One-mSv CT colonography: Effect of different iterative reconstruction algorithms on radiologists' performance

Diagnostic accuracy of ultra-low-dose CT colonography for the detection of colorectal polyps: a feasibility study

PURPOSE

The aim of this feasibility study was to evaluate the diagnostic accuracy of ultra-low-dose CT colonography using iterative reconstruction algorithms with reference to standard colonoscopy.

MATERIALS AND METHODS

Prior to this study, a phantom study was performed to investigate the optimal protocol for ultra-low-dose CT colonography. A total of 206 patients with average/high risk of colorectal cancer were recruited. After undergoing full bowel preparation, the patients were scanned in the prone and supine positions with the CT conditions set to 120 kV, standard deviation 45 to 50, and an adaptive iterative reconstruction algorithm applied. Two expert readers read the images independently. The main outcome measures were the per-patient and per-polyp accuracies for the detection of polyps ≥ 10 mm, with colonoscopy results as the reference standard.

RESULTS

Two hundred patients (102 females, mean age 67.5 years) underwent both ultra-low-dose CT colonography and colonoscopy on the same day. The mean radiation exposure dose was 0.64 ± 0.34 mSv. On colonoscopy, 39 patients had 45 polyps ≥ 10 mm (non-polypoid morphology 7), including 4 cancers. Per-patient sensitivity, specificity, and accuracy of CT colonography for polyps ≥ 10 mm were 0.74, 0.96, and 0.92 for reader one, and 0.74, 0.99, and 0.94 for reader two, respectively. Per-polyp sensitivities for polyps ≥ 10 mm were 0.73 for reader one and 0.71 for reader two. On subgroup analysis by morphology, non-polypoid polyps ≥ 10 mm were not detected by both readers.

CONCLUSION

Extreme ultra-low-dose CT colonography had an insufficient diagnostic performance for the detection of polyps ≥ 10 mm, because it was unable to detect non-polypoid polyps. This study showed that the problem with ultra-low-dose CT colonography was the lack of detectability of small-size polyps, especially non-polypoid polyps. To use ultra-low-dose CT colonography clinically, it is necessary to resolve the problems identified by this study.

EXTRACOLONIC FINDINGS-IDENTIFICATION AT LOW-DOSE CTC

In contrast to optical colonoscopy, computed tomography colonography (CTC) has the ability to reveal pathology outside of the colon. While identification of colorectal lesions at CTC requires only limited radiation dose, the detection of abnormalities in extracolonic soft tissue requires more radiation. The purpose of this study was to investigate the influence of ultra-low-dose (ULD) CTC on the detection and characterisation of extracolonic findings. In a prospective study 49 patients with colorectal symptoms were examined with CTC adding a ULD series (mean effective dose 0.9 ± 0.4 mSv) to the normal unenhanced standard dose (SD) series (mean effective dose 3.6 ± 1.2 mSv). Five radiologists individually and blindly evaluated the ULD, followed by evaluation of the SD after ≥9 weeks (median 35 weeks). A ViewDEX-based examination protocol was used, including a confidence scale and a graded assessment of need for follow-up according to the CTC Reporting and Data System (C-RADS E0-E4). The reference findings comprised the combined information from CTC (ULD, SD and contrast-enhanced CTC series) and a 4-year radiological and clinical follow-up. For the overall detection of reference findings (E2-E4) we found a statistically significant difference in favour of SD. This, however, was not the case when looking at classification of possibly important/important reference findings (E3-E4). Our results suggest that CTC with ULD (0.9 mSv) is comparable to SD (3.6 mSv) for identification of clinically relevant extracolonic pathology, but there is a large inter-observer variability.

Ultra-low dose CT colonography with automatic tube current modulation and sinogram-affirmed iterative reconstruction: Effects on radiation exposure and image quality

Objective

To assess the radiation dose and image quality of ultra‐low dose (ULD)‐CT colonography (CTC) obtained with the combined use of automatic tube current (mAs) modulation with a quality reference mAs of 25 and sinogram‐affirmed iterative reconstruction (SAFIRE), compared to low‐dose (LD) CTC acquired with a quality reference mAs of 55 and reconstructed with filtered back projection (FBP).

Methods

Eighty‐two patients underwent ULD‐CTC acquisition in prone position and LD‐CTC acquisition in supine position. Both ULD‐CTC and LD‐CTC protocols were compared in terms of radiation dose [weighted volume computed tomography dose index (CTDI_vol) and effective dose], image noise, image quality, and polyp detection.

Results

The mean effective dose of ULD‐CTC was significantly lower than that of LD‐CTC (0.98 and 2.69 mSv respectively, P < 0.0001) with an overall dose reduction of 63.2%. Image noise was comparable between ULD‐CTC and LD‐CTC (28.6 and 29.8 respectively, P = 0.09). There was no relevant difference when comparing image quality scores and polyp detection for both 2D and 3D images.

Conclusion

ULD‐CTC allows to significantly reduce the radiation dose without meaningful image quality degradation compared to LD‐CTC.

Low-Dose Computed Tomography Colonography Technique

Significant anxiety has been expressed by some over the radiation risks associated with computed tomography (CT), particularly when it applies to a screening examination such as CT colonography. These theoretic risks are far outweighed by the significant benefits colorectal cancer screening offers. Regardless of how significant the theoretic risk of CT radiation is in the older population, the ALARA principle maintains that radiation dose should be reduced to As Low As Reasonably Achievable. This article will discuss various strategies that may be utilized to reduce radiation dose and mitigate any increase in image noise that may occur.

Diagnostic accuracy of low-dose versus ultra-low-dose CT for lumbar disc disease and facet joint osteoarthritis in patients with low back pain with MRI correlation

OBJECTIVE

To compare the image quality, radiation dose, and diagnostic performance between low-dose (LD) and ultra-low-dose (ULD) lumbar-spine (L-spine) CT with iterative reconstruction (IR) for patients with chronic low back pain (LBP).

METHODS

In total, 260 patients with chronic LBP who underwent L-spine CT between November 2015 and September 2016 were prospectively enrolled. Of these, 143 underwent LD-CT with IR and 117 underwent ULD-CT with IR. The patients were divided according to their body mass index (BMI) into BMI1 (<22.9 kg/m²), BMI2 (23.0-24.9 kg/m²), and BMI3 (≥25 kg/m²) groups. Two blinded radiologists independently evaluated the signal-to-noise ratio (SNR), qualitative image quality, and final diagnoses (lumbar disc disease and facet joint osteoarthritis). L-spine MRIs interpreted by consensus were used as the reference standard. All data were statistically analyzed.

RESULTS

ULD protocol showed significantly lower SNR for all patients (p < 0.001) except the vertebral bodies and lower qualitative image quality for BMI3 patients (p ≤ 0.033). There was no statistically significant difference between ULD (sensitivity, 95.1-98.1%; specificity, 92.5-98.7%; accuracy, 94.6-98.0%) and LD protocols (sensitivity, 95.6-100%; specificity, 95.5-98.9%; accuracy, 97.4-98.1%), (all p≥0.1) in the BMI1 and BMI2; while dose was 60-68% lower with the ULD protocol. Interobserver agreements were excellent or good with regard to image quality and final diagnoses.

CONCLUSIONS

For the BM1 and BMI2 groups, ULD-CT provided an acceptable image quality and exhibited a diagnostic accuracy similar to that of LD-CT. These findings suggest that it is a useful diagnostic tool for patients with chronic LBP who exhibit a BMI of <25 kg/m².

Lack of agreement between radiologists: implications for image-based model observers

We tested the agreement of radiologists' rankings of different reconstructions of breast computed tomography images based on their diagnostic (classification) performance and on their subjective image quality assessments. We used 102 pathology proven cases (62 malignant, 40 benign), and an iterative image reconstruction (IIR) algorithm to obtain 24 reconstructions per case with different image appearances. Using image feature analysis, we selected 3 IIRs and 1 clinical reconstruction and 50 lesions. The reconstructions produced a range of image quality from smooth/low-noise to sharp/high-noise, which had a range in classifier performance corresponding to AUCs of 0.62 to 0.96. Six experienced Mammography Quality Standards Act (MQSA) radiologists rated the likelihood of malignancy for each lesion. We conducted an additional reader study with the same radiologists and a subset of 30 lesions. Radiologists ranked each reconstruction according to their preference. There was disagreement among the six radiologists on which reconstruction produced images with the highest diagnostic content, but they preferred the midsharp/noise image appearance over the others. However, the reconstruction they preferred most did not match with their performance. Due to these disagreements, it may be difficult to develop a single image-based model observer that is representative of a population of radiologists for this particular imaging task.