Model observers for Low Contrast Detectability evaluation in dynamic angiography: A feasible approach

Adaptation of a channelized Hotelling observer model to accommodate anthropomorphic backgrounds and moving test objects in X-ray angiography

BACKGROUND

Prior implementations of the channelized Hotelling observer (CHO) model have succeeded in assessing the performance of X-ray angiography systems under a variety of imaging conditions. However, often times these conditions do not resemble those present in routine clinical imaging scenarios, such as having complex anthropomorphic backgrounds in conjunction with moving test objects.

PURPOSE

This work builds up on prior established CHO methods and introduces a new approach to switch from the already established "multiple-sample" CHO implementation to a "single-sample" technique. The proposed implementation enables the inclusion of moving test objects upon nonuniform backgrounds by allowing only a single sample to represent the test object present condition that is to be used within the statistical test to estimate the detectability index.

METHODS

To assess the proposed method, two image data sets were acquired with a clinical X-ray angiography system. The first set consisted of a uniform background in combination with static test objects while the second consisted of an anthropomorphic chest phantom in conjunction with moving test objects. The first set was used to validate the proposed approach against the multiple-sample method while the second was used to assess the feasibility of the proposed method under a variety of imaging conditions, including seven object sizes and seven detector target dose (DTD) levels.

RESULTS

For the uniform background data set, considering all detectability indices greater or equal than 1, the ratio between the detectability indices of the proposed single-sample approach versus the multiple-sample method was 0.997 ± 0.056 (range 0.884-1.159). The average single-direction width of the 95% confidence intervals (CIs) of the detectability index estimates for the multiple-sample method was 0.38 ± 0.43 (range 0.03-2.20). For the single-sample approach, the average width was 2.52 ± 0.63 (range 1.11-5.44). For the anthropomorphic background image set, the results were consistent with classical quantum-limited signal-to-noise ratio (SNR) theory. The magnitude of the detectability indices varied predictably with changes in both object size and DTD, with the highest value associated with the highest dose and the largest object size. Additionally, the proposed method was able to capture differences in the imaging performance for a given test object across the field of view, which was associated with the attenuation levels provided by different features of the anthropomorphic background.

CONCLUSIONS

A new single-sample variant of the CHO model to assess the performance of X-ray angiography imaging systems is proposed. The new approach is consistent with quantum-limited image quality theory and with a standard implementation of the CHO model. The proposed method enables the assessment of moving test objects in combination with complex, nonuniform image backgrounds, thereby opening the possibility to assess imaging conditions which more closely resemble those used in clinical care.

Spatio-temporal generalized Model Observers methods for Low Contrast Detectability assessment in digital angiography: Application to moving targets

The purpose of this work is to investigate the feasibility of spatio-temporal generalized Model Observer methods for protocol optimization programs in the field of interventional radiography. Two Model Observers were taken under examination: a Channelized Hotelling Observer with 24 spatio-temporal Gabor channels and a Non Pre-Whitening Model Observer with two different implementations of the spatio-temporal contrast sensitivity function. The images of targets, both stationary and in motion, were acquired in fluoroscopic mode using a CDRAD phantom for signal-present images and an homogenous slab of PMMA for signal-absent ones. After the processing, these images were used to build three series of two alternative forced choice experiments, designed to simulate tasks of clinical interest, and submitted to three human observers in order to set a goal on detectability. A first set of images was used for model tuning and subsequently the verified models were validated throughout a second set of images. Results from the validation phase, for both models, show good agreement with the human observer performances (Root Mean Square Error RMSE ≤ 12%). The tuning phase emerges as a crucial step in building models for angiographic dynamic images; the final agreement underlines the good capability of these spatio-temporal models in simulating human performances, allowing to consider them as a useful and worthwhile tool in protocol optimization when dynamic images are involved.

A single phantom, a single statistical method for low-contrast detectability assessment

PURPOSE

The assessment of low-contrast-details is a part of the quality control (QC) program in digital radiology. It generally consists of evaluating the threshold contrast (Cth) detectability details for different-sized inserts, appropriately located in dedicated QC test tools. This work aims to propose a simplified method, based on a statistical model approach for threshold contrast estimation, suitable for different modalities in digital radiology.

METHODS

A home-madelow-contrast phantom, made of a central aluminium insert with a step-wedge, was assembled and tested. The reliability and robustness of the method were investigated for Mammography, Digital Radiography, Fluoroscopy and Angiography. Imageswere analysed using our dedicated software developed on Matlab®. TheCth is expressed in the same unit (mmAl) for all studied modalities.

RESULTS

This method allows the collection of Cthinformation from different modalities and equipment by different vendors, and it could be used to define typical values. Results are summarized in detail. For 0.5 diameter detail, Cthresults are in the range of: 0.018-0.023 mmAl for 2D mammography and 0.26-0.34 mmAl DR images. For angiographic images, for 2.5 mm diameter detail, the Cths median values are 0.55, 0.4, 0.06, 0.12 mmAl for low dose fluoroscopy, coronary fluorography, cerebral and abdominal DSA, respectively.

CONCLUSIONS

The statistical method proposed in this study gives a simple approach for Low-Contrast-Details assessment, and the typical values proposed can be implemented in a QA program for digital radiology modalities.

SIGNAL-TO-NOISE RATIO RATE MEASUREMENT IN FLUOROSCOPY FOR QUALITY CONTROL AND TEACHING GOOD RADIOLOGICAL IMAGING TECHNIQUE

Visibility of low-contrast details in fluoroscopy and interventional radiology is important. Assessing detail visibility with human observers typically suffers from large observer variances. Objective, quantitative measurement of low-contrast detail visibility using a model observer, such as the square of the signal-to-noise ratio rate (SNR2rate), was implemented in MATLAB™ and evaluated. The expected linear response of SNR2rate based on predictions by the so-called Rose model and frame statistics was verified. The uncertainty in the measurement of SNR2rate for a fixed imaging geometry was 6% based on 16 repeated measurements. The results show that, as expected, reduced object thickness and x-ray field size substantially improved SNR2rate/PKA,rate with PKA,rate being the air kerma area product rate. The measurement precision in SNR2rate/PKA,rate (8-9%) is sufficient to detect small but important improvements, may guide the selection of better imaging settings and provides a tool for teaching good radiological imaging techniques to clinical staff.

Evaluation of a no-reference image quality metric for projection X-ray imaging using a 3D printed patient-specific phantom

PURPOSE

Feasability of a no-reference image quality metric was assessed on patient-like images using a patient-specific phantom simulating a frame of a coronary angiogram.

METHODS

One background and one contrast-filled frame of a coronary angiogram, acquired using a clinical imaging protocol, were selected from a Philips Integris Allura FD (Philips Healthcare, Best, The Netherlands). The background frame's pixels were extruded to a thickness proportional to their grey value. One phantom was 3D printed using composite 80% bronze filament (max. thickness of 5.1 mm), the other was a custom PMMA cast (max thickness of 8.5 cm). A vessel mold was created from the contrast-filled frame and injected with a solution of 320 mg I/ml contrast fluid (75%), water and gelatin. Still X-ray frames of the vessel mold + background phantom + 16 cm PMMA were acquired at manually selected different exposure settings using a Philips Azurion (Philips Healthcare, Best, The Netherlands) in User Quality Control Mode and were exported as RAW images. The signal-difference-to-noise-ratio-squared (SDNR²) and a spatial-domain-equivalent of the noise equivalent quanta (NEQ_SDE) were calculated. The Spearman's correlation of the latter parameters with a no-reference perceptual image quality metric (NIQE) was investigated.

RESULTS

The bronze phantom showed better resemblance to the original patient frame selected from a coronary angiogram of an actual patient, with better contrast and less blur than the PMMA phantom. Both phantoms were imaged using a comparable imaging protocol to the one used to acquire the original frame. The bronze phantom was hence used together with the vessel mold for image quality measurements on the 165 still phantom frames. A strong correlation was noted between NEQ_SDE and NIQE (SROCC = -0.99, p < 0.0005) and between SDNR² and NIQE (SROCC = -0.97, p < 0.0005).

CONCLUSION

Using a cost-effective and easy to realize patient-specific phantom we were able to generate patient-like X-ray frames. NIQE as a no-reference image quality model has the potential to predict physical image quality from patient images.

Typical values related to the complexity of interventional treatment of acute ischemic stroke

BACKGROUND AND PURPOSE

Interventional Neuroradiology (INR) procedures are often complex, requiring prolonged high-dose exposures. This leads to increased radiation exposure to both patient and operating staff. The purpose of this study is to identify parameters related to the complexity of acute ischemic stroke (AIS) procedures that increase patient exposure and derive DRLs according to ICRP 135.

METHODS

Data from 145 patients treated for AIS between 2017 and 2019 in a Hub Stroke center were retrospectively analyzed. Dosimetric parameters, demographic and clinical data were collected for each patient. The INR operator and the fluoroscopy system used were included.

RESULTS

A multivariable analysis was performed to identify which parameters significantly influence the dosimetric data. Thrombus location and the use of stent retriever were noted as the most likely parameters of complex INR procedures. Male sex is an indicator of complex procedure only with regards to the Kerma area product and the air kerma. Patient age significantly affects the exposure time alone. Senior or more experienced operator's data demonstrated reduced patient's exposure time and therefore the KAP and Kar values. The type of X-ray equipment influenced the outcome of the procedure in terms of number of images acquired. Typical values obtained are 168 Gycm², 0.68 Gy, 19 min and 181 images.

CONCLUSION

Typical values derived in this study promote patient dose optimization, when considering the complexity of INR procedures. The clinical variables related to the complexity of procedure that mainly affect the dosimetric data in our experience are thrombus location and use of stent retrievers.