK were minimal, with a -3.5 ± 3.5% (mean ±95% PI) percent difference between the two sizes of IC's. The solid-state detector produced highly similar measurements to the 180-cc IC. These small differences were consistent across all scanners and all scan modes tested. Neither measured nor vendor-reported EAK values were found to show relevant dependence on scan length, with all COV values ≤4%. Differences between measured and reported EAK were higher at -6 ± 48%. Likely errors in vendor-reported EAK calculations were also identified. CONCLUSION: It is feasible to quantify DXA scanner stability using EAK as a quality-control metric with a variety of solid-state and IC dose sensors, and the scan length used is not critical. Although vendor-reported EAK was consistent among scanners of the same platform, measured EAK varied significantly from scanner to scanner. As a result, measured and reported EAK may not always be comparable.

Temperature mapping of exothermic in situ chemistry: imaging of thermoembolization via MR.

Purpose: MR temperature imaging (MRTI) was employed for visualizing the spatiotemporal evolution of the exotherm of thermoembolization, an investigative transarterial treatment for solid tumors. Materials and methods: Five explanted kidneys were injected with thermoembolic solutions, and monitored by MRTI. In three nonselective experiments, 5 ml of 4 mol/l dichloroacetyl chloride (DCA-Cl) solution in a hydrocarbon vehicle was injected via the main renal artery. For two of these three, MRTI temperature data were compared to fiber optic thermal probes. Another two kidneys received selective injections, treating only portions of the kidneys with 1 ml of 2 mol/l DCA-Cl. MRTI data were acquired and compared to changes in pre- and post-injection CT. Specimens were bisected and photographed for gross pathology 24 h post-procedure. Results: MRTI temperature estimates were within ±1 °C of the probes. In experiments without probes, MRTI measured increases of 30 °C. Some regions had not reached peak temperature by the end of the >18 min acquisition. MRTI indicated the initial heating occurred in the renal cortex, gradually spreading more proximally toward the main renal artery. Gross pathology showed the nonselective injection denatured the entire kidney whereas in the selective injections, only the treated territory was coagulated. Conclusion: The spatiotemporal evolution of thermoembolization was visualized for the first time using noninvasive MRTI, providing unique insight into the thermodynamics of thermoembolization. Précis Thermoembolization is being investigated as a novel transarterial treatment. In order to begin to characterize delivery of this novel treatment modality and aid translation from the laboratory to patients, we employ MR temperature imaging to visualize the spatiotemporal distribution of temperature from thermoembolization in ex vivo tissue.

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

PURPOSE: 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. METHODS: A closed-form steady state model is trained on and then subsequently compared to N = 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 (ω) and optical parameter (µeff) values, throughout a parameter space totalling 11 440 value-pairs. This represents a lookup table of µeff-ω pairs with the corresponding DSC value for each patient dataset. The µeff-ω 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 ω and µeff. RESULTS: 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 (p < 0.001). CONCLUSIONS: 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.