Slice Interval Research Articles

Optimum CT reconstruction parameters for vascular and hepatocellular carcinoma models in a liver phantom with multi-level dynamic computed tomography with 64 detector rows: a basic study

We quantified to clarify the optimum factors for CT image reconstruction of an enhanced hepatocellular carcinoma (HCC) model in a liver phantom obtained by multi-level dynamic computed tomography (M-LDCT) with 64 detector rows. After M-LDCT scanning of a water phantom and an enhanced HCC model, we compared the standard deviation (SD, 1 ± SD), noise power spectrum (NPS) values, contrast-noise ratios (CNR), and the M-LDCT image among the reconstruction parameters, including the convolution kernel (FC11, FC13, and FC15), post-processing quantum filters (2D-Q00, 2D-Q01, and 2D-Q02) and slice thicknesses/slice intervals. The SD and NPS values were lowest with FC11 and 2D-Q02. The CNR values were highest with 2D-Q02. The M-LDCT image quality was highest with FC11 and 2D-Q02, and with slice thicknesses/slice intervals of 0.5 mm/0.5 mm and 0.5 mm/0.25 mm. The optimum factors were the FC11 convolution kernel, 2D-Q02 quantum filter, and 0.5 mm slice thickness/0.5 mm slice interval or less.

Surgical Measurement of the Sphenoid Sinus on Sagittal Reformatted CT in the Turkish Population.

The objectives of this study were to determine sinus measurements specific for the Turkish population using CT sagittal thin-slice reconstruction images and to clarify the three-dimensional anatomical features of the sphenoid sinus, along with its surrounding structures, that are relevant to performing an endoscopic sphenoidotomy. Images of 300 patients (165 female, 135 male) were studied. The research was conducted on the axial plane with a 1 mm slice thickness and a 0.6 mm slice interval, and sagittal reconstruction was performed with a 0.4 mm slice interval. Measurements of the sinus were obtained, and the presence of Onodi cells was researched. Line 1 was found to be significantly shorter in the Turkish patients of this study compared to studies of other populations. Lines 4 and 6 were found to be longer on the left side (Line 4 right: 18.8±3.6 mm, left: 19.3±3.4 mm, p=0.027; Line 6 right: 24.1±6.8 mm, left: 24.3±6.8 mm, p=0.008). Lines 2, 3, 4 and 6 were longer in men than in women (p<0.05). In the Turkish population, Line 1 is shorter, so the risk of skull base perforation is greater. Lines 4 and 6 are longer on the left side; thus, choosing the left ostium in sinus dilation is safer. Because of sex differences regarding Lines 2, 3, 4 and 6, sex should be considered in sphenoid sinus procedures.

Reference Scanの位置における画質の検討

In magnetic resonance imaging (MRI), we can use sensitivity encoding (SENSE) as a parallel imaging reconstruct from aliasing based on the sensitivity map of each coil element by reference scan. We researched SENSE reconstruction depending on the position of the reference scan. 1.5 T MRI (Achiva, Philips), 32-channel SENSE cardiac coil and rectangular solid phantom (nickel chloride) were used. Seven slices (A to G: from head to foot) were set at the phantom, slice thickness was 1 cm, and each slice interval was 5 cm. When T2 weighted axial images (TR: 3000 ms, TE: 120 ms) were taken, the center of the reference scan (C-Ref) was changed A to G, SENSE factor was changed 1 to 5, and number of signals averaged (NSA) was changed 1 to 3 with fold over suppression. Signal-to-noise ratio (SNR) and coefficient of variation (CV) from 9 regions of interest (ROI) of axial images were calculated. The SNR of slices A and G were lower than the other slices. %CV of slices F with C-Ref D was 69.4% lower than C-Ref A. %CV of slices D to F were higher than the other slices when C-Ref was A. %CV had no relation with SNR. Therefore, a 30 cm area around the center of reference can obtain best SENSE reconstruction.

Accuracy of lung nodule density on HRCT: analysis by PSF‐based image simulation

A computed tomography (CT) image simulation technique based on the point spread function (PSF) was applied to analyze the accuracy of CT‐based clinical evaluations of lung nodule density. The PSF of the CT system was measured and used to perform the lung nodule image simulation. Then, the simulated image was resampled at intervals equal to the pixel size and the slice interval found in clinical high‐resolution CT (HRCT) images. On those images, the nodule density was measured by placing a region of interest (ROI) commonly used for routine clinical practice, and comparing the measured value with the true value (a known density of object function used in the image simulation). It was quantitatively determined that the measured nodule density depended on the nodule diameter and the image reconstruction parameters (kernel and slice thickness). In addition, the measured density fluctuated, depending on the offset between the nodule center and the image voxel center. This fluctuation was reduced by decreasing the slice interval (i.e., with the use of overlapping reconstruction), leading to a stable density evaluation. Our proposed method of PSF‐based image simulation accompanied with resampling enables a quantitative analysis of the accuracy of CT‐based evaluations of lung nodule density. These results could potentially reveal clinical misreadings in diagnosis, and lead to more accurate and precise density evaluations. They would also be of value for determining the optimum scan and reconstruction parameters, such as image reconstruction kernels and slice thicknesses/intervals.PACS numbers: 87.57.‐s, 87.57.cf, 87.57.Q‐

Double reading for gross tumor volume assessment in radiotherapy planning

Background/Objective: The precise definition of the gross tumor volume (GTV) that takes into account intra- and interobserver variability is necessary for high-precision radiotherapy (RT) techniques. The purpose of this study was to demonstrate the practical GTV assessment by a “double reading” approach. Methods: Pretreatment magnetic resonance (MR) imaging, including the post-contrast 3D magnetization-prepared rapid-gradient echo (MP-RAGE) sequence (section thickness 1.0 mm) was performed on a 3T superconducting imager in 50 patients with glioblastoma. MR images were transferred to a RT planning system (RTPS) that provides many opportunities for GTV contouring, e.g., at diagnosis, surgical navigation, and RT deliberations. Independent 2 observers preliminarily contoured the GTV on MR images. After planning-CT scanning, CT images with a 1.0 mm slice interval were transferred to the RTPS, registered with the diagnostic images, and then the preliminarily-contoured strictures were copied onto the CT images and used for GTV assessment. The practical GTV on the planning CT was determined by integrating the interpretations and adding information on postoperative changes. The interobserver variability in GTV contouring was assessed by Bland-Altman analysis and the concordance index. Results: There was substantial interobserver variability in GTV contouring (95% limits of agreement: -29.4%, 16.8%). The mean interobserver concordance rate for the GTV was 82.1% (range 56.5-91.2%). The practical GTVs were significantly larger than the preliminarily-contoured GTVs by both observers ( p < 0.01). Conclusions: Considering interobserver variability, “double reading” is necessary for practical GTV assessment. This approach for volume assessment may facilitate the standardization of treatments, not only of RT but also of surgery and chemotherapy.

Tomographic ultrasound imaging of the pelvic floor in nulliparous pregnant women: limits of normality

To define normal appearance of the puborectalis muscle on tomographic ultrasound imaging in pregnant nulliparous women, establishing limits of normality. This was a subanalysis of consecutive ultrasound volume datasets of 497 pregnant nulliparous women recruited in the context of two studies. All participants were carrying a singleton pregnancy at a mean gestation of 36.4 (range, 33-38) weeks. Tomographic ultrasound imaging was performed by subsequent post-processing on volumes obtained at maximal pelvic floor contraction at 2.5-mm slice intervals, from 5 mm below to 12.5 mm above the plane of minimal hiatal dimensions, producing eight slices per patient. Apparent abnormalities of the insertion of the puborectalis muscle were commonly seen in slices 1 and 2, but were uncommon in slice 3 (< 8%), very uncommon in slice 4 (1%) and rare elsewhere. They were not associated with bladder neck descent. Considering published minimal criteria for diagnosing an avulsion of the puborectalis muscle (slices 3 to 5 all abnormal), this diagnosis was made in three women. On reviewing those cases, one of which was rated abnormal on both sides, two were false positive as judged by the two senior authors. However, one was judged to be highly abnormal by both senior authors, with a full avulsion diagnosed on the left. Published minimal criteria for the diagnosis of avulsion of the puborectalis muscle by tomographic pelvic floor ultrasound imaging are highly unlikely to result in a false-positive diagnosis and appear to be sufficiently robust for clinical practice.

Investigating the relationship between virtual cystoscopy image quality and CT slice thickness

To investigate the effect of reconstruction slice thickness on image quality at CT virtual cystoscopy (VC). Pelvic CT examinations in bladder cancer patients were reconstructed at different slice thicknesses (0.6-5 mm) and intervals, and resulting VC images assessed. Quality indicators were ridging, holes, floaters and dimpling artefacts, tumour definition, and an overall score, ranked 1 (best) to 7 (worst). CT number and standard deviation (SD) for bladder contents and bladder wall were recorded. The mean SD was used as a measure of noise, and the contrast-to-noise ratio (CNR) was calculated as the CT number difference between them divided by the average image noise. The mean CNR across the three levels was used for analysis. Each qualitative image quality measure was compared with CT number, noise and CNR measurements. Dimpling artefacts increased with thinner slice reconstruction and correlated with increased noise, often resulting in poor tumour definition. The best overall image quality score was seen for VC images reconstructed at 1.2 mm slice thickness, probably because of the competing effects of spatial resolution and CNR. A slice thickness reconstruction <1.2 mm does not provide for better image quality at VC owing to the presence of increased noise.

Assessing the effect of CT slice interval on unidimensional, bidimensional and volumetric measurements of solid tumours

Objectives: To study the magnitude of differences in tumour unidimensional (1D), bidimensional (2D) and volumetric (VOL) measurements determined from computed tomography (CT) images reconstructed at 5, 2.5 and 1.25 mm slice intervals. Materials and Methods: A total of 118 lesions in lung, liver and lymph nodes were selected from 30 patients enrolled in early phase clinical trials. Each CT scan was reconstructed at 5, 2.5 and 1.25 mm slice intervals during the image acquisition. Lesions were semi-automatically segmented on each interval image series and supervised by a radiologist. 1D, 2D and VOL were computed based on the final segmentation results. Average measurement differences across different slice intervals were obtained using linear mixed-effects analysis of variance models. Results: Lesion diameters ranged from 6.1 to 80.1 mm (median 18.4 mm). The largest difference was seen between 1.25 and 5 mm (mean difference of 7.6% for 1D [P < 0.0001], 13.1% for 2D [P < 0.0001], −5.7% for VOL [P = 0.0001]). Mean differences between 1.25 and 2.5 mm were all within ±3.5% (within ±6% confidence interval). For VOL, there was a larger average difference between measurements on different slice intervals for the smaller lesions (<10 mm) compared with the larger lesions. Conclusions: Different slice intervals may give different 1D, 2D and VOL measurements. In clinical practice, it would be prudent to use the same slice interval for consecutive measurements.

Simulation of Elbow Flexion with a Three-Dimensional Arm Model

We developed an arm model by first creating bone models (humerus, ulna, and radius) based on CT images of human arms; muscle spring models (brachialis, biceps brachii, and brachioradialis) based on magnetic resonance (MR) images; and ligament wire models (17 ligaments that connect bones) based on literature and MR images, and then integrating these models. MR images of a human arm with the elbow flexed at arbitrary angles were obtained. Furthermore, these image data and the simulation results were compared to determine the simulation accuracy. The arm model was also used to analyze the behavior of each bone at ligament rupture. Comparison of the simulation results with MR images of a human arm during elbow flexion revealed a deviation of up to 16.7 mm at the midpoint of the ulnar notch of the radius (distal portion). This could be explained by the following: (1) the slice interval (3 mm) used to obtain MR images of a human arm; (2) influence of the articular capsule; and (3) influence of ligaments around the wrist. When medial collateral ligament rupture and ligament rupture around the lateral collateral ligament were simulated with the model, both bones extroverted and introverted, respectively. The deviation of both bones during medial collateral ligament rupture was greater than that during ligament rupture around the lateral collateral ligament, indicating that the medial collateral ligament was a major contributor to elbow stability. The above results demonstrated that the arm model created in this study simulated human arm movement well.

SU‐E‐T‐40: Exploring the Reproducibility of Tumor Volumes Measured by Radiologist, Computer‐Aided Radiologist and Computer Alone

Purpose: The use of volumetric CT as an imaging metric to better assess cancer response to treatment requires knowledge of measurement reproducibility. This study was designed to explore the reproducibility of tumor volumes obtained by radiologist manual delineation (MAN), computer‐aided method (CAM) and computer alone (CA) using a same‐day repeat CT dataset of 32 non‐small cell lung cancer (NSCLC) patients. Methods: We used a publicly accessible repeat CT dataset aimed at studying cancer treatment response. Briefly, each patient was scanned twice within 15 minutes using the same imaging protocol and CT scanner (16‐ or 64‐row). Patients were repositioned before the second scan. Thin‐sectional images of 1.25mm slice interval were reconstructed using a shaper filter. Thirty‐two lesions (one per patient) were analyzed using the following three Methods: (1) MAN‐an experienced radiologist manually drew tumor contours on two repeat scans in a side‐by‐side mode, (2) CAM‐an operator applied a home‐grown algorithm to segment the tumors and the computer‐generated contours were reviewed/edited by the same radiologist, also in a side‐by‐side mode, and (3) CA‐an operator applied a different, also homegrown, algorithm to delineate tumor contours (no edit). Bland‐Altman plots were constructed to assess the agreement between volumes measured by each method on the two repeat scans. Volume difference between MAN and CA on each patientˈs first scan was analyzed using a paired t‐test. Results: The 95% limits of agreements for the tumor volumes made by MAN, CAM and CA on two repeat scans were (−19.9%, 19.6%), (−12.1%, 13.4%) and (−11.8%, 16.0%), respectively. The difference between tumor volumes measured by MAN and CA was not statistically significant (p=0.497). Conclusions: MAN is the least reproducible method for measuring tumor volumes compared to CAM and CA. The recommended way to obtain tumor volumes is to use a computer algorithm to segment tumors followed by radiologistˈs supervision.This work is supported in part by R01CA125143 from National Cancer Institute

Between-slice intervals in quantification of adipose tissue and muscle in children

Magnetic Resonance Imaging (MRI) is increasingly being used in children to quantify adipose tissue (AT) and skeletal muscle (SM) in vivo. It is unclear whether the every 5 cm whole body MRI protocol used in adults is appropriate when applied in children. Whole body MRI continuous 1 cm thick slices were acquired in 73, aged 5-17-year-old healthy children. Images were segmented into subcutaneous (SAT), visceral (VAT), intermuscular AT (IMAT), and SM. The percentage difference between volumes measured by the continuous protocol and volumes estimated with protocols of different between-slice intervals (i.e., interval = 2, 3, 4 and 5 cm) was larger with an increase in interval size, depot size, weight and body mass index percentile. For group comparisons, studies will require less than 5.4% more subjects if an every 5 cm protocol is used for equivalent power as the every 1 cm protocol. For individual subject comparisons, interval protocols can be used to reliably distinguish between subjects who differ in SM or SAT volume by 0.14 to 0.64 L (i.e., 1 to 5% of SM or SAT volume) or more, or in VAT or IMAT volume by 0.06 to 0.21 L (i.e., 10 to 30% of VAT or IMAT volume) or more. The every 5 cm image acquisition protocol can be considered as accurate as the contiguous protocol for group comparisons in children, as well as for comparison of SM and SAT among individual children. However, a smaller slice interval protocol would be more accurate for comparison of VAT or IMAT among individual children.

Patient Size and Radiation Exposure in Thoracic, Pelvic, and Abdominal CT Examinations Performed With Automatic Exposure Control

The purpose of this study was to investigate the effect of patient size on the amount of radiation used to perform CT examinations of the chest, abdomen, and pelvis with automatic exposure control and on the corresponding patient doses. Ninety-one patients underwent CT of the chest, abdomen, and pelvis with a 64-MDCT scanner with automatic exposure control in the x, y, and z planes (noise index, 11.5; tube rotation speed, 1 second; maximal x-ray tube capacity, 800 mA; slice thickness, 5 mm; slice interval, 5 mm; table speed, 40 mm/rotation; pitch, 1; tube voltage, 120 kVp). Volume CT dose index was obtained from the scanner console at the completion of each examination. The volume CT dose index and a dosimetry calculator were used to determine the organ dose in a 70-kg patient. Patient organ doses were obtained by correction of the calculator organ doses by factors that accounted for size variations in the lung and abdomen among patients and the corresponding regions in the phantom. The average volume CT dose index for a 60-kg patient was approximately 11 mGy, which increased to approximately 22 mGy for an 80-kg patient and to approximately 33 mGy for a 100-kg patient. The corresponding average liver doses for 60-kg patients was approximately 16 mGy, which increased to approximately 25 mGy for 80-kg patients and to approximately 34 mGy for 100-kg patients. For this patient cohort, the median doses to the colon, stomach, and liver were approximately 25 mGy; to the bladder, 31 mGy; and to the red bone marrow, 16 mGy. The 90th percentile organ doses were generally three to four times that of the corresponding 10th percentile organ doses. For body CT examinations performed with automatic exposure control, the radiation used to perform examinations of 100-kg patients is approximately three times that for a 60-kg patient and results in organ doses that are generally twice as high as those in a 60-kg patient.

Characterization of masses in digital breast tomosynthesis: Comparison of machine learning in projection views and reconstructed slices

In digital breast tomosynthesis (DBT), quasi-three-dimensional (3D) structural information is reconstructed from a small number of 2D projection view (PV) mammograms acquired over a limited angular range. The authors developed preliminary computer-aided diagnosis (CADx) methods for classification of malignant and benign masses and compared the effectiveness of analyzing lesion characteristics in the reconstructed DBT slices and in the PVs. A data set of MLO view DBT of 99 patients containing 107 masses (56 malignant and 51 benign) was collected at the Massachusetts General Hospital with IRB approval. The DBTs were obtained with a GE prototype system which acquired 11 PVs over a 50 degree arc. The authors reconstructed the DBTs at 1 mm slice interval using a simultaneous algebraic reconstruction technique. The region of interest (ROI) containing the mass was marked by a radiologist in the DBT volume and the corresponding ROIs on the PVs were derived based on the imaging geometry. The subsequent processes were fully automated. For classification of masses using the DBT-slice approach, the mass on each slice was segmented by an active contour model initialized with adaptive k-means clustering. A spiculation likelihood map was generated by analysis of the gradient directions around the mass margin and spiculation features were extracted from the map. The rubber band straightening transform (RBST) was applied to a band of pixels around the segmented mass boundary. The RBST image was enhanced by Sobel filtering in the horizontal and vertical directions, from which run-length statistics texture features were extracted. Morphological features including those from the normalized radial length were designed to describe the mass shape. A feature space composed of the spiculation features, texture features, and morphological features extracted from the central slice alone and seven feature spaces obtained by averaging the corresponding features from three to 19 slices centered at the central slice were compared. For classification of masses using the PV approach, a feature extraction process similar to that described above for the DBT approach was performed on the ROIs from the individual PVs. Six feature spaces obtained from the central PV alone and by averaging the corresponding features from three to 11 PVs were formed. In each feature space for either the DBT-slice or the PV approach, a linear discriminant analysis classifier with stepwise feature selection was trained and tested using a two-loop leave-one-case-out resampling procedure. Simplex optimization was used to guide feature selection automatically within the training set in each leave-one-case-out cycle. The performance of the classifiers was evaluated by the area (Az) under the receiver operating characteristic curve. The test Az values from the DBT-slice approach ranged from 0.87 +/- 0.03 to 0.93 +/- 0.02, while those from the PV approach ranged from 0.78 +/- 0.04 to 0.84 +/- 0.04. The highest test Az of 0.93 +/- 0.02 from the nine-DBT-slice feature space was significantly (p = 0.006) better than the highest test Az of 0.84 +/- 0.04 from the nine-PV feature space. The features of breast lesions extracted from the DBT slices consistently provided higher classification accuracy than those extracted from the PV images.

Normal bronchi on high resolution CT

The delineation of normal bronchi was evaluated by high resolution CT. Under the usual conditions for lung survey, with window width of 1500, window level -650, and slice thickness 10 mm, using high spatial frequency algorithm, the subsegmental bronchi were delineated in 77% of total branches. Sub-subsegmental bronchi were delineated in 8% of branches. Under thin slice high resolution CT, with slice thickness of 1.5 mm and slice interval 10 mm, subsegmental bronchi were delineated in 89% of branches, and sub-subsegmental bronchi were delineated in 35% of branches. In two of the cases in which almost the whole lungs were studied on continuous slice images with thin slice high resolution CT, sub-sub-subsegmental bronchi could be easily delineated, except in for the lingular segment. High resolution CT is very useful for the interpretation of normal pulmonary structures and for diagnosis of bronchial lesions.

Multistep Level Sections to Detect Occult Fallopian Tube Carcinoma in Risk-reducing Salpingo-oophorectomies From Women With BRCA Mutations

Risk-reducing salpingo-oophorectomy (RRSO) significantly lowers the incidence of ovarian, tubal, peritoneal, and breast cancer in women who carry BRCA1 or BRCA2 germline mutations. A minority of RRSO specimens from these women will contain occult early-stage carcinoma. Most occult cancer is localized in the fallopian tube fimbriae and is as small as 1 mm in size. Pathologic detection is dependent on thoroughness of tissue examination. Recommended protocols to maximize tumor detection emphasize the role of thinly slicing the tubes and ovaries and embedding the entire specimen for microscopic examination. Additional multistep level sections of tubal fimbriae tissue blocks could theoretically increase detection of occult tubal carcinoma but the value of level sections has not been formally evaluated. This study tests the diagnostic utility of multistep level sections in RRSO specimens from 102 women with BRCA germline mutations. The original diagnoses were based on a single section from each block of thinly sliced (2 to 3 mm intervals) tissues of the entire RRSO specimen. Three multistep level sections were retrospectively obtained from each block containing tubal fimbriae. Clinically occult carcinoma ranging in size from 1 to 13 mm was initially detected in 11 of 102 women (5 in tubal fimbriae only, 1 in tubal isthmus only, 2 in fimbriae and ovary, and 3 in ovary only). Diagnoses in the original fimbrial slides and their level sections were concordant in all cases. All tubal cancers were detected in both the original sections and in the multistep level sections. None of the tubal carcinomas that were noninvasive on the original slides showed invasive growth on additional level sections. No tubal carcinoma was identified in the level sections of any case originally classified as benign. Clinical follow-up among women with benign RRSO findings revealed that 2 women subsequently developed peritoneal carcinomatosis at 22 and 62 months postoperatively. Retrospective exhaustive multistep level sectioning of all remaining tubal and ovarian blocks from both these women confirmed the original benign diagnosis in 1 woman but in the other woman, the deepest levels of 1 ovarian block revealed a single 1-mm nodule of cancer at the base of an ovarian surface epithelial invagination. This specimen was one of the first RRSO cases in our experience and on review of the original report, this ovary was not dissected into multiple slices along its short axis but was only bivalved along its long axis. We propose that there does not seem to be any diagnostic value in automatically performing multistep deeper level sections of RRSO specimens if the tissue is sectioned appropriately and if the specimen is sliced at intervals that are no more than 3 mm thick. Guidelines for evaluation of RRSO specimens should emphasize the use of an optimal dissection protocol and the importance of thin tissue slice intervals.

Assessment of Prognosis of Patients With Idiopathic Pulmonary Fibrosis by Computer-aided Analysis of CT Images

To present the Gaussian Histogram Normalized Correlation (GHNC) system, to quantify the extent of disease on computed tomography (CT) images of idiopathic pulmonary fibrosis (IPF), and to assess its utility by comparing the radiologist' scoring and prognosis. GHNC was used to analyze baseline thin-section CT images (30-60images per patients) of 40 patients with IPF. It classified the CT lung field into normal (N), ground-glass opacities (G), consolidation (C), emphysema (E) and fibrosis (F) patterns [the latter was also subdivided into reticular (F1) and honeycomb (F2) patterns], then the relative lung volume and relative each pattern volume (area multiplied by slice thickness and interval and divided by predicted total lung capacity) were estimated. The radiologists estimated the area of these patterns on 4 slices per patient; the average was regarded as total extent of each pattern. We compared the estimates determined by radiologists and GHNC with pulmonary function tests, and used Cox regression analysis to examine the relationships between the volumes and patient survival. The area of each pattern measured by GHNC correlated significantly with that estimated by the radiologist on 160 images (P<0.001, each). The volumes of N-pattern and F-patterns are measured by GHNC correlated with carbon monoxide diffusing capacity.During the follow-up (mean 49 mo), 24 patients died. Relative lung volume, N-pattern, F-pattern and F2-pattern correlated with survival in univariate analysis. Multivariate analysis identified F2-pattern volume by GHNC (P=0.034) as a significant predictor of survival. The GHNC provides automatic measurement of volume of fibrosis. The F2-pattern on CT can predict prognosis of patients with IPF.

SU-FF-T-254: Factors Study for MapCheck IMRT QA Evaluation

Purpose: To examine the factors that function in MapCheck IMRT QA result. Method and Materials:IMRT plan was calculated with Eclipse planning system and projected into a phantom at gantry angle zero position to create a verification plan. MapCheck QA result variation was evaluated with (1) a linac output fluctuation by calibrated MapCheck at previous 1.007 and current 0.995 linac outputs, (2) an effect of projected phantom slice interval at 0.5cm and 0.3cm, and (3) the number of point passing the criteria with MapCheck comparision models (AD/DTA, RD/DTA, AD/γ and RD/γ). A normalization point was selected as the value difference ⩽2% and fixed the point was used for all comparison models. All comparisons were done at 3% and 3mm criteria with a threshold 10. Results: MapCheck result varied with linac output showed an average improvement of 1.94% from 4 plans and 2.00% from 20 individual fields at CAX reading, and no signification improvement with the comparison models through MapCheck re‐calibration. Phantom slice interval difference related with a QA result showed no signification change in CAX reading, and the mean improvement from five field measurements was 0.76%, 1.30%, 5.80% and 4.10% in four comparison models from 0.5cm to 0.3cm interval. There was 100% point passing observed with a normalization point off 3.44%, and 91.8% point passing observed from same testing when the normalization point difference reduced to 0.32%. An average point passing the criteria from four comparison models was 91.81%, 95.71%, 85.77% and 95.30% from 50 fields, and 95.59%, 98.49%, 90.76% and 98.03% from 16 plans. Conclusions: A phantom slice interval 0.3cm is suggested for IMRT verification plan projection. MapCheck re‐calibration should be considered when a linac output changes. All comparison model results vary with normalization point selection. RD model is more sensitivity to the normalization point selection than AD model.

Tomographic ultrasound imaging of the pelvic floor: which levels matter most?

Tomographic ultrasound imaging has greatly simplified pelvic floor assessment. Abnormalities of the insertion of the levator ani can be documented in a single frame. In this study we aimed to determine which levels of the levator hiatus are associated with alterations in ultrasound parameters of pelvic organ support. This was a subanalysis of a study conducted in 296 women seen before and after their first delivery. We analyzed postpartum changes in bladder neck descent and hiatal area as indicators of altered pelvic organ support. Tomographic ultrasound examination was performed on volumes obtained at maximal pelvic floor muscle contraction, at 2.5-mm slice intervals, from 5 mm below to 12.5 mm above the plane of minimal hiatal dimensions. Two hundred and eight recruits (70%) returned for a postnatal appointment. Of these, 130 had delivered vaginally and 26 (20%) were diagnosed with an avulsion injury. An abnormality in slices 3-8 was associated with increased bladder neck descent postpartum (P = 0.038 to P = 0.001) and increased hiatal area on Valsalva maneuver (P = 0.029 to P < 0.001). This was not the case for the two most distal slices. We found no association between levator ani defects observed on tomographic ultrasound imaging below the plane of minimal hiatal dimensions and indices of increased hiatal distension or bladder neck descent on Valsalva maneuver. This implies that defects observed below this plane are either irrelevant for pelvic organ support or artifactual.

Precision of cortical bone reconstruction based on 3D CT scans

The precision and accuracy of human cortical bone reconstruction using 3D CT scans was evaluated using machined bone segments. Both linear and angular errors were measured. Cadaver adult femoral and tibial cortical bone segments were obtained and machined in six orthogonal planes with a precision milling machine. CT scans were then obtained and the bone segments were reconstructed as digital replicas. Dimensional and angular measurements errors were evaluated for the machined bone segments and the results were compared with known dimensions based on milling machine settings to calculate errors due to scanning and model reconstruction. The model dimensional error in the coronal, sagittal and axial directions had a mean of 0.21 mm, with standard a deviation of 0.12 mm and a maximum error of 0.47 mm. The mean percent error was 0.74% and the maximum percent error was 1.9%. The angular error of models in the coronal, sagittal and axial directions was calculated, yielding a mean of 0.47° with a standard deviation of 0.37° and a maximum of 1.33°. The error in the cross-sectional axial direction had a mean of 0.54 mm with a maximum error of 0.83 mm, depending on the slice interval. The main error source was of the image processing, which was about 70% of the total error. We found that machining cortical bone segments prior to CT scanning is an effective method for accuracy evaluation of CT-based bone reconstruction. This method can provide a reference for assessing the sensitivity, reliability and accuracy of CT-based applications in the study of movement, finite element modeling, and prosthesis construction.

SU-GG-T-230: Method to Validate the Dosimetric Accuracy of Motion Tracking in Cyberknife Using a CIRS Dynamic Phantom

Purpose: The dose distributions in Cyberknife planning are more conformal with steeper dose gradients than what has been available with gantry based linear accelerators. With the inception of the motion tracking algorithm, these steep dose gradients are delivered to a small moving lesion with submillimeter targeting accuracy. The CIRS dynamic phantom will be used to validate the dose accuracy of a moving target and compare to a static target. Method and Materials: The phantom was scanned with a 4 slice GE HiSpeed helical scanner at 1 mm slice intervals. The treatment regiment for each delivered plan was one fraction at 20 Gy to the 85% isodose line. The exposed gafchromic film was scanned and analyzed with ImageJ to acquire dose profiles in each plane. Results: The dose profiles showed dips that coincided with lower dose regions in the treatment plan. This was apparent in measurements with the phantom static as well as with the phantom in motion. Treatments delivered to the dynamic phantom yielded results within 5% of the prescribed dose as compared to static deliveries. Conclusion: The CIRS dynamic phantom provides a method to validate the dosimetric accuracy of Cyberknife when compensating for complex motion. This is a sound method to include in the quality assurance program. Because this can be a lengthy procedure, up to two hours, it may be more feasible to include in a quarterly or annual quality assurance program.