Liver diffusivity in healthy volunteers and patients with chronic liver disease: comparison of breathhold and free-breathing techniques.

PURPOSE: To compare liver ADC obtained with breathhold and free-breathing diffusion weighted imaging (DWI) in healthy volunteers and patients with liver disease. MATERIALS AND METHODS: Twenty-eight subjects, 12 healthy volunteers and 16 patients (9 NAFLD, 7 chronic active HCV), underwent breathhold (BH) and free-breathing (FB) DWI MRI at 1.5 Tesla. Pearson's correlation coefficient was used to determine correlation while paired t-tests assessed differences between BH and FB ADC. Estimated bias was calculated using the Bland-Altman method. RESULTS: Liver ADC (×10(-3) mm(2) /s) was lower on BH for all groups (mean difference 0.36 ± 0.20; P < 0.01). ADC was higher in healthy volunteers (BH 1.80 ± 0.18; FB 2.24 ± 0.20) compared with NAFLD patients (BH 1.43 ± 0.27; FB 1.78 ± 0.28) (P < 0.001) and HCV patients (BH 1.63 ± 0.191; FB 1.88 ± 0.12). Overall correlation between BH and FB ADC was (r = 0.75), greatest in NAFLD (r = 0.90) compared with the correlation in HCV (r = 0.24) and healthy subjects (r = 0.34). Bland-Altman plots did not show agreement in mean absolute difference and estimated bias between subjects. CONCLUSION: Correlation between BH and FB liver ADC is moderate indicating that BH and FB should not be used interchangeably. Additionally, the lower ADC values in BH versus FB should be accounted for when comparing different liver DWI studies.

MRI steatosis grading: development and initial validation of a color mapping system.

OBJECTIVE: The purpose of this article is to develop and validate a chemical-shift imaging-derived color mapping system for evaluation of liver steatosis. MATERIALS AND METHODS: Opposed phase MRI was evaluated for 85 subjects (51 with presumed nonalcoholic fatty liver disease and 34 healthy volunteers). Liver signal intensity loss was compared with histologic analysis for 52 subjects, assuming grade 0 steatosis for healthy volunteers, to determine signal-intensity-loss threshold points differentiating steatosis grades and subsequent Spearman correlation. Color scale grading was then applied for 78 subjects. Interpretation of color maps for steatosis severity and heterogeneity was performed by three readers. Analyses of agreement among readers and of color map steatosis grade with biopsy were performed using weighted kappa values. RESULTS: The numbers of subjects with steatosis grades 0, 1, 2, and 3 were 41, 12, 13, and 19, respectively. A correlation of 0.90 was obtained using selected threshold values of 5.9% or less, 6-26.1%, 26.2-36.8%, and greater than 36.8% for steatosis grades 0, 1, 2, and 3, respectively. Interobserver agreement for color map grading of steatosis was excellent (κ = 0.93-0.94). Color map interpretation for all readers also showed excellent agreement with histologic findings for whole liver (κ = 0.82-0.86) and estimated biopsy site location (κ = 0.81-0.86; anterior region of right lobe). Heterogeneous steatosis on color maps was identified in 56-60% of subjects with nonalcoholic fatty liver disease and in 7% of healthy volunteers and was associated with greater disagreement between color map and histology grading (61-74%) compared with the whole group (37-40%). CONCLUSION: MRI-derived color map estimation of liver steatosis grade appears to be reproducible and accurate.

Effect of novel amplitude/phase binning algorithm on commercial four-dimensional computed tomography quality.

PURPOSE: Respiratory motion is a significant source of anatomic uncertainty in radiotherapy planning and can result in errors of portal size and the subsequent radiation dose. Although four-dimensional computed tomography allows for more accurate analysis of the respiratory cycle, breathing irregularities during data acquisition can cause considerable image distortions. The aim of this study was to examine the effect of respiratory irregularities on four-dimensional computed tomography, and to evaluate a novel image reconstruction algorithm using percentile-based tagging of the respiratory cycle. METHODS AND MATERIALS: Respiratory-correlated helical computed tomography scans were acquired for 11 consecutive patients. The inspiration and expiration data sets were reconstructed using the default phase-based method, as well as a novel respiration percentile-based method with patient-specific metrics to define the ranges of the reconstruction. The image output was analyzed in a blinded fashion for the phase- and percentile-based reconstructions to determine the prevalence and severity of the image artifacts. RESULTS: The percentile-based algorithm resulted in a significant reduction in artifact severity compared with the phase-based algorithm, although the overall artifact prevalence did not differ between the two algorithms. The magnitude of differences in respiratory tag placement between the phase- and percentile-based algorithms correlated with the presence of image artifacts. CONCLUSION: The results of our study have indicated that our novel four-dimensional computed tomography reconstruction method could be useful in detecting clinically relevant image distortions that might otherwise go unnoticed and to reduce the image distortion associated with some respiratory irregularities. Additional work is necessary to assess the clinical impact on areas of possible irregular breathing.

Assessment of intrafraction mediastinal and hilar lymph node movement and comparison to lung tumor motion using four-dimensional CT.

PURPOSE: To quantify the amount of free-breathing motion measured using Four-dimensional (4D) CT scans of mediastinal and hilar lymph nodes and to compare this motion to the primary lung tumor motion. METHODS AND MATERIALS: Twenty patients with primary lung cancer, radiographically positive lymph nodes, and prior 4D CT scans were retrospectively analyzed. The 4D CT data sets were divided into four respiratory phases, and the primary tumor and radiographically positive nodes were contoured. Geometric and volumetric analysis was performed to analyze the motion of the primary tumors and the lymph nodes. RESULTS: The mean lymph node motion was 2.6 mm in the mediolateral direction, 2.5 mm in the anterior-posterior direction, and 5.2 mm in the cranial-caudal direction with a maximum of 14.4 mm. All lymph nodes were found to move inferiorly during inspiration, with 12.5% of nodes moving more than 1 cm. Lymph nodes located below the carina showed significantly more motion than those above the carina (p = 0.01). In comparing the primary tumor motion to the lymph node motion, no correlation was identified. CONCLUSIONS: Four-dimensional CT scans can be used to measure the motion of the primary lung tumor and pathologic lymph nodes encountered during the respiratory cycle. Both the primary lung tumor and the lymph node must to be examined to assess their individual degree of motion. This study demonstrates the need for individualized plans to assess the heterogeneous motion encountered in both primary lung tumors and among lymph node stations.

A semi-automatic method for peak and valley detection in free-breathing respiratory waveforms.

The existing commercial software often inadequately determines respiratory peaks for patients in respiration correlated computed tomography. A semi-automatic method was developed for peak and valley detection in free-breathing respiratory waveforms. First the waveform is separated into breath cycles by identifying intercepts of a moving average curve with the inspiration and expiration branches of the waveform. Peaks and valleys were then defined, respectively, as the maximum and minimum between pairs of alternating inspiration and expiration intercepts. Finally, automatic corrections and manual user interventions were employed. On average for each of the 20 patients, 99% of 307 peaks and valleys were automatically detected in 2.8 s. This method was robust for bellows waveforms with large variations.

Novel breathing motion model for radiotherapy.

PURPOSE: An accurate model of breathing motion under quiet respiration is desirable to obtain the most accurate and conformal dose distributions for mobile lung cancer lesions. On the basis of recent lung motion measurements and the physiologic functioning of the lungs, we have determined that the motion of lung and lung tumor tissues can be modeled as a function of five degrees of freedom, the position of the tissues at a user-specified reference breathing phase, tidal volume and its temporal derivative airflow (tidal volume phase space). Time is an implicit variable in this model. METHODS AND MATERIALS: To test this hypothesis, a mathematical model of motion was developed that described the motion of objects p in the lungs as linear functions of tidal volume and airflow. The position of an object was described relative to its position -->P0 at the reference tidal volume and zero airflow, and the motion of the object was referenced to this position. Hysteresis behavior was hypothesized to be caused by pressure imbalances in the lung during breathing and was, in this model, a function of airflow. The motion was modeled as independent tidal volume and airflow displacement vectors, with the position of the object at time t equal to the vector sum -->rP(t) = -->rv(t) + -->rf(t) where -->rv(t) and -->rf(t) were displacement vectors with magnitudes approximated by linear functions of the tidal volume and airflow. To test this model, we analyzed five-dimensional CT scans (CT scans acquired with simultaneous real-time monitoring of the tidal volume) of 4 patients. The scans were acquired throughout the lungs, but the trajectories were analyzed in the couch positions near the diaphragm. A template-matching algorithm was implemented to identify the positions of the points throughout the 15 scans. In total, 76 points throughout the 4 patients were tracked. The lateral motion of these points was minimal; thus, the model was described in two spatial dimensions, with a total of six parameters necessary to describe the 30 degrees of freedom inherent in the 15 positions. RESULTS: For the 76 evaluated points, the average discrepancy (the distance between the measured and prediction positions) of the 15 locations for each tracked point was 0.75 +/- 0.25 mm, with an average maximal discrepancy of 1.55 +/- 0.54 mm. The average discrepancy was also tabulated as a fraction of the breathing motion. Discrepancies of <10% and 15% of the overall motion occurred in 73% and 95% of the tracked points, respectively. CONCLUSION: The motion tracking algorithms are being improved and automated to provide more motion data to test the models. This may allow a measurement of the motion-fitting parameters throughout the lungs. If the parameters vary smoothly, interpolation may be possible, yielding a continuous mathematical model of the breathing motion throughout the lungs. The utility of the model will depend on its stability as a function of time. If the model is only robust during the measurement session, it may be useful for determining lung function. If it is robust for weeks, it may be useful for treatment planning and gating of lung treatments. The use of tidal volume phase space for characterizing breathing motion appears to have provided, for the first time, the potential for a patient-specific mathematical model of breathing motion.

Comparison of spirometry and abdominal height as four-dimensional computed tomography metrics in lung.

An important consideration in four-dimensional CT scanning is the selection of a breathing metric for sorting the CT data and modeling internal motion. This study compared two noninvasive breathing metrics, spirometry and abdominal height, against internal air content, used as a surrogate for internal motion. Both metrics were shown to be accurate, but the spirometry showed a stronger and more reproducible relationship than the abdominal height in the lung. The abdominal height was known to be affected by sensor placement and patient positioning while the spirometer exhibited signal drift. By combining these two, a normalization of the drift-free metric to tidal volume may be generated and the overall metric precision may be improved.

Quantitation of the reconstruction quality of a four-dimensional computed tomography process for lung cancer patients.

We have developed a four-dimensional computed tomography (4D CT) technique for mapping breathing motion in radiotherapy treatment planning. A multislice CT scanner (1.5 mm slices) operated in ciné mode was used to acquire 12 contiguous slices in each couch position for 15 consecutive scans (0.5 s rotation, 0.25 s between scans) while the patient underwent simultaneous quantitative spirometry measurements to provide a sorting metric. The spirometry-sorted scans were used to reconstruct a 4D data set. A critical factor for 4D CT is quantifying the reconstructed data set quality which we measure by correlating the metric used relative to internal-object motion. For this study, the internal air content within the lung was used as a surrogate for internal motion measurements. Thresholding and image morphological operations were applied to delineate the air-containing tissues (lungs, trachea) from each CT slice. The Hounsfield values were converted to the internal air content (V). The relationship between the air content and spirometer-measured tidal volume (v) was found to be quite linear throughout the lungs and was used to estimate the overall accuracy and precision of tidal volume-sorted 4D CT. Inspection of the CT-scan air content as a function of tidal volume showed excellent correlations (typically r>0.99) throughout the lung volume. Because of the discovered linear relationship, the ratio of internal air content to tidal volume was indicative of the fraction of air change in each couch position. Theoretically, due to air density differences within the lung and in room, the sum of these ratios would equal 1.11. For 12 patients, the mean value was 1.08 +/- 0.06, indicating the high quality of spirometry-based image sorting. The residual of a first-order fit between v and V was used to estimate the process precision. For all patients, the precision was better than 8%, with a mean value of 5.1% +/- 1.9%. This quantitative analysis highlights the value of using spirometry as the metric in sorting CT scans. The 4D reconstruction provides the CT data required to measure the three-dimensional trajectory of tumor and lung tissue during free breathing.

A method for the reconstruction of four-dimensional synchronized CT scans acquired during free breathing.

Breathing motion is a significant source of error in radiotherapy treatment planning for the thorax and upper abdomen. Accounting for breathing motion has a profound effect on the size of conformal radiation portals employed in these sites. Breathing motion also causes artifacts and distortions in treatment planning computed tomography (CT) scans acquired during free breathing and also causes a breakdown of the assumption of the superposition of radiation portals in intensity-modulated radiation therapy, possibly leading to significant dose delivery errors. Proposed voluntary and involuntary breath-hold techniques have the potential for reducing or eliminating the effects of breathing motion, however, they are limited in practice, by the fact that many lung cancer patients cannot tolerate holding their breath. We present an alternative solution to accounting for breathing motion in radiotherapy treatment planning, where multislice CT scans are collected simultaneously with digital spirometry over many free breathing cycles to create a four-dimensional (4-D) image set, where tidal lung volume is the additional dimension. An analysis of this 4-D data leads to methods for digital-spirometry, based elimination or accounting of breathing motion artifacts in radiotherapy treatment planning for free breathing patients. The 4-D image set is generated by sorting free-breathing multislice CT scans according to user-defined tidal-volume bins. A multislice CT scanner is operated in the ciné mode, acquiring 15 scans per couch position, while the patient undergoes simultaneous digital-spirometry measurements. The spirometry is used to retrospectively sort the CT scans by their correlated tidal lung volume within the patient's normal breathing cycle. This method has been prototyped using data from three lung cancer patients. The actual tidal lung volumes agreed with the specified bin volumes within standard deviations ranging between 22 and 33 cm3. An analysis of sagittal and coronal images demonstrated relatively small (<1 cm) motion artifacts along the diaphragm, even for tidal volumes where the rate of breathing motion is greatest. While still under development, this technology has the potential for revolutionizing the radiotherapy treatment planning for the thorax and upper abdomen.

Comparison of spirometry and abdominal height as four-dimensional computed tomography metrics in lung.

An important consideration in four-dimensional CT scanning is the selection of a breathing metric for sorting the CT data and modeling internal motion. This study compared two noninvasive breathing metrics, spirometry and abdominal height, against internal air content, used as a surrogate for internal motion. Both metrics were shown to be accurate, but the spirometry showed a stronger and more reproducible relationship than the abdominal height in the lung. The abdominal height was known to be affected by sensor placement and patient positioning while the spirometer exhibited signal drift. By combining these two, a normalization of the drift-free metric to tidal volume may be generated and the overall metric precision may be improved.