Mm In Lung Research Articles

Lung and Liver Stereotactic Body Radiation Therapy During Mechanically Assisted Deep Inspiration Breath-Holds: A Prospective Feasibility Trial

PurposeRadiation therapy of tumours subject to breathing-related motion during breath-holds (BH) has the potential to substantially reduce the irradiated volume. Mechanically-assisted and non-invasive ventilation (MANIV) could ensure the target repositioning accuracy during each BH while facilitating treatment feasibility through oxygen supplementation and a perfectly replicated mechanical support. However, there is currently no clinical evidence substantiating the use of MANIV-induced BH for moving tumours. The aim of this work was therefore to evaluate the technique performances under real treatment conditions. Methods and MaterialsPatients eligible for lung or liver stereotactic body radiotherapy were prospectively included in a single-arm trial. The primary endpoint corresponded to the treatment feasibility with MANIV. Secondary outcomes comprised intrafraction geometrical uncertainties extracted from real-time imaging, tolerance to BH and treatment time. ResultsTreatment was successfully delivered in 92.9% (13/14) of patients: one patient with a liver tumour was excluded due to a mechanically-induced gastric insufflation displacing the liver cranially by more than 1 cm. In the Left-right/Anteroposterior/Craniocaudal directions, the recalculated safety margins based on intrafraction positional data were 4.6 mm / 5.1 mm / 5.6 mm and 4.7 mm / 7.3 mm / 5.9 mm for lung and liver lesions, respectively. Compared to the free-breathing internal target volume and mid-position approaches, the average reduction in the planning target volume with MANIV reached -47.2±15.3 %, p<0.001 and -29.4±19.2 %, p=0.007 for intra-thoracic tumours and -23.3±12.4 %, p<0.001 and -9.3±15.3 %, p=0.073 for upper abdominal tumours, respectively. For one liver lesion, large caudal drifts of occasionally more than one centimetre were measured. The total slot time was 53.1 ± 10.6 minutes with a BH comfort level of 80.1±10.6%. ConclusionsMANIV enables high treatment feasibility within a non-selected population. Accurate intrafraction tumour repositioning is achieved for lung tumours. Due to occasional intra-BH caudal drifts, pre-treatment assessment of BH stability for liver lesions is however recommended.

Population-based asymmetric margins for moving targets in real-time tumor tracking.

Both geometric and dosimetric components are commonly considered when determining the margin for planning target volume (PTV). As dose distribution is shaped by controlling beam aperture in peripheral dose prescription and dose-escalated simultaneously integrated boost techniques, adjusting the margin by incorporating the variable dosimetric component into the PTV margin is inappropriate; therefore, geometric components should be accurately estimated for margin calculations. We introduced an asymmetric margin-calculation theory using the guide to the expression of uncertainty in measurement (GUM) and intra-fractional motion. The margins in fiducial marker-based real-time tumor tracking (RTTT) for lung, liver, and pancreatic cancers were calculated and were then evaluated using Monte Carlo (MC) simulations. A total of 74705, 73235, and 164968 sets of intra- and inter-fractional positional data were analyzed for 48 lung, 48 liver, and 25 pancreatic cancer patients, respectively, in RTTT clinical trials. The 2.5th and 97.5th percentiles of the positional error were considered representative values of each fraction of the disease site. The population-based statistics of the probability distributions of these representative positional errors (PD-RPEs) were calculated in six directions. A margin covering 95% of the population was calculated using the proposed formula. The content rate in which the clinical target volume (CTV) was included in the PTV was calculated through MC simulations using the PD-RPEs. The margins required for RTTT were at most 6.2, 4.6, and 3.9mm for lung, liver, and pancreatic cancer, respectively. MC simulations revealed that the median content rates using the proposed margins satisfied 95% for lung and liver cancers and 93% for pancreatic cancer, closer to the expected rates than the margins according to van Herk's formula. Our proposed formula based on the GUM and motion probability distributions (MPD) accurately calculated the practical margin size for fiducial marker-based RTTT. This was verified through MC simulations.

Theoretical Calculation of Population-Based Margins in Fiducial Marker-Based Real-time Tumor Tracking

We introduced a theoretical margin calculation method based on a combination of the guide to the expression of uncertainty in measurement (GUM) and the probability distribution of the tracking error, and determined the population-based margins in fiducial marker-based real-time tumor tracking (RTTT) radiotherapy.A total of 74,705, 73,235, and 164,968 sets of intrafractional X-ray images were analyzed for 47 lung, 48 liver, and 25 pancreatic cancer patients, respectively, in an RTTT clinical trial using a gimbaled Linac. The 2.5th and 97.5th percentiles of the tracking error, defined as the difference between the predicted and detected target positions, were regarded as representative values in each fraction of the disease site. The population-based statistics of the probability distribution of these representative tracking errors (PD-RTEs) were calculated in six directions. The goodness of fit of the PD-RTEs with the normal distribution were tested. The novel margin theory is expressed as follows: Margin = Υ+k⋅√(υ^2+τ^2), where Υ, υ, and τ are the population-based mean difference, interpatient uncertainty, and intrapatient uncertainty of the population of a representative tracking error in each direction, respectively. k is the factor to expect the margin satisfying 95% of the population. Considering that k depended on the target shape, k = 2.0 for the lung and liver cancer, 2.33 for the pancreatic cancer were applied. To verify the margin formula, the content rate in which the CTV was included in the PTV was calculated through Monte Carlo simulation (MCS) using the PD-RTE. The same calculation was also performed using the van Herk's theory intending to cover 90% of the population.The calculated results are shown in Table. The margins on the left, right, anterior, and posterior were within 4.1 mm for all sites. The superior and inferior margins were up to 6.2, 4.7, and 3.9 mm for lung, liver, and pancreatic cancer, respectively. Although some of the PD-RTEs could not be considered normal distributions, MCS revealed that the median content rates using the proposed margins satisfied 95% for lung and liver cancer, and 93% for pancreatic cancer. By contrast, although the median content rate according to van Herk's equation was 89% for pancreatic cancer, the content rates were more than 96% for lung and liver cancer, which was higher than their expected coverage of the population.In this study, we proposed a theoretically determined margin calculation formula for RTTT based on a combination of the GUM and the probability distribution of the tracking errors. The proposed formula appropriately calculated the practical margin size in fiducial marker-based RTTT for lung, liver, and pancreatic cancer.

44 Dynamic Tumor Tracking with SBRT dedicated system VERO (Brainlab): Quality control and PTV volume reduction

Introduction SBRT for mobile tumors requires a breathing control method. Since 2014, the dedicated SBRT system VERO (Brainlab-Mitsubishi) provides a real-time dynamic tracking method: “dynamic tracking” (DT). We present this method and the results obtained for quality control, PTV volume and treatment time reduction. Methods The robotic irradiation head of the VERO system (6 MV) is equipped with a 5 mm MLC and follows in real time the target position, thanks to gyroscopic movements guided by infrared and radiological control. DT method was used for liver and pancreas (41 and 3 patients) and thoracic lesions (60 patients) for which the movement amplitude, evaluated by 4DCT (RPM Varian), was >7 mm and after marker implantation (Visicoil, IBA). The treatment plan (TPS IPLAN, Brainlab) was performed with 6 to 8 non-coplanar beams and the Monte Carlo algorithm for lungs on the exhale phase. PTV Margins were determined with the Van Herk et al. 2000 method. PT V DT volume (using DT) was compared to PT V ITV (calculated with MIP images for Internal Target Volume, ITV method) for 60 patients. Treatment times were evaluated for each session for 104 patients. DT mechanical and dosimetric accuracy were evaluated with QUASAR Respiratory Motion et CIRS 008A dynamic thorax phantoms, EBT3 films associated to Doselab Pro software, and with log files analysis. Quality control for 104 patients was performed with Brainlab mobile platform and calibrated films. Results PTV margins are 5 mm for lung and 8 mm for liver. The mean PT V DT was 28.8 cc (6.5 to 14.3 cc) and 46.4 cc for PT V ITV (10.4 to 139 cc), so a 40% volume reduction. The mean treatment time for DT was 25 min, lower than the one for ITV method for which control CBCT are necessary. The patient breathing rates (frequency and amplitude) are often irregular during treatment and different from the reference 4DCT. This doesn’t affect the treatment delivery and target tracking. With 4 year a follow-up, the clinical tolerance during and after SBRT with DT is very good with 1 case of symptomatic grade 3 radiation pneumonitis (PR) and 8 asymptomatic PR for 60 patients. The DT mecanical accuracy was measured γ 1 (3%-1 mm). Conclusion DT allows treatments with breathing control for all patients, even those with irregular breathing rates. Treatment times are lower than classical treatments based on ITV with an accuracy

Technical Note: Solving the "Chinese postman problem" for effective contour deformation.

To develop a practical approach for accurate contour deformation when deformable image registration (DIR) is used for atlas-based segmentation or contour propagation in image-guided radiotherapy. We developed a contour deformation approach based on 3D mesh operations. The 2D contours represented by a series of points in each slice were first converted to a 3D triangular mesh, which was deformed by the deformation vectors resulting from DIR. A set of parallel 2D planes then cut through the deformed 3D mesh, generating unordered points and line segments, to be reorganized into a set of 2D contour points. The reorganization problem was equivalent to solving the "Chinese postman problem" (CPP) by traversing a graph built from the unordered points with the least cost. Alternatively, deformation could be applied to a binary image converted from the original contours. The deformed binary image was then converted back into contours at the CT slice locations. We validated the mesh-based contour deformation approach using lung and heart contours from 10 patients with thoracic cancer. DIR could change the 3D mesh considerably, complicating 2D contour representations after deformation. CPP could effectively reorganize the points in 2D planes regardless of how complicated the 2D contours were. Among the 10 patients, the Dice similarity coefficient between the mesh-based contour and binary image-based contour was 97.6% ± 0.3% for lung and 97.5% ± 0.7% for heart, and the Hausdoroff distance between them was 19.8 ± 5.1 mm for lung and 6.1 ± 2.2 mm for heart. Subjective evaluation showed that the mesh-based approach could keep fine details, especially for the lung. The image-based approach seemed to overprocess contours and suffered from image resolution limits. We developed a practical approach for accurate contour deformation and demonstrated its effectiveness for both clinical and research applications.

The long- and short-term variability of breathing induced tumor motion in lung and liver over the course of a radiotherapy treatment

PurposeTo evaluate the short and long-term variability of breathing induced tumor motion. Materials and methods3D tumor motion of 19 lung and 18 liver lesions captured over the course of an SBRT treatment were evaluated and compared to the motion on 4D-CT. An implanted fiducial could be used for unambiguous motion information. Fast orthogonal fluoroscopy (FF) sequences, included in the treatment workflow, were used to evaluate motion during treatment.Several motion parameters were compared between different FF sequences from the same fraction to evaluate the intrafraction variability. To assess interfraction variability, amplitude and hysteresis were compared between fractions and with the 3D tumor motion registered by 4D-CT. Population based margins, necessary on top of the ITV to capture all motion variability, were calculated based on the motion captured during treatment. ResultsBaseline drift in the cranio-caudal (CC) or anterior-poster (AP) direction is significant (ie. >5 mm) for a large group of patients, in contrary to intrafraction amplitude and hysteresis variability. However, a correlation between intrafraction amplitude variability and mean motion amplitude was found (Pearson's correlation coefficient, r = 0.72, p < 10−4). Interfraction variability in amplitude is significant for 46% of all lesions. As such, 4D-CT accurately captures the motion during treatment for some fractions but not for all. Accounting for motion variability during treatment increases the PTV margins in all directions, most significantly in CC from 5 mm to 13.7 mm for lung and 8.0 mm for liver. ConclusionBoth short-term and day-to-day tumor motion variability can be significant, especially for lesions moving with amplitudes above 7 mm. Abandoning passive motion management strategies in favor of more active ones is advised.

MO-FG-BRA-07: Intrafractional Motion Effect Can Be Minimized in Tomotherapy Stereotactic Body Radiotherapy (SBRT)

Purpose: Tomotherapy has unique challenges in handling intrafractional motion compared to conventional LINAC. In this study, we analyzed the impact of intrafractional motion on cumulative dosimetry using actual patient motion data and investigated real time jaw/MLC compensation approaches to minimize the motion-induced dose discrepancy in Tomotherapy SBRT treatment. Methods: Intrafractional motion data recorded in two CyberKnife lung treatment cases through fiducial tracking and two LINAC prostate cases through Calypso tracking were used in this study. For each treatment site, one representative case has an average motion (6mm) and one has a large motion (10mm for lung and 15mm for prostate). The cases were re-planned on Tomotherapy for SBRT. Each case was planned with 3 different jaw settings: 1cm static, 2.5cm dynamic, and 5cm dynamic. 4D dose accumulation software was developed to compute dose with the recorded motions and theoretically compensate motions by modifying original jaw and MLC to track the trajectory of the tumor. Results: PTV coverage in Tomotherapy SBRT for patients with intrafractional motion depends on motion type, amplitude and plan settings. For the prostate patient with large motion, PTV coverage changed from 97.2% (motion-free) to 47.1% (target motion-included), 96.6% to 58.5% and 96.3% to 97.8% for the 1cm static jaw, 2.5cm dynamic jaw and 5cm dynamic jaw setting, respectively. For the lung patient with large motion, PTV coverage discrepancies showed a similar trend of change. When the jaw and MLC compensation program was engaged, the motion compromised PTV coverage was recovered back to >95% for all cases and plans. All organs at risk (OAR) were spared with < 5% increase from original motion-free plans. Conclusion: Tomotherapy SBRT is less motion-impacted when 5cm dynamic jaw is used. Once the motion pattern is known, the jaw and MLC compensation program can largely minimize the compromised target coverage and OAR sparing.

SU-C-210-02: Impact of Intrafractional Motion On TomoTherapy Stereotactic Body Radiotherapy (SBRT) 4D Dosimetry

Purpose: TomoTherapy treatment has unique challenges in handling intrafractional motion compared to conventional LINAC. This study is aimed to gain a realistic and quantitative understanding of motion impact on TomoTherapy SBRT treatment of lung and prostate cancer patients. Methods: A 4D dose engine utilizing GPUs and including motion during treatment was developed for the efficient simulation of TomoTherapy delivered dosimetry. Two clinical CyberKnife lung cases with respiratory motion tracking and two prostate cases with a slower non-periodical organ motion treated by LINAC plus Calypso tracking were used in the study. For each disease site, one selected case has an average motion (6mm); the other has a large motion (10mm for lung and 15mm for prostate). SBRT of lung and prostate cases were re-planned on TomoTherapy with 12 Gyx4 fractions and 7Gyx5 fractions, respectively, all with 95% PTV coverage. Each case was planned with 4 jaw settings: 1) conventional 1cm static, 2) 2.5cm static, 3) 2.5cm dynamic, and 4) 5cm dynamic. The intrafractional rigid motion of the target was applied in the dose calculation of individual fractions of each plan and total dose was accumulated from multiple fractions. Results: For 1cm static jaw plans with motions applied, PTV coverage is related to motion type and amplitude. For SBRT patients with average motion (6mm), the PTV coverage remains > 95% for lung case and 74% for prostate case. For cases with large motion, PTV coverage drops to 61% for lung SBRT and 49% for prostate SBRT. Plans with other jaws improve uniformity of moving target, but still suffer from poor PTV coverage (< 70%). Conclusion: TomoTherapy lung SBRT is less motion-impacted when average amplitude of respiratory-induced intrafractional motion is present (6mm). When motion is large and/or non-periodic (prostate), all studied plans lead to significantly decreased target coverage in actual delivered dosimetry.

TU-E-BRA-09: Evaluation of a Patient-Specific Respiratory Motion Model in Thoracic and Abdominal Phantom and Patient CT Images.

We have previously described a model of patient-specific respiratory motion to predict organ deformations without assuming repeatable breath cycles. The model is derived from deformable image registration (DIR) between respiration-correlated images (RCCT), followed by a principal component analysis (PCA) which relates the first two principal components of 3D deformations to the position and direction of motion of the diaphragm or implanted fiducials. This study examines model accuracy in phantom and patient images. We compare model and DIR accuracy using 3 types of image sets, each exhibiting different deformation patterns: (1) synthetic images in lung and abdomen from the 4D NURBS-based cardiac torso (NCAT) phantom with known deformations; (2) CT scans of physical deformable phantom with implanted markers in liver; and (3) liver structures in patient RCCT images using rigid registration in a small VOI as approximate ground truth. The model is calibrated by applying fast free-form DIR between a reference image set at end expiration and each of the other images at different motion states, defined by diaphragm or, in some patient cases, implanted fiducials as surrogate signals. Following PCA, the first two principal components are selected to yield a model-predicted displacement field for the given surrogate signal. Discrepancy between model prediction and ground truth (mean ± stand deviation) in 3D displacements is 3.3±2.0 mm in lung and 3.7±1.9 mm in abdomen in NCAT phantom, 3.8±2.7 mm in physical deformable phantom and 2.8±2.9 mm in patient data (N=7). Corresponding DIR discrepancies are 3.8±2.0 mm (NCAT lung), 3.7±1.8 mm (NCAT abdomen), 3.6±2.8 mm (physical phantom), and 2.0±2.2 mm (patient data). Motion model accuracy is found to be comparable to fast free-form in all three types of images, indicating that the assumption of two principal components is sufficient to describe the fast free-form DIR-derived deformations. NIH/NCI award R01 CA126993.

Evaluation of deformable image registration and a motion model in CT images with limited features

Deformable image registration (DIR) is increasingly used in radiotherapy applications and provides the basis for a previously described model of patient-specific respiratory motion. We examine the accuracy of a DIR algorithm and a motion model with respiration-correlated CT (RCCT) images of software phantom with known displacement fields, physical deformable abdominal phantom with implanted fiducials in the liver and small liver structures in patient images. The motion model is derived from a principal component analysis that relates volumetric deformations with the motion of the diaphragm or fiducials in the RCCT. Patient data analysis compares DIR with rigid registration as ground truth: the mean ± standard deviation 3D discrepancy of liver structure centroid positions is 2.0 ± 2.2 mm. DIR discrepancy in the software phantom is 3.8 ± 2.0 mm in lung and 3.7 ± 1.8 mm in abdomen; discrepancies near the chest wall are larger than indicated by image feature matching. Marker's 3D discrepancy in the physical phantom is 3.6 ± 2.8 mm. The results indicate that visible features in the images are important for guiding the DIR algorithm. Motion model accuracy is comparable to DIR, indicating that two principal components are sufficient to describe DIR-derived deformation in these datasets.

SU-GG-I-112: Evaluation of Deformable Registration in CT Images with Limited Feature Visibility

Purpose: Applications of deformable image registration (DIR) often assume deformations to be correct everywhere in the patient volume of interest, but prior studies of DIR accuracy have been limited mostly to high‐contrast features in lung. This study examines DIR accuracy with respiration‐correlated CT (RCCT) images of software and physical deformable phantoms and with patient images in abdomen. Methods and Materials: DIR uses a fast free‐form algorithm, which minimizes an energy function consisting of pixel grayscale similarity and smoothness terms. We evaluate its accuracy in 3 types of RCCT images: an anthropomorphic software phantom that models diaphragmatic contraction and chest expansion and whose known voxel displacements provide ground truth; a physical deformable abdominal phantom with implanted radiopaque markers; and patient data in which the motion between end expiration (EE) and end inspiration (EI) images of small low‐contrast features in or near the liver are compared to rigid registration as an approximate ground truth. Results: The mean 3D vector EE‐to‐EI discrepancy between DIR and ground truth displacement in software phantom is 4.5 mm in lung and 5.0 mm in abdomen. This is larger than that observed by comparing visible features in images alone. Mean 3D vector discrepancy is 6.1mm in physical phantom. In both phantoms, larger discrepancy appears to correlate with regions that lack visible features. In patient images, visible features in liver show good agreement between DIR prediction and ground truth, with mean 3D vector EE‐to‐EI discrepancy of 2.0 mm. Conclusions: Visible internal features in CTimages are important for guiding deformable registration. Radiotherapy applications that assume DIR is accurate throughout the volume may underestimate errors in regions lacking visible features. Results in patient images show that reasonable results can be obtained for features in abdomen. Research supported by NIH/NCI grant R01CA126993.

A Comprehensive Assessment by Tumor Site of Patient Setup Using Daily MVCT Imaging From More Than 3,800 Helical Tomotherapy Treatments

To assess patient setup corrections based on daily megavoltage CT (MVCT) imaging for four anatomic treatment sites treated on tomotherapy. Translational and rotational setup corrections, based on registration of daily MVCT to planning CT images, were analyzed for 1,179 brain and head and neck (H&N), 1,414 lung, and 1,274 prostate treatment fractions. Frequencies of three-dimensional vector lengths, overall distributions of setup corrections, and patient-specific distributions of random and systematic setup errors were analyzed. Brain and H&N had lower magnitude positioning corrections and smaller variations in translational setup errors but were comparable in roll rotations. Three-dimensional vector translational shifts of larger magnitudes occurred more frequently for lung and prostate than for brain and H&N treatments, yet this was not observed for roll rotations. The global systematic error for prostate was 4.7 mm in the vertical direction, most likely due to couch sag caused by large couch extension distances. Variations in systematic errors and magnitudes of random translational errors ranged from 1.6 to 2.6 mm for brain and H&N and 3.2 to 7.2 mm for lung and prostate, whereas roll rotational errors ranged from 0.8 degrees to 1.2 degrees for brain and H&N and 0.5 degrees to 1.0 degrees for lung and prostate. Differences in setup were observed between brain, H&N, lung, and prostate treatments. Patient setup can be improved if daily imaging is performed. This analysis can assess the utilization of daily image guidance and allows for further investigation into improved anatomic site-specific and patient-specific treatments.

Effect of chloride and diamide on sheep kidney, lung and serum angiotensin converting enzyme

The effect of chloride and diamide on angiotensin converting enzyme (ACE) activity from sheep kidney, lung and serum was investigated by using Hip-His-Leu as substrate. Optimum chloride concentrations were 400-1000 mM for kidney, 700 mM for lung and 1000 mM for serum. Optimum chloride concentration increased ACE activity of serum and lung 1.70 folds and 2.73 folds respectively of the activity at physiological chloride concentrations, suggesting that the effect of salt on blood pressure may be due to the chloride sensitivity of ACE. The difference in effect of chloride on lung, kidney and serum ACE suggest that each tissue ACE has unique three dimentional structure. Increased pulmonary and serum ACE activity on pretreatment with diamide indicates that tissue oxidation may alter blood pressure.

TU‐EE‐A3‐05: Assessment of Treatment Site‐Specific Setup Accuracy and Reproducibility in Patient Positioning Using Daily MVCT Imaging

Purpose: To assess treatment site‐specific corrections in patient positioning from TomoTherapy Hi‐ART® megavoltage images. Method and Materials: Initial positioning corrections, determined by fusion of daily pre‐treatment MVCT to planning CT images, were analyzed for different anatomical treatment sites.Over 600,1400, and 1200 fractions of head and neck (H&amp;N) and brain, lung, and prostate tomotherapy treatments, respectively, were assessed. Translational and rotational, per‐fraction setup corrections were retrospectively compiled from individual patient archive files. Setup corrections were compared amongst anatomical treatment sites. Setup reproducibility was assessed by analyzing standard deviations and histograms of setup corrections. Setup accuracy was also assessed by analyzing 3D vector lengths and magnitudes of corrections. Results: Large variations in setup corrections were seen in all three disease sites. H&amp;N treatments had a significantly smaller (p&lt;0.001) vector length standard deviation of 2.54 mm compared with 6.99 mm and 6.46 mm for lung and prostate treatments, respectively, but had no significantly different standard deviation in roll rotations. The frequency of translations of vector lengths ⩾ 10 mm were 48.9% and 48.1% of all lung and prostate treatments, respectively, whereas corrections of that magnitude occurred in only 1.56% of H&amp;N treatments. Frequencies of roll rotations were more comparable among the three disease sites. Conclusions: Analysis of patient positioning corrections indicates large variations between patients and treatments, suggesting a role for imaging every patient per‐fraction to ensure the most accurate reproducibility. H&amp;N treatments had a higher setup reproducibility and accuracy in the lateral, longitudinal, and vertical directions. Even so, they were not significantly different rotationally than prostate and lung treatments, suggesting a role for daily imaging in all three treatment sites. In quantifying site‐specific positioning reproducibility and accuracy, this work may be useful for assessing new treatment planning margins for image‐guided procedures or for developing adaptive radiotherapy techniques.

Differences in Ablation Size in Porcine Kidney, Liver, and Lung After Cryoablation Using the Same Ablation Protocol

The purpose of our study was to assess the variation in size of acute necrosis and the variation in thermal map measured during cryoablation in multiple organs using the same ablation protocol for each organ. Eight female pigs underwent one cryoablation per organ of kidney, lung, and liver performed with open surgery with a 2.4-mm cryoprobe. A 12- and 8-minute double-freeze cycle was used. Intratissue temperatures were monitored using 16-gauge thermometers spaced at 5.0-mm increments from the cryoprobe. The comparison of results among tissues was performed using the multiple analysis of variance. The -20 degrees C thermal diameter was correlated with tissue damage. The kidneys, lungs, and liver were removed and examined histologically for a pathologic complete coagulative necrosis zone. A single 2.4-mm cryoprobe had a mean ice ball diameter in kidney, lung, and liver of 38.5 +/- 4.7, 35.5 +/- 3.6, and 32.5 +/- 2.7 mm, respectively. A mean -20 degrees C thermal diameter was achieved at 24.07 +/- 1.38 mm in kidney, 12.76 +/- 3.0 mm in lung, and 8.8 +/- 3.7 mm in liver by means of regression analysis. The acute pathologic complete coagulative necrosis zone size was 21.0 +/- 1.56 mm (kidney), 11.6 +/- 1.48 mm (lung), and 8.0 +/- 1.20 mm (liver). The inherent characteristics of different organs manifest different ablation zone sizes during cryoablation despite the same ablation protocol being used. This information should be factored into planning for ablation procedures.