Economic impact of spectral body imaging in diagnosis of patients suspected for occult cancer.

BACKGROUND: Based on prior studies spectral CT has shown a higher sensitivity for malignant lesions than conventional CT at the cost of lower specificity. For the radiologists, it also offers a higher degree of certainty in the diagnosis of benign lesions. The objective of this study was to evaluate the economic impact of spectral CT in patients suspected of occult cancer in a medical center in Denmark. METHODS: This study was a secondary analysis using de-identified data from a prospective study of patients receiving a contrast-enhanced spectral CT scan. Based on suggested follow-up examinations on both spectral CT and contrast-enhanced CT, costs from a payer's perspective were determined using unit costs obtained from national databases. RESULTS: The dataset contained 400 patients. Overall, 203 follow-up procedures were eliminated based on spectral data reading. The largest reduction in suggested follow-up procedures was found for the kidney (83%), followed by the liver (66%), adrenal glands (60%), and pancreas (42%). The total estimated costs for suggested follow-up procedures based on spectral data reading were €155,219, 25.2% (€52,384) less than that of conventional CT reading. CONCLUSION: Our results provide support for spectral body imaging as an advanced imaging modality for suspected occult cancer. A substantial number of follow-up diagnostic procedures could be eliminated based on spectral data reading, which would result in significant cost savings.

Lung-RADS Version 1.0 versus Lung-RADS Version 1.1: Comparison of Categories Using Nodules from the National Lung Screening Trial.

Background The American College of Radiology updated Lung Imaging Reporting and Data System (Lung-RADS) version 1.0 to version 1.1 in May 2019, with the two key changes involving perifissural nodules (PFNs) and ground-glass nodules (GGNs) now designated as a negative screening result. This study examines the effects of these changes using National Lung Screening Trial (NLST) data. Purpose To determine the frequency of PFNs and GGNs reclassified from category 3 or 4A to the more benign category 2 in the updated Lung-RADS version 1.1, as compared with Lung-RADS version 1.0, using CT scans from the NLST. Materials and Methods In this secondary analysis of the NLST, the authors studied all noncalcified nodules (NCNs) found on the incident scan. Nodules were evaluated using criteria from both Lung-RADS version 1.0 and version 1.1, which were compared to determine changes in the number of nodules deemed benign. A McNemar test was used to assess statistical significance. Results A total of 2813 patients (mean age ± standard deviation, 62 years ± 5; 1717 men) with 4408 NCNs were studied. Of the largest 1092 solid NCNs measuring at least 6 mm but less than 10 mm, 216 (19.8%) were deemed PFNs (category 2) using Lung-RADS version 1.1. Eleven of the 1092 solid NCNs (1.0%) were malignant, but none were PFNs. Of 161 GGNs, three (1.9%) were category 3 according to Lung-RADS version 1.0, of which two (66.7%) were down-classified to category 2 with version 1.1. One of the three down-categorized GGNs (version 1.1) proved to be malignant (false-negative finding). Statistically significant improvement for Lung-RADS version 1.1 was found for total nodules (P < .01) and PFNs (P < .01), but not GGNs (P = .48). Conclusion This secondary analysis of National Lung Screening Trial data shows that Lung Imaging Reporting and Data System version 1.1 decreased the number of false-positive results. This was related to the down-classification of perifissural nodules in the range of 6 up to 10 mm. The increase in allowable nodule size for ground-glass nodules in category 2 from 20 mm (version 1.0) to 30 mm (version 1.1) showed no benefit. © RSNA, 2021 See also the editorial by Mayo and Lam in this issue.

Follow-up Recommendation Rates Associated With Spectral Detector Dual-Energy CT of the Abdomen and Pelvis: A Retrospective Comparison to Single-Energy CT.

BACKGROUND: Dual-energy CT image sets have many applications in abdominopelvic imaging but no demonstrated clinical effect. PURPOSE: To determine the effect of dual-energy CT iodine maps on abdominopelvic imaging follow-up recommendation rates. MATERIALS AND METHODS: Retrospective study of abdominopelvic CTs acquired from April 2017 through June 2018. CT reports were analyzed for radiologic follow-up recommendation and follow-up recommendation reason. Follow-up MRI reports were analyzed for benign or nonbenign diagnosis. CT scans with iodine maps (CTIMs) and conventional CT scans (CCTs) subgroups were compared using χ2 testing. RESULTS: In all, 3,221 abdominopelvic CT scans of 2,401 patients (1,326 men, 1,075 women, mean age 54.1 years) were analyzed; 1,423 were CTIMs and 1,798 were CCTs. Follow-up recommendation rates were not significantly different for CTIMs and CCTs (19.5% and 21.4%, respectively, P = .19). Follow-up recommendations because of incomplete diagnosis were significantly lower in CTIMs (9.1%) than in CCTs (11.9%, P = .01). Follow-up recommendations for MRI and PET/CT were significantly lower in CTIMs (9.6%) than CCTs (13.0%, P = .003). Follow-up MRI outcomes (n = 111) were not different between CTIMs (61.2% benign) and CCTs (59.6%, P = .87). CONCLUSION: Dual-energy CT iodine maps are associated with decreased follow-up examinations because of incomplete diagnosis and decreased recommendations for follow-up MRI, suggesting that abdominopelvic iodine maps may benefit patient care and decrease institutional cost.

Vancouver Risk Calculator Compared with ACR Lung-RADS in Predicting Malignancy: Analysis of the National Lung Screening Trial.

Purpose To compare the Vancouver risk calculator (VRC) with American College of Radiology (ACR) Lung Imaging Reporting and Data System (Lung-RADS) in predicting the risk of malignancy in the National Lung Screening Trial (NLST). Materials and Methods A total of 2813 patients with 4408 nodules (4078 solid, 330 subsolid) were available from the NLST for evaluation. Nodules were scored by using VRC with nine parameters (output was the percentage likelihood of malignancy; VRC threshold for malignancy likelihood set as greater than 5%) and Lung-RADS (output was category 2-4B; malignancy defined as category 4A or 4B; malignancy likelihood greater than 5%). Lung-RADS and VRC were compared for sensitivity, specificity, and accuracy for malignancy on a per-nodule and per-patient basis. Results Of 4408 total nodules, 100 of 4078 (2.5%) solid nodules were malignant and 10 of 330 (3%) subsolid nodules were malignant. On an overall per-nodule basis, the sensitivity, specificity, and accuracy for VRC and Lung-RADS were 93%, 90%, and 90% for VRC and 87%, 83%, and 83% for Lung-RADS, respectively (P = .077, P < .001, and P < .001, respectively). On a per-patient basis, the sensitivity, specificity, and accuracy for VRC and Lung-RADS were 93%, 85%, and 85% for VRC and 87%, 76%, and 76% for Lung-RADS, respectively (P = .077, P < .001, and P < .001, respectively). Conclusion The Vancouver risk calculator had superior overall accuracy than the Lung Imaging Reporting and Data System in predicting malignancy in the National Lung Screening Trial for total nodules, as well as on a per-patient basis. © RSNA, 2019 See also the editorial by Black in this issue.

Dual-energy CT in the obese: a preliminary retrospective review to evaluate quality and feasibility of the single-source dual-detector implementation.

PURPOSE: To determine the feasibility of performing dual-energy CT with a single-source spectral detector system in obese patients. MATERIALS AND METHODS: Retrospective, IRB-approved review of 28 patients weighing ≥ 270 lbs (122 kg) who underwent CT of the abdomen on a single-source spectral detector system was performed. Two blinded, independent radiologists rated relative preference between conventional CT images taken at 120 kVp (CCT120) and monoenergetic 70 keV equivalent (MonoE70) as well as iodine map image quality in the spleen, pancreas, kidneys, and liver. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between conventional CT and MonoE70 images and correlated with body habitus markers of weight, height, and abdominal diameter. RESULTS: MonoE70 images were preferred by radiologists 100% of the time (1-sample t test, p < 0.0001) over conventional CCT120 images. Noise was significantly lower; SNR and CNR were significantly higher in MonoE70 images than in CCT120 images (paired t tests, p < 0.0001). Mean iodine map rating (scale 1-5) was 4.54 ± 0.58, denoting near homogenous and complete iodine mapping through the spleen, pancreas, kidneys, and liver for the majority of patients. Body habitus markers were not significantly correlated with image preference score; noise; MonoE70 SNR; MonoE70 CNR; change in noise, SNR, or CNR from CCT120 to MonoE70, or iodine map quality; ordinal and linear regression, p = 0.2547, p = 0.6837, p = 0.1888, p = 0.5489, p = 0.9830, p = 0.8849, p = 0.8741, p = 0.1522, respectively. CONCLUSION: The single-source spectral detector implementation of dual-energy CT provides viable, high-quality imaging for obese patients.

Dual-layer spectral detector CT monoenergetic reconstruction improves image quality of non-contrast cerebral CT as compared with conventional single energy CT.

PURPOSE: To investigate and compare image quality of monoenergetic reconstructions from spectral NCCT to conventional 120 kVp images acquired at a similar dose. MATERIALS AND METHODS: Patients undergoing NCCT on a dual-layer spectral detector CT (n = 30) and a conventional CT (n = 30) were enrolled in the study. The spectral detector CT data was reconstructed at monoenergetic images from 40 to 140 keV in 5-keV increments and 65-70 keV in 1-keV increments (Group A1) and using single energy CT equivalent reconstruction (Group A2). The reference conventional 120kVp images (Group B) were acquired using a standard-of-care protocol with the same radiation dose. We evaluated the image quality of monoenergetic images and determined the optimal keV level using HU attenuation, noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), artifact evaluation in posterior fossa by placing region-of-interest (ROI) and subjective image score by 2 radiologists independently using a 4-point scale (1-excellent, 4-undiagnostic). RESULTS: The SNR and subjective image score were optimal at 66-70keV, while monoenergetic 68 keV images with a higher SNR (18.48 ±â€¯1.94, 15.55 ±â€¯1.56 and 14.33 ±â€¯1.38 for Group 68keV, A2 and B respectively, p < 0.001), CNR (4.09 ±â€¯0.65, 3.43 ±â€¯0.56 and 3.52 ±â€¯0.55 for Group 68keV, A2 and B respectively, p < 0.001) and a lower noise (1.80 ±â€¯0.19, 2.11 ±â€¯0.19 and 2.25 ±â€¯0.25 for Group 68keV, A2 and B respectively, p < 0.001). CONCLUSION: Spectral NCCT monoenergetic reconstructions at 68 keV improve image quality and reduce artifact compared to conventional single energy CT without radiation dose penalty.

The Vancouver Lung Cancer Risk Prediction Model: Assessment by Using a Subset of the National Lung Screening Trial Cohort.

Purpose To assess the likelihood of malignancy among a subset of nodules in the National Lung Screening Trial (NLST) by using a risk calculator based on nodule and patient characteristics. Materials and Methods All authors received approval for use of NLST data. An institutional review board exemption and a waiver for informed consent were granted to the author with an academic appointment. Nodule characteristics and patient attributes with regard to benign and malignant nodules in the NLST were applied to a nodule risk calculator from a group in Vancouver, Canada. Patient populations and their nodule characteristics were compared between the NLST and Vancouver cohorts. Multiple thresholds were tested to distinguish benign nodules from malignant nodules. An optimized threshold value was used to determine positive and negative predictive values, and a full logistic regression model was applied to the NLST data set. Results Sufficient data were available for 4431 nodules (4315 benign nodules and 116 malignant nodules) from the NLST data set. The NLST and Vancouver data sets differed in that the former included fewer nodules per study, fewer nonsolid nodules, and more nodule spiculation and emphysema. A composite risk score threshold of 10% was determined to be optimal, demonstrating sensitivity, specificity, positive predictive value, and negative predictive value of 85.3%, 93.9%, 27.4%, and 99.6%, respectively. The receiver operating characteristic curve for the full regression model applied to the NLST database demonstrated an area under the receiver operating characteristic curve of 0.963 (95% confidence interval: 0.945, 0.974). Conclusion Application of an NLST data subset to the Vancouver risk calculator yielded a high discriminant value, which supports the use of a risk calculator method as a valuable approach to distinguish between benign and malignant nodules. © RSNA, 2016 Online supplemental material is available for this article.

Informatics in radiology: Hesse rendering for computer-aided visualization and analysis of anomalies at chest CT and breast MR imaging.

A volume-rendering (VR) technique known as Hesse rendering applies image-enhancement filters to three-dimensional imaging volumes and depicts the filter responses in a color-coded fashion. Unlike direct VR, which makes use of intensities, Hesse rendering operates on the basis of shape properties, such that nodular structures in the resulting renderings have different colors than do tubular structures and thus are easily visualized. The renderings are mouse-click sensitive and can be used to navigate to locations of possible anomalies in the original images. Hesse rendering is meant to complement rather than replace conventional section-by-section viewing or VR. Although it is a pure visualization technique that involves no internal segmentation or explicit object detection, Hesse rendering, like computer-aided detection, may be effective for quickly calling attention to points of interest in large stacks of images and for helping radiologists to avoid oversights.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.

PURPOSE: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. METHODS: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ("nodule > or =3 mm," "nodule <3 mm," and "non-nodule > or =3 mm"). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. RESULTS: The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "nodule > or =3 mm" by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. CONCLUSIONS: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.

Assessment of COPD severity by computed tomography: correlation with lung functional testing.

CT scans of 474 patients with suspected chronic obstructive pulmonary disease (COPD) were retrospectively evaluated by automated software. There was a correlation between the total lung capacity (TLC) and the total lung volume (TLV) (r=.675, P<.001), between the TLC and the total emphysema volume (r=.571, P<.001), as well as between the TLC and the emphysema index (r=.532, P<.001), respectively. The correlation between the TLC and the TLV was dependent on the COPD severity according to the Global Initiative for Chronic Obstructive Lung Disease classification (chi(2)=6.3079, P=.043). The TLC allows a prediction of clinical illness severity.

Lung nodule computer-aided detection as a second reader: influence on radiology residents.

OBJECTIVE: The purpose of this study was to evaluate the use of a computed tomographic lung nodule computer-aided detection (CAD) software as a second reader for radiology residents. METHODS: The study involved 110 cases from 4 sites. Three expert radiologists identified nodules that were 4 to 30 mm in maximum diameter to form the ground truth. These cases were then interpreted by 6 board-certified radiologists and 6 radiology residents. The residents read each case without and then with a CAD software (Lung Nodule Assesment, Extended Brilliance Workspace; Philips Healthcare, Highlands Heights, OH) to identify nodules that were 4 to 30 mm in maximum diameter. RESULTS: The experts identified 91 nodules as the ground truth for the study. The mean sensitivity of the 6 board-certified radiologists was 89%. The mean sensitivity of the residents was 85% without the CAD and 90% (P < 0.05) with the CAD as a second reader. CONCLUSIONS: The CAD software can help improve the sensitivity of residents in the detection of pulmonary nodules on computed tomography, making them comparable with board-certified radiologists.

Lung nodule CAD software as a second reader: a multicenter study.

RATIONALE AND OBJECTIVES: The purpose of this multicenter, multireader study was to evaluate the performance of computed tomography (CT) lung nodule computer-aided detection (CAD) software as a second reader. METHODS AND MATERIALS: The study involved 109 patients from four sites. The data were collected from a variety of multidetector CT scanners and had different scan parameters. Each chest CT scan was divided into four quadrants. A group of three expert thoracic radiologists identified nodules between 4 and 30 mm in maximum diameter within each quadrant. The standard of reference was established by a consensus read of these experienced radiologists. The cases were then interpreted by 10 other radiologist readers with varying degrees of experience, without and then with CAD software. These readers identified nodules and assigned an actionability rating to each quadrant before and after using CAD software. Receiver operating characteristic curves were used to measure the performance of the readers without and with CAD software. RESULTS: The average increase in area under the curve for the 10 readers with CAD software was 1.9% for a 95% confidence interval (0.8-8.0%). The area under the curve without CAD software was 86.7% and with CAD software was 88.7%. A nonsignificant correlation was observed between the improvement in sensitivity and experience of the radiologists. The readers also showed a greater improvement in patients with cancer as compared to those without cancer. CONCLUSIONS: In this multicenter trial, CAD software was shown to be effective as a second reader by improving the sensitivity of the radiologists in detecting pulmonary nodules.

Comparison of manual and automated size measurements of lung metastases on MDCT images: potential influence on therapeutic decisions.

PURPOSE: The goal of this study was to evaluate the influence of automated measurement of diameter, area, and volume from chest CT scans on therapeutic decisions of lung nodules as compared to manual 2-D measurements. PATIENTS AND METHOD: The retrospective study involved 25 patients with 75 lung metastases. Contrast enhanced CT scans (16 row) of the lung were performed three times during chemotherapy with a mean time interval of 67.9 days between scans. In each patient, three metastases were evaluated (n=225). Automatic measurements were compared to manual assessment for the following parameters: diameter, area, and density. The influence on the therapeutic decisions was evaluated using the RECIST criteria. RESULTS: The maximum diameter measured by the automatic application was on an average 27% (S.D. 39; CI: 0.22-0.32; p<0.0001) higher than the maximum diameter with manual assessment, and the differences depended on metastases size. Based on diameter calculation, manual and automated assessment disagreed in up to 32% of therapeutic decisions. Volumetric assessment tended towards more changes in therapy as compared to diameter calculation. The calculation of mean transversal area of metastases was 36% (S.D. 0.305; CI: -0.40 to -0.32; p<0.0001) less with automated measurement. Therapeutic strategy would be changed in up to 25.7% of nodules using automated area calculation. Automated assessment of nodules' area and volume could influence the therapeutic decisions in up to 51.4% of all nodules. Density of the nodules was not validated to determine the influence on therapeutic decisions. CONCLUSION: There is a discrepancy between the manual and automated size measurement of lung metastases which could be significant.