The United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) recently reported a reduction in the average overall mortality among ovarian cancer patients screened with an annual sequential, multimodal strategy that tracked biomarker CA125 over time, where increasing serum CA125 levels prompted ultrasound. However, multiple cases were documented wherein serum CA125 levels were rising, but ultrasound screens were normal, thus delaying surgical intervention. A significant factor which could contribute to false negatives is that many aggressive ovarian cancers are believed to arise from epithelial cells on the fimbriae of the fallopian tubes, which are not readily imaged. Moreover, because only a fraction of metastatic tumors may reach a sonographically-detectable size before they metastasize, annual screening with ultrasound may fail to detect a large fraction of early-stage ovarian cancers. The ability to detect ovarian carcinomas before they metastasize is critical and future efforts towards improving screening should focus on identifying unique features specific to aggressive, early-stage tumors, as well as improving imaging sensitivity to allow for detection of tubal lesions. Implementation of a three-stage multimodal screening strategy in which a third modality is employed in cases where the first-line blood-based assay is positive and the second-line ultrasound exam is negative may also prove fruitful in detecting early-stage cases missed by ultrasound.

Purpose: Most methods to estimate patient dose from computed tomography (CT) exams have been developed based on fixed tube current scans. However, in current clinical practice, many CT exams are performed using tube current modulation (TCM). Detailed information about the TCM function is difficult to obtain and therefore not easily integrated into patient dose estimate methods. The purpose of this study was to investigate the accuracy of organ dose estimates obtained using methods that approximate the TCM function using more readily available data compared to estimates obtained using the detailed description of the TCM function. Methods: Twenty adult female models generated from actual patient thoracic CT exams and 20 pediatric female models generated from whole body PET/CT exams were obtained with IRB (Institutional Review Board) approval. Detailed TCM function for each patient was obtained from projection data. Monte Carlo based models of each scanner and patient model were developed that incorporated the detailed TCM function for each patient model. Lungs and glandular breast tissue were identified in each patient model so that organ doses could be estimated from simulations. Three sets of simulations were performed: one using the original detailed TCM function (x, y, and z modulations), one using an approximation to the TCM function (only the z-axis or longitudinal modulation extracted from the image data), and the third was a fixed tube current simulation using a single tube current value which was equal to the average tube current over the entire exam. Differences from the reference (detailed TCM) method were calculated based on organ dose estimates. Pearson's correlation coefficients were calculated between methods after testing for normality. Equivalence test was performed to compare the equivalence limit between each method (longitudinal approximated TCM and fixed tube current method) and the detailed TCM method. Minimum equivalence limit was reported for each organ. Results: Doses estimated using the longitudinal approximated TCM resulted in small differences from doses obtained using the detailed TCM function. The calculated root-mean-square errors (RMSE) for adult female chest simulations were 9% and 3% for breasts and lungs, respectively; for pediatric female chest and whole body simulations RMSE were 9% and 7% for breasts and 3% and 1% for lungs, respectively. Pearson's correlation coefficients were consistently high for the longitudinal approximated TCM method, ranging from 0.947 to 0.999, compared to the fixed tube current value ranging from 0.8099 to 0.9916. In addition, an equivalence test illustrated that across all models the longitudinal approximated TCM is equivalent to the detailed TCM function within up to 3% for lungs and breasts. Conclusions: While the best estimate of organ dose requires the detailed description of the TCM function for each patient, extracting these values can be difficult. The presented results show that an approximation using available data extracted from the DICOM h...

The purpose of this study was to reduce the radiation dosage associated with computed tomography (CT) lung cancer screening while maintaining overall diagnostic image quality and definition of ground‐glass opacities (GGOs). A lung screening phantom and a multipurpose chest phantom were used to quantitatively assess the performance of two iterative image reconstruction algorithms (adaptive statistical iterative reconstruction (ASIR) and model‐based iterative reconstruction (MBIR)) used in conjunction with reduced tube currents relative to a standard clinical lung cancer screening protocol (51 effective mAs (3.9 mGy) and filtered back‐projection (FBP) reconstruction). To further assess the algorithms' performances, qualitative image analysis was conducted (in the form of a reader study) using the multipurpose chest phantom, which was implanted with GGOs of two densities. Our quantitative image analysis indicated that tube current, and thus radiation dose, could be reduced by 40% or 80% from ASIR or MBIR, respectively, compared with conventional FBP, while maintaining similar image noise magnitude and contrast‐to‐noise ratio. The qualitative portion of our study, which assessed reader preference, yielded similar results, indicating that dose could be reduced by 60% (to 20 effective mAs (1.6 mGy)) with either ASIR or MBIR, while maintaining GGO definition. Additionally, the readers' preferences (as indicated by their ratings) regarding overall image quality were equal or better (for a given dose) when using ASIR or MBIR, compared with FBP. In conclusion, combining ASIR or MBIR with reduced tube current may allow for lower doses while maintaining overall diagnostic image quality, as well as GGO definition, during CT lung cancer screening.PACS numbers: 87.57.Q‐, 87.57.nf

From a dosimetry perspective, the MDCT scanners tested in this study demonstrated a high degree of within-run, between-run, and between-scanner precision (with relative precision errors typically well under 5%).

The proposed Lambert W model accurately describes attenuation of both monoenergetic radiation and (kilovoltage) polyenergetic beams (under narrow-beam geometry).