U.S. Diagnostic Reference Levels and Achievable Doses for 10 Pediatric CT Examinations.

Background Diagnostic reference levels (DRLs) and achievable doses (ADs) were developed for the 10 most commonly performed pediatric CT examinations in the United States using the American College of Radiology Dose Index Registry. Purpose To develop robust, current, national DRLs and ADs for the 10 most commonly performed pediatric CT examinations as a function of patient age and size. Materials and Methods Data on 10 pediatric (ie, patients aged 18 years and younger) CT examinations performed between 2016 and 2020 at 1625 facilities were analyzed. For head and neck examinations, dose indexes were analyzed based on patient age; for body examinations, dose indexes were analyzed for patient age and effective diameter. Data from 1 543 535 examinations provided medians for AD and 75th percentiles for DRLs for volume CT dose index (CTDIvol), dose-length product (DLP), and size-specific dose estimate (SSDE). Results Of all facilities analyzed, 66% of the facilities (1068 of 1625) were community hospitals, 16% (264 of 1625) were freestanding centers, 9.5% (154 of 1625) were academic facilities, and 3.5% (57 of 1625) were dedicated children's hospitals. Fifty-two percent of the patients (798 577 of 1 543 535) were boys, and 48% (744 958 of 1 543 535) were girls. The median age of patients was 14 years (boys, 13 years; girls, 15 years). The head was the most frequent anatomy examined with CT (876 655 of 1 543 535 examinations [57%]). For head without contrast material CT examinations, the age-based CTDIvol AD ranged from 19 to 46 mGy, and DRL ranged from 23 to 55 mGy, with both AD and DRL increasing with age. For body examinations, DRLs and ADs for size-based CTDIvol, SSDE, and DLP increased consistently with the patient's effective diameter. Conclusion Diagnostic reference levels and achievable doses as a function of patient age and effective diameter were developed for the 10 most commonly performed CT pediatric examinations using American College of Radiology Dose Index Registry data. These benchmarks can guide CT facilities in adjusting pediatric CT protocols and resultant doses for their patients. © RSNA, 2021 An earlier incorrect version appeared online. This article was corrected on October 29, 2021.

Contrast-enhanced Mammography: How Does It Work?

Contrast-enhanced mammography (CEM) is an imaging technique that uses iodinated contrast medium to improve visualization of breast lesions and assessment of tumor neovascularity. Through modifications in x-ray energy, high- and low-energy images of the breast are combined to highlight areas of contrast medium pooling. The use of contrast material introduces different workflows, artifacts, and risks related to the contrast medium dose. In addition, the need to acquire multiple images in each view introduces different workflows, artifacts, and risks associated with the radiation dose. Although CEM and conventional mammography share many underlying principles, it is important to understand how these two mammographic examinations differ and the mechanisms that facilitate image contrast at CEM. ©RSNA, 2021.

Tracheomegaly among Extremely Preterm Infants on Prolonged Mechanical Ventilation.

By using phantom radiographs, the accuracy of tracheal measurements was established. Preterm infants (≤29 weeks) were enrolled in short (<7 days) and prolonged ventilation (≥28 days) groups. Both groups had 3 weight categories, namely, <1000 g, 1000-1999 g, and >2000 g. Tracheal sizes were measured on serial chest radiographs (CXR). We noted tracheomegaly in association with prolonged ventilation at ≥1000 g.

Patients undergoing recurrent CT scans: assessing the magnitude.

OBJECTIVES: To assess percent of patients undergoing multiple CT exams that leads to cumulative effective dose (CED) of ≥ 100 mSv and determine their age distribution. METHODS: Data was retrieved retrospectively from established radiation dose monitoring systems by setting the threshold value of 100 mSv at four institutions covering 324 hospitals. The number of patients with CED ≥ 100 mSv only from recurrent CT exams during a feasible time period between 1 and 5 years was identified. Age and gender distribution of these patients were assessed to identify the magnitude of patients in the relatively lower age group of ≤ 50 years. RESULTS: Of the 2.5 million (2,504,585) patients who underwent 4.8 million (4,819,661) CT exams during the period of between 1 and 5 years, a total of 33,407 (1.33%) patients received a CED of ≥ 100 mSv with an overall median CED of 130.3 mSv and maximum of 1185 mSv. Although the vast majority (72-86%) of patients are > 50 years of age, nearly 20% (13.4 to 28%) are ≤ 50 years. The minimum time to accrue 100 mSv was a single day at all four institutions, an unreported finding to date. CONCLUSIONS: We are in an unprecedented era, where patients undergoing multiple CT exams and receiving CED ≥ 100 mSv are not uncommon. While underscoring the need for imaging appropriateness, the consideration of the number and percent of patients with high exposures and related clinical necessities creates an urgent need for the industry to develop CT scanners and protocols with sub-mSv radiation dose, a goal that has been lingering. KEY POINTS: • We are in an era where patients undergoing multiple CT exams during a short span of 1 to 5 years are not uncommon and a sizable fraction among them are below 50 years of age. • This leads to cumulative radiation dose to individual patients at which radiation effects are of real concern. • There is an urgent need for the industry to develop CT scanners with sub-mSv radiation dose, a goal that has been lingering.

Fetal Dosimetry at CT: A Primer.

CT scanning of a pregnant patient is often a source of distress for both patient and staff. Despite having expertise in image interpretation, a radiologist may not feel equipped to discuss the radiation-related safety issues during CT scanning of the fetus. In addition, patients are frequently concerned about the risk of adverse effects on the fetus from exposure to ionizing radiation. Recognizing the possibility of adverse effects from fetal exposure and the impossibility of direct in vivo measurement, medical physicists have developed several methods to estimate the amount of radiation reaching the fetus. A physician should know the potential biologic effects of fetal irradiation and at what radiation dose thresholds they occur. Physicians should also have an understanding of these methods and how the numbers they produce relate to potential fetal bioeffects. Furthermore, radiologists should have some understanding of how a qualified medical physicist calculates the fetal dose, how much they should trust those numbers, and the relevant variables that can affect the outcomes. Finally, the radiologist should know the magnitude of doses for CT scans commonly used in pregnant patients. Armed with this knowledge, a radiologist should be confident when discussing fetal dose and determining the best course of action for the pregnant patient. Online supplemental material is available for this article. ©RSNA, 2020.

Sample content of kinesthetic educational training: Reducing scattered X-ray exposures to interventional physician operators of fluoroscopy.

Content used by Medical Physicists for fluoroscopy safety training to staff is deliverable via several formats, that is, online content or a live audience slide presentations. Here, we share one example of a kinesthetic (live, hands-on simulation) educational program in use at our facility for some time (~10 years). In this example, the format and content specifically target methods of reducing physician operator exposures from scattered x rays. A kinesthetic format identifies and promotes the adoption of exposure-reducing behaviors. Key kinesthetic elements of this type of training include: physician hands-on measurements of radiation levels at locations specific to their standing positions (e.g., primary arterial access points) in the room using handheld exposure rate meters, measurement of exposure rate reduction to physicians provided by using personal protective equipment, that is, wearable aprons, hanging lead drapes, and pull-down shields. Physician choice of procedure-specific tableside selectable controls affecting exposure rate from optional fluoroscopy, Cine or digital subtraction angiography (DSA), along with comparative measured contribution to physician exposure is demonstrated. The inverse square exposure rate reduction to physicians when stepping back from the table during DSA is a key observation. Kinesthetic simulations in the rooms used by physicians have been found to provide the highest level of understanding giving rise to adoption of practices that are impactful for physicians. Specific training scripts are in place for physician sub-specialization in interventional radiology, cardiology, neurosurgery, vascular surgery, and gastroenterology. This training is used for new physician staff while classroom presentations (whose content mimics in room training) are used with staff who have had previously had in room training.

Dynamic contrast-enhanced CT for the assessment of tumour response in malignant pleural mesothelioma: a pilot study.

OBJECTIVES: The aim of this pilot study was to investigate the utility of haemodynamic parameters derived from dynamic contrast-enhanced computed tomography (DCE-CT) scans in the assessment of tumour response to treatment in malignant pleural mesothelioma (MPM) patients. METHODS: The patient cohort included nine patients undergoing chemotherapy and five patients on observation. Each patient underwent two DCE-CT scans separated by approximately 2 months. The DCE-CT parameters of tissue blood flow (BF) and tissue blood volume (BV) were obtained within the dynamically imaged tumour. Mean relative changes in tumour DCE-CT parameters between scans were compared between the on-treatment and on-observation cohorts. DCE-CT parameter changes were correlated with relative change in tumour bulk evaluated according to the modified RECIST protocol. RESULTS: Differing trends in relative change in BF and BV between scans were found between the two patient groups (p = 0.19 and p = 0.06 for BF and BV, respectively). No significant rank correlations were found when comparing relative changes in DCE-CT parameters with relative change in tumour bulk. CONCLUSIONS: Differing trends in the relative change of BF and BV between patients on treatment and on observation indicate the potential of DCE-CT for the assessment of pharmacodynamic endpoints with respect to treatment in MPM. A future study with a larger patient cohort and unified treatment regimens should be undertaken to confirm the results of this pilot study. KEY POINTS: • CT-derived haemodynamic parameters show differing trends between malignant pleural mesothelioma patients on treatment and patients off treatment • Changes in haemodynamic parameters do not correlate with changes in tumour bulk as measured according to the modified RECIST protocol • Differing trends across the two patient groups indicate the potential sensitivity of DCE-CT to assess pharmacodynamic endpoints in the treatment of MPM.

SPECT/CT image-based dosimetry for Yttrium-90 radionuclide therapy: Application to treatment response.

This work demonstrates the efficacy of voxel-based 90 Y microsphere dosimetry utilizing post-therapy SPECT/CT imaging and applies it to the prediction of treatment response for the management of patients with hepatocellular carcinoma (HCC). A 90 Y microsphere dosimetry navigator (RapidSphere) within a commercial platform (Velocity, Varian Medical Systems) was demonstrated for three microsphere cases that were imaged using optimized bremsstrahlung SPECT/CT. For each case, the 90 Y SPECT/CT was registered to follow-up diagnostic MR/CT using deformable image registration. The voxel-based dose distribution was computed using the local deposition method with known injected activity. The system allowed the visualization of the isodose distributions on any of the registered image datasets and the calculation of dose-volume histograms (DVHs). The dosimetric analysis illustrated high local doses that are characteristic of blood-flow directed brachytherapy. In the first case, the HCC mass demonstrated a complete response to treatment indicated by a necrotic region in follow-up MR imaging. This result was dosimetrically predicted since the gross tumor volume (GTV) was well covered by the prescription isodose volume (V150 Gy = 85%). The second case illustrated a partial response to treatment which was characterized by incomplete necrosis of an HCC mass and a remaining area of solid enhancement in follow-up MR imaging. This result was predicted by dosimetric analysis because the GTV demonstrated incomplete coverage by the prescription isodose volume (V470 Gy = 18%). The third case demonstrated extrahepatic activity. The dosimetry indicated that the prescription (125 Gy) isodose region extended outside of the liver into the duodenum (178 Gy maximum dose). This was predictive of toxicity as the patient later developed a duodenal ulcer. The ability to predict outcomes and complications using deformable image registration, calculated isodose distributions, and DVHs, points to the clinical utility of patient-specific dose calculations for 90 Y radioembolization treatment planning.

GammaKnife versus VMAT radiosurgery plan quality for many brain metastases.

The purpose of this work was to compare dose distributions between two radiosurgery modalities, single-isocenter volumetric modulated arc therapy (VMAT), and GammaKnife Perfexion (GK), in the treatment of a large number (≥7) of brain metastases. Twelve patients with 103 brain metastases were analyzed. The median number of targets per patient was 8 (range: 7-14). GK plans were compared to noncoplanar VMAT plans using both 6-MV flattening filter-free (FFF) and 10-MV FFF modes. Parameters analyzed included radiation therapy oncology group conformity index (CI), 12, 6, and 3 Gy isodose volumes (V12 Gy, V6 Gy, V3 Gy), mean and maximum hippocampal dose, and maximum skin dose. There were statistically significant differences in CI (2.5 ± 1.6 vs 1.6 ± 0.8 and 1.7 ± 0.9, P < 0.001, P < 0.001), V12 Gy (2.8 ± 6.1 cc vs 3.0 ± 5.2 cc and 3.1 ± 5.4 cc, P = 0.003, P < 0.001), and V3 Gy (323.0 ± 294.8 cc vs, 880.1 ± 369.1 cc and 937.9 ±  vs 361.9 cc, P = 0.005, P = 0.001) between GK versus both 6-MV FFF and 10-MV FFF. No significant differences existed for maximum hippocampal or skin doses. In conclusion, highly optimized VMAT produced improved conformity at the expense of a higher V12 Gy and V3 Gy volume when compared with highly optimized GK.

Bariatric CT Imaging: Challenges and Solutions.

The obesity epidemic in the adult and pediatric populations affects all aspects of health care, including diagnostic imaging. With the increasing prevalence of obese and morbidly obese patients, bariatric computed tomographic (CT) imaging is becoming common in day-to-day radiology practice, and a basic understanding of the unique problems that bariatric patients pose to the imaging community is crucial in any setting. Because larger patients may not fit into conventional scanners, having a CT scanner with an adequate table load limit, a large gantry aperture, a large scan field of view, and a high-power generator is a prerequisite for bariatric imaging. Iterative reconstruction methods, high tube current, and high tube voltage can reduce the image noise that is frequently seen in bariatric CT images. Truncation artifacts, cropping artifacts, and ring artifacts frequently complicate the interpretation of CT images of larger patients. If recognized, these artifacts can be easily reduced by using the proper CT equipment, scan acquisition parameters, and postprocessing options. Lastly, because of complex contrast material dynamics, contrast material-enhanced studies of bariatric patients require special attention. Understanding how the rate of injection, the scan timing, and the total mass of iodine affect vascular and parenchymal enhancement will help to optimize contrast-enhanced studies in the bariatric population. This article familiarizes the reader with the challenges that are frequently encountered at CT imaging of bariatric patients, beginning with equipment selection and ending with a review of the most commonly encountered obesity-related artifacts and the technical considerations in the acquisition of contrast-enhanced images. (©)RSNA, 2016.

Image quality and dose differences caused by vendor-specific image processing of neonatal radiographs.

BACKGROUND: Image processing plays an important role in optimizing image quality and radiation dose in projection radiography. Unfortunately commercial algorithms are black boxes that are often left at or near vendor default settings rather than being optimized. OBJECTIVE: We hypothesize that different commercial image-processing systems, when left at or near default settings, create significant differences in image quality. We further hypothesize that image-quality differences can be exploited to produce images of equivalent quality but lower radiation dose. MATERIALS AND METHODS: We used a portable radiography system to acquire images on a neonatal chest phantom and recorded the entrance surface air kerma (ESAK). We applied two image-processing systems (Optima XR220amx, by GE Healthcare, Waukesha, WI; and MUSICA(2) by Agfa HealthCare, Mortsel, Belgium) to the images. Seven observers (attending pediatric radiologists and radiology residents) independently assessed image quality using two methods: rating and matching. Image-quality ratings were independently assessed by each observer on a 10-point scale. Matching consisted of each observer matching GE-processed images and Agfa-processed images with equivalent image quality. A total of 210 rating tasks and 42 matching tasks were performed and effective dose was estimated. RESULTS: Median Agfa-processed image-quality ratings were higher than GE-processed ratings. Non-diagnostic ratings were seen over a wider range of doses for GE-processed images than for Agfa-processed images. During matching tasks, observers matched image quality between GE-processed images and Agfa-processed images acquired at a lower effective dose (11 ± 9 µSv; P < 0.0001). CONCLUSION: Image-processing methods significantly impact perceived image quality. These image-quality differences can be exploited to alter protocols and produce images of equivalent image quality but lower doses. Those purchasing projection radiography systems or third-party image-processing software should be aware that image processing can significantly impact image quality when settings are left near default values.

ACR testing of a dedicated head SPECT unit.

Physics testing necessary for program accreditation is rigorously defined by the ACR. This testing is easily applied to most conventional SPECT systems based on gamma camera technology. The inSPira HD is a dedicated head SPECT system based on a rotating dual clamshell design that acquires data in a dual-spiral geometry. The unique geometry and configuration force alterations of the standard ACR physics testing protocol. Various tests, such as intrinsic planar uniformity and/or resolution, do not apply. The Data Spectrum Deluxe Phantom used for conventional SPECT testing cannot fit in the inSPira HD scanner bore, making (currently) unapproved use of the Small Deluxe SPECT Phantom necessary. Matrix size, collimator type, scanning time, reconstruction method, and attenuation correction were all varied from the typically prescribed ACR instructions. Visible spheres, sphere contrast, visible rod groups, uniformity, and root mean square (RMS) noise were measured. The acquired SPECT images surpassed the minimum ACR requirements for both spatial resolution (9.5 mm spheres resolved) and contrast (6.4 mm rod groups resolved). Sphere contrast was generally high. Integral uniformity was 4% and RMS noise was 1.7%. Noise appeared more correlated than in images from a conventional SPECT scanner. Attenuation-corrected images produced from direct CT scanning of the phantom and a manufacturer supplied model of the phantom demonstrated negligible differences.

Quantifying misdiagnosis rates from cross-calibration biases and precision errors in dual-energy X-ray absorptiometry of the femoral neck.

BACKGROUND: Dual-energy X-ray absorptiometry (DXA) is an exam that measures areal bone mineral density (aBMD) and is regularly used to diagnose and monitor osteoporosis. Except for exam quality issues such as operator error, the quantitative results of an exam are not modified by a radiologist or other physician. DXA cross-calibration errors can shift diagnoses, conceivably leading to alternate intervention decisions and patient outcomes. PURPOSE: After identifying and correcting a cross-calibration bias of 3.8% in our two DXA scanners' aBMD measurements, we investigated misdiagnosis rates for given cross-calibration errors in a single patient cohort to determine the impact on patient care and the value of cross-calibration quality control. METHODS: The studied cohort was 8012 patients of all ages and sexes with femoral neck exams that were scanned on a single DXA unit from October 1, 2018 to March 31, 2021. There were six subcohorts delineated by age and sex, three female groups and three male groups. Data reporting focused on the highest risk subcohort of 2840 females aged 65 or older. The DXA unit had no calibration changes during that time. Only one femoral neck-left or right-was randomly chosen for analysis. Patients with multiple qualifying exams within the time interval had one exam randomly chosen. The proof-of-principle simulation shifted the aBMD values within a range of ±10%, ±8%, ±6%, ±4%, ±3.5%, ±3%, ±2.5%, ±2%, ±1.5%, ±1%, ±0.5%, and 0 (no shift); the cross-calibration shifts were informed by published results and institutional experience. Measurement precision was modeled by randomly sampling a Gaussian distribution characterized by the worst acceptable least significant change (LSC) of 6.9%, with 100 000 samplings for each patient. T-scores were recalculated from the shifted aBMD values, followed by reassigned diagnoses from the World Health Organization's T-score-based scheme. RESULTS: The unshifted original subcohort of women aged 65 and older had 599 normal diagnoses (21.1% of the cohort), 1784 osteopenia diagnoses (62.8%), and 455 osteoporosis diagnoses (16.1%). Osteoporosis diagnosis rates were highly sensitive to aBMD shifts. At the extrema, a -10% aBMD shift led to +161% osteoporosis cases, and a +10% aBMD shift led to -64.5% osteoporosis cases. Within the more plausible ±4% aBMD error range, the osteoporosis diagnosis rate changed -10.5% per +1% aBMD shift as indicated by linear regression (R2  = 0.98). Except for the men aged 49 years and younger subcohort, the total cohort and five subcohorts had fit line slopes ranging between -9.7% and -12.1% with R2 ≥ 0.98. Cross-calibration bias had greater influence for diagnosis count rates compared to measurement precision, that is, LSC. CONCLUSIONS: These results quantify the degree of misdiagnosis that can occur in a clinically relevant cohort due to cross-calibration bias. In medical practices where patients may be scanned on more than one DXA unit, ensuring cross-calibration quality is a critical and high-value quality control task with direct impact on patient diagnosis and treatment course. The clinical impact and incidence of poor DXA quality control practices, and cross-calibration in particular, should be studied further.

Opportunistic screening for low bone density using abdominopelvic computed tomography scans.

BACKGROUND: While low bone density is a major burden on US health system, current osteoporosis screening guidelines by the US Preventive Services Task Force are limited to women aged ≥65 and all postmenopausal women with certain risk factors. Even within recommended screening groups, actual screening rates are low (<26%) and vary across socioeconomic groups. The proposed model can opportunistically screen patients using abdominal CT studies for low bone density who may otherwise go undiagnosed. PURPOSE: To develop an artificial intelligence (AI) model for opportunistic screening of low bone density using both contrast and non-contrast abdominopelvic computed tomography (CT) exams, for the purpose of referral to traditional bone health management, which typically begins with dual energy X-ray absorptiometry (DXA). METHODS: We collected 6083 contrast-enhanced CT imaging exams paired with DXA exams within ±6 months documented between May 2015 and August 2021 in a single institution with four major healthcare practice regions. Our fusion AI pipeline receives the coronal and axial plane images of a contrast enhanced abdominopelvic CT exam and basic patient demographics (age, gender, body cross section lengths) to predict risk of low bone mass. The models were trained on lumbar spine T-scores from DXA exams and tested on multi-site imaging exams. The model was again tested in a prospective group (N = 344) contrast-enhanced and non-contrast-enhanced studies. RESULTS: The models were evaluated on the same test set (1208 exams)-(1) Baseline model using demographic factors from electronic medical records (EMR) - 0.7 area under the curve of receiver operator characteristic (AUROC); Imaging based models: (2) axial view - 0.83 AUROC; (3) coronal view- 0.83 AUROC; (4) Fusion model-Imaging + demographic factors - 0.86 AUROC. The prospective test yielded one missed positive DXA case with a hip prosthesis among 23 positive contrast-enhanced CT exams and 0% false positive rate for non-contrast studies. Both positive cases among non-contrast enhanced CT exams were successfully detected. While only about 8% patients from prospective study received a DXA exam within 2 years, about 30% were detected with low bone mass by the fusion model, highlighting the need for opportunistic screening. CONCLUSIONS: The fusion model, which combines two planes of CT images and EMRs data, outperformed individual models and provided a high, robust diagnostic performance for opportunistic screening of low bone density using contrast and non-contrast CT exams. This model could potentially improve bone health risk assessment with no additional cost. The model's handling of metal implants is an ongoing effort.

Lung texture in serial thoracic CT scans: assessment of change introduced by image registration.

PURPOSE: The aim of this study was to quantify the effect of four image registration methods on lung texture features extracted from serial computed tomography (CT) scans obtained from healthy human subjects. METHODS: Two chest CT scans acquired at different time points were collected retrospectively for each of 27 patients. Following automated lung segmentation, each follow-up CT scan was registered to the baseline scan using four algorithms: (1) rigid, (2) affine, (3) B-splines deformable, and (4) demons deformable. The registration accuracy for each scan pair was evaluated by measuring the Euclidean distance between 150 identified landmarks. On average, 1432 spatially matched 32 × 32-pixel region-of-interest (ROI) pairs were automatically extracted from each scan pair. First-order, fractal, Fourier, Laws' filter, and gray-level co-occurrence matrix texture features were calculated in each ROI, for a total of 140 features. Agreement between baseline and follow-up scan ROI feature values was assessed by Bland-Altman analysis for each feature; the range spanned by the 95% limits of agreement of feature value differences was calculated and normalized by the average feature value to obtain the normalized range of agreement (nRoA). Features with small nRoA were considered "registration-stable." The normalized bias for each feature was calculated from the feature value differences between baseline and follow-up scans averaged across all ROIs in every patient. Because patients had "normal" chest CT scans, minimal change in texture feature values between scan pairs was anticipated, with the expectation of small bias and narrow limits of agreement. RESULTS: Registration with demons reduced the Euclidean distance between landmarks such that only 9% of landmarks were separated by ≥1 mm, compared with rigid (98%), affine (95%), and B-splines (90%). Ninety-nine of the 140 (71%) features analyzed yielded nRoA > 50% for all registration methods, indicating that the majority of feature values were perturbed following registration. Nineteen of the features (14%) had nRoA < 15% following demons registration, indicating relative feature value stability. Student's t-tests showed that the nRoA of these 19 features was significantly larger when rigid, affine, or B-splines registration methods were used compared with demons registration. Demons registration yielded greater normalized bias in feature value change than B-splines registration, though this difference was not significant (p = 0.15). CONCLUSIONS: Demons registration provided higher spatial accuracy between matched anatomic landmarks in serial CT scans than rigid, affine, or B-splines algorithms. Texture feature changes calculated in healthy lung tissue from serial CT scans were smaller following demons registration compared with all other algorithms. Though registration altered the values of the majority of texture features, 19 features remained relatively stable after demons registration, indicating their potential for detecting pathologic change in serial CT scans. Combined use of accurate deformable registration using demons and texture analysis may allow for quantitative evaluation of local changes in lung tissue due to disease progression or treatment response.

Characterization of mesothelioma and tissues present in contrast-enhanced thoracic CT scans.

PURPOSE: The purpose of this study was to characterize the Hounsfield unit (HU) distributions of mesothelioma and other tissues present in contrast-enhanced thoracic CT scans, to compare the HU distributions of mesothelioma, muscle, and liver by scanner and reconstruction filter/kernel combination, and to assess interpatient HU distribution variability. METHODS: The database consisted of 28 contrast-enhanced thoracic CT scans from different patients. For each scan, regions of interest were manually outlined within each of 13 tissues, including mesothelioma. For each tissue, the empirical percentiles in HU values were calculated along with the interpatient variability. The HU distributions of select tissues were compared across three different scanner and reconstruction filter/kernel combinations. RESULTS: The HU distributions of blood-containing tissues demonstrated substantial overlap, as did the HU distributions of pleural effusion, mesothelioma, muscle, and liver. The HU distribution of fat had the least overlap with the other tissues. Fat and muscle had the lowest interpatient HU variability and the narrowest HU distributions, while blood-containing tissues had the highest interpatient HU variability. A soft-tissue reconstruction filter/kernel yielded the narrowest HU distribution, and fat with artifact had the widest HU distribution. CONCLUSIONS: Characterization of tissues in CT scans enhances the understanding of those tissues' HU distributions. Due to their overlapping HU distributions and close spatial proximity to one another, separating pleural effusion, mesothelioma, muscle, and liver from one another is a difficult task based on HU value thresholding alone. The results illustrate the wide distributions and large variability that exist for tissues present in clinical thoracic CT scans.

Computerized segmentation and measurement of malignant pleural mesothelioma.

PURPOSE: The current linear method to track tumor progression and evaluate treatment efficacy is insufficient for malignant pleural mesothelioma (MPM). A volumetric method for tumor measurement could improve the evaluation of novel treatments, but a fully manual implementation of volume measurement is too tedious and time-consuming. This manuscript presents a computerized method for the three-dimensional segmentation and volumetric analysis of MPM. METHODS: The computerized MPM segmentation method segments the lung parenchyma and hemithoracic cavities to define the pleural space. Nonlinear diffusion and a k-means classifier are then implemented to identify MPM in the pleural space. A database of 31 computed tomography scans from 31 patients with pathologically confirmed MPM was retrospectively collected. Three observers independently outlined five randomly selected sections in each scan. The Jaccard similarity coefficient (J) between each of the observers and between the observer-defined and computer-defined segmentations was calculated. The computer-defined and the observer-defined segmentation areas (averaged over all observers) were both calculated for each axial section and compared using Bland-Altman plots. RESULTS: The median J value among observers averaged over all sections was 0.517. The median J between the computer-defined and manual segmentations was 0.484. The difference between these values was not statistically significant. The area delineated by the computerized method demonstrated variability and bias comparable to the tumor area calculated from manual delineations. CONCLUSIONS: A computerized method for segmentation and measurement of MPM was developed. This method requires minimal initialization by the user and demonstrated good agreement with manually drawn outlines and area measurements. This method will allow volumetric tracking of tumor progression and may improve the evaluation of novel MPM treatments.