The impact of iterative reconstruction on image quality and radiation dose in thoracic and abdominal CT

An inventory of patient-image based risk/dose, image quality and body habitus/size metrics for adult abdomino-pelvic CT protocol optimisation

PURPOSE

Patient-specific protocol optimisation in abdomino-pelvic Computed Tomography (CT) requires measurement of body habitus/size (BH), sensitivity-specificity (surrogates image quality (IQ) metrics) and risk (surrogates often dose quantities) (RD). This work provides an updated inventory of metrics available for each of these three categories of optimisation variables derivable directly from patient measurements or images. We consider objective IQ metrics mostly in the spatial domain (i.e., those related directly to sharpness, contrast, noise quantity/texture and perceived detectability as these are used by radiologists to assess the acceptability or otherwise of patient images in practice).

MATERIALS AND METHODS

The search engine used was PubMed with the search period being 2010-2024. The key words used were: 'comput* tomography', 'CT', 'abdom*', 'dose', 'risk', 'SSDE', 'image quality', 'water equivalent diameter', 'size', 'body composition', 'habit*', 'BMI', 'obes*', 'overweight'. Since BH is critical for patient specific optimisation, articles correlating RD vs BH, and IQ vs BH were reviewed.

RESULTS

The inventory includes 11 BH, 12 IQ and 6 RD metrics. 25 RD vs BH correlation studies and 9 IQ vs BH correlation studies were identified. 7 articles in the latter group correlated metrics from all three categories concurrently.

CONCLUSIONS

Protocol optimisation should be fine-tuned to the level of the individual patient and particular clinical query. This would require a judicious choice of metrics from each of the three categories. It is suggested that, for increased utility in clinical practice, more future optimisation studies be clinical task based and involve the three categories of metrics concurrently.

Ultra-low-dose CT vs. chest X-ray in non-traumatic emergency department patients - a prospective randomised crossover cohort trial

Background

Ultra-low-dose CT (ULDCT) examinations of the chest at only twice the radiation dose of a chest X-ray (CXR) now offer a valuable imaging alternative to CXR. This trial prospectively compares ULDCT and CXR for the detection rate of diagnoses and their clinical relevance in a low-prevalence cohort of non-traumatic emergency department patients.

Methods

In this prospective crossover cohort trial, 294 non-traumatic emergency department patients with a clinically indicated CXR were included between May 2nd and November 26th of 2019 (www.clinicaltrials.gov: NCT03922516). All participants received both CXR and ULDCT, and were randomized into two arms with inverse reporting order. The detection rate of CXR was calculated from 'arm CXR' (n = 147; CXR first), and of ULDCT from 'arm ULDCT' (n = 147; ULDCT first). Additional information reported by the second exam in each arm was documented. From all available clinical and imaging data, expert radiologists and emergency physicians built a compound reference standard, including radiologically undetectable diagnoses, and assigned each finding to one of five clinical relevance categories for the respective patient.

Findings

Detection rates for main diagnoses by CXR and ULDCT (mean effective dose: 0.22 mSv) were 9.1% (CI [5.2, 15.5]; 11/121) and 20.1% (CI [14.2, 27.7]; 27/134; P = 0.016), respectively. As an additional imaging modality, ULDCT added 9.1% (CI [5.2, 15.5]; 11/121) of main diagnoses to prior CXRs, whereas CXRs did not add a single main diagnosis (0/134; P < 0.001). Notably, ULDCT also offered higher detection rates than CXR for all other clinical relevance categories, including findings clinically irrelevant for the respective emergency department visit with 78.5% (CI [74.0, 82.5]; 278/354) vs. 16.2% (CI [12.7, 20.3]; 58/359) as a primary modality and 68.2% (CI [63.3, 72.8]; 245/359) vs. 2.5% (CI [1.3, 4.7]; 9/354) as an additional imaging modality.

Interpretation

In non-traumatic emergency department patients, ULDCT of the chest offered more than twice the detection rate for main diagnoses compared to CXR.

Funding

The Department of Biomedical Imaging and Image-guided Therapy of Medical University of Vienna received funding from Siemens Healthineers (Erlangen, Germany) to employ two research assistants for one year.

Reducing the radiation dose of pediatric paranasal sinus CT using an ultralow tube voltage (70 kVp) combined with iterative reconstruction: Feasibility and image quality

BACKGROUND

As the gold standard for imaging sinus disease, the main disadvantage of computed tomography (CT) of the pediatric paranasal sinus is radiation exposure. Because of this, 1 protocol for CT should reduce radiation dose while maintaining image quality. The aim of this study is to evaluate the image quality of dose-reduced paranasal sinus computed tomography (CT) using an ultralow tube voltage (70 kVp) combined with iterative reconstruction (IR) in children.

METHODS

CT scans of the paranasal sinus were performed using different protocols [70 kVp protocols with IR, Group A, n = 80; 80 kVp protocols with a filtered back projection algorithm, Group B, n = 80] in 160 pediatric patients. Then, the volume-weighted CT dose index, dose-length product, and effective dose were estimated. Image noise, the signal-to-noise ratio and the diagnostic image quality were also evaluated.

RESULTS

For the radiation dose, the volume-weighted CT dose index, dose-length product and effective dose values were significantly lower for the 70 kVp protocols than for the 80 kVp protocols (P < .001). Compared with the 80 kVp protocols, the 70 kVp protocols had significantly higher levels of image noise (P = .001) and a lower signal-to-noise ratio (P = .002). No significant difference in the overall subjective image quality grades was observed between these 2 groups (P = .098).

CONCLUSION

The ultralow tube voltage (70 kVp) technique combined with IR enabled a significant dose reduction in CT examinations performed in the pediatric paranasal sinus while maintaining diagnostic image quality with clinically acceptable image noise.

Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT

OBJECTIVE. The objective of this study was to compare image quality and clinically significant lesion detection on deep learning reconstruction (DLR) and iterative reconstruction (IR) images of submillisievert chest and abdominopelvic CT. MATERIALS AND METHODS. Our prospective multiinstitutional study included 59 adult patients (33 women, 26 men; mean age ± SD, 65 ± 12 years old; mean body mass index [weight in kilograms divided by the square of height in meters] = 27 ± 5) who underwent routine chest (n = 22; 16 women, six men) and abdominopelvic (n = 37; 17 women, 20 men) CT on a 640-MDCT scanner (Aquilion ONE, Canon Medical Systems). All patients gave written informed consent for the acquisition of low-dose (LD) CT (LDCT) after a clinically indicated standard-dose (SD) CT (SDCT). The SDCT series (120 kVp, 164-644 mA) were reconstructed with interactive reconstruction (IR) (adaptive iterative dose reduction [AIDR] 3D, Canon Medical Systems), and the LDCT (100 kVp, 120 kVp; 30-50 mA) were reconstructed with filtered back-projection (FBP), IR (AIDR 3D and forward-projected model-based iterative reconstruction solution [FIRST], Canon Medical Systems), and deep learning reconstruction (DLR) (Advanced Intelligent Clear-IQ Engine [AiCE], Canon Medical Systems). Four subspecialty-trained radiologists first read all LD image sets and then compared them side-by-side with SD AIDR 3D images in an independent, randomized, and blinded fashion. Subspecialty radiologists assessed image quality of LDCT images on a 3-point scale (1 = unacceptable, 2 = suboptimal, 3 = optimal). Descriptive statistics were obtained, and the Wilcoxon sign rank test was performed. RESULTS. Mean volume CT dose index and dose-length product for LDCT (2.1 ± 0.8 mGy, 49 ± 13mGy·cm) were lower than those for SDCT (13 ± 4.4 mGy, 567 ± 249 mGy·cm) (p < 0.0001). All 31 clinically significant abdominal lesions were seen on SD AIDR 3D and LD DLR images. Twenty-five, 18, and seven lesions were detected on LD AIDR 3D, LD FIRST, and LD FBP images, respectively. All 39 pulmonary nodules detected on SD AIDR 3D images were also noted on LD DLR images. LD DLR images were deemed acceptable for interpretation in 97% (35/37) of abdominal and 95-100% (21-22/22) of chest LDCT studies (p = 0.2-0.99). The LD FIRST, LD AIDR 3D, and LD FBP images had inferior image quality compared with SD AIDR 3D images (p < 0.0001). CONCLUSION. At submillisievert chest and abdominopelvic CT doses, DLR enables image quality and lesion detection superior to commercial IR and FBP images.

Thorax CT Dose Reduction Based on Patient Features: Effect of Patient Characteristics on Image Quality and Effective Dose

Computed tomography (CT) radiation dose reduction is vital without compromising image quality. The aim was to determine the effects of patient characteristics on the received radiation dose and image quality in chest CT examinations and to be able to predict dose and image quality prior to scanning. Consecutive 230 patients underwent routine chest CT examinations were included. CT examination and patients input parameters were recorded for each patient. The effect of patients' demographics/anthropometrics on received dose and image quality was investigated by linear regression analysis. All parameters were evaluated using an artificial neural network (ANN). Of all parameters, patient demographics/anthropometrics were found to be 98% effective in calculating dose reduction. Using ANN on 60 new patients was more than 90% accurate for output parameters and 91% for image quality. Patient characteristics have a significant impact on radiation dose and image quality. Dose and image quality can be determined before CT. This will allow setting the most appropriate scanning parameters before the CT scan.

Liver Extraction Using Residual Convolution Neural Networks From Low-Dose CT Images

An efficient and precise liver extraction from computed tomography (CT) images is a crucial step for computer-aided hepatic diseases diagnosis and treatment. Considering the possible risk to patient's health due to X-ray radiation of repetitive CT examination, low-dose CT (LDCT) is an effective solution for medical imaging. However, inhomogeneous appearances and indistinct boundaries due to additional noise and streaks artifacts in LDCT images often make it a challenging task. This study aims to extract a liver model from LDCT images for facilitating medical expert in surgical planning and post-operative assessment along with low radiation risk to the patient. Our method carried out liver extraction by employing residual convolutional neural networks (LER-CN), which is further refined by noise removal and structure preservation components. After patch-based training, our LER-CN shows a competitive performance relative to state-of-the-art methods for both clinical and publicly available MICCAI Sliver07 datasets. We have proposed training and learning algorithms for LER-CN based on back propagation gradient descent. We have evaluated our method on 150 abdominal CT scans for liver extraction. LER-CN achieves dice similarity coefficient up to 96.5[Formula: see text], decreased volumetric overlap error up to 4.30[Formula: see text], and average symmetric surface distance less than 1.4 [Formula: see text]. These findings have shown that LER-CN is a favorable method for medical applications with high efficiency allowing low radiation risk to patients.

Iterative Reconstructions in Reduced-Dose CT: Which Type Ensures Diagnostic Image Quality in Young Oncology Patients?

RATIONALE AND OBJECTIVES

To compare adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) algorithms for reduced-dose computed tomography (CT).

MATERIALS AND METHODS

Forty-four young oncology patients (mean age 30 ± 9 years) were included. After routine thoraco-abdominal CT (dose 100%, average CTDI_vol 9.1 ± 2.4 mGy, range 4.4-16.9 mGy), follow-up CT was acquired at 50% (average CTDI_vol 4.5 ± 1.2 mGy, range 2.2-8.4 mGy) in 29 patients additionally at 20% dose (average CTDI_vol 1.9 ± 0.5 mGy, range 0.9-3.4 mGy). Each reduced-dose CT was reconstructed using both ASIR and MBIR. Four radiologists (two juniors and two seniors) blinded to dose and technique read each set of CT images regarding objective and subjective image qualities (high- or low-contrast structures), subjective noise or pixilated appearance, diagnostic confidence, and lesion detection.

RESULTS

At all dose levels, objective image noise was significantly lower with MBIR than with ASIR (P < 0.001). The subjective image quality for low-contrast structures was significantly higher with MBIR than with ASIR (P < 0.001). Reduced-dose abdominal CT images of patients with higher body mass index (BMI) were read with significantly higher diagnostic confidence than images of slimmer patients (P < 0.001) and had higher subjective image quality, regardless of technique. Although MBIR images appeared significantly more pixilated than ASIR images, they were read with higher diagnostic confidence, especially by juniors (P < 0.001).

CONCLUSIONS

Reduced-dose CT during the follow-up of young oncology patients should be reconstructed with MBIR to ensure diagnostic quality. Elevated body mass index does not hamper the quality of reduced-dose CT.

Image quality of virtual monochromatic images obtained using 320-detector row CT: A phantom study evaluating the effects of iterative reconstruction and body size

OBJECTIVES

To compare the image quality between virtual monochromatic spectral (VMS) images obtained using 320-row detector CT and polychromatic 120-kVp images reconstructed with or without iterative reconstruction using various phantom sizes.

MATERIALS AND METHODS

Torso phantoms simulating three patient sizes and containing four syringes filled with water or different contrast media (5, 10, 15mgI/mL15mgI/ml) were used. The phantoms were scanned using dual-energy (80/135-kVp) and single-energy (120-kVp) protocols at different settings (20mGy, 12mGy, and 6mGy). VMS images were generated at 1-keV intervals (range, 35-135keV). Both the VMS images and the single-energy 120-kVp images were reconstructed using filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR-3D). The signal-to-noise ratio (SNR), and the contrast-to-noise ratio (CNR) were assessed.

RESULTS

Using FBP reconstruction, the SNR and CNR of the VMS images were lower than or similar to those of the 120-kVp images for most dose settings. Using AIDR-3D reconstruction, however, the 70-keV VMS images had higher SNRs and CNRs than the 120-kVp images at most settings.

CONCLUSIONS

The image quality of VMS images with FBP reconstruction tended to be lower than that of the 120-kVp images. With the use of AIDR-3D, however, approximately 70-keV VMS images had a higher image quality than the 120-kVp images.

256 Slice Multi-detector Computed Tomography Thoracic Aorta Computed Tomography Angiography: Improved Luminal Opacification Using a Patient-Specific Contrast Protocol and Caudocranial Scan Acquisition

CLINICAL RELEVANCE STATEMENT

Caudocranial scan direction and contrast injection timing based on measured patient vessel dynamics can significantly improve arterial and aneurysmal opacification and reduce both contrast and radiation dose in the assessment of thoracic aortic aneurysms (TAA) using helical thoracic computed tomography angiography (CTA).

OBJECTIVES

To investigate opacification of the thoracic aorta and TAA using a caudocranial scan direction and a patient-specific contrast protocol.

MATERIALS AND METHODS

Thoracic aortic CTA was performed in 160 consecutive patients with suspected TAA using a 256-slice computed tomography scanner and a dual barrel contrast injector. Patients were subjected in equal numbers to one of two contrast protocols. Patient age and sex were equally distributed across both groups. Protocol A, the department's standard protocol, consisted of a craniocaudal scan direction with 100 mL of contrast, intravenously injected at a flow rate of 4.5 mL/s. Protocol B involved a caudocranial scan direction and a novel contrast formula based on patient cardiovascular dynamics, followed by 100 mL of saline at 4.5 mL/s. Each scan acquisition comprised of 120 kVp, 200 mA with modulation, temporal resolution 0.27 seconds, and pitch 0.889:1. The dose length product was measured between each protocol and data generated were compared using Mann-Whitney U nonparametric statistics. Receiver operating characteristic analysis, visual grading characteristic (VGC), and κ analyses were performed.

RESULTS

Mean opacification in the thoracic aorta and aneurysm measured was 24 % and 55%, respectively. The mean contrast volume was significantly lower in protocol B (73 ± 10 mL) compared with A (100 ± 1 mL) (P<0.001). The contrast-to-noise ratio demonstrated significant differences between the protocols (protocol A, 18.2 ± 12.9; protocol B, 29.7 ± 0.61; P < 0.003). Mean effective dose in protocol B (2.6 ± 0.4 mSv) was reduced by 19% compared with A (3.2 ± 0.8 mSv) (P < 0.004). Aneurysmal detectability demonstrated significant increases by receiver operating characteristic and visual grading characteristic analysis for protocol B compared with A (P < 0.02), and reader agreement increased from poor to excellent.

CONCLUSIONS

Significant increase in the visualization of TAAs following a caudocranial scan direction during helical thoracic CTA can be achieved using low-contrast volume based on patient-specific contrast formula.

Technical Pitfalls and Limitations of SPECT/CT

The synergy of functional and anatomic information in hybrid systems has undoubtedly enhanced the diagnostic potential of radionuclide imaging in recent years, contributing to the advancement of SPECT/CT in clinical practice. Since the introduction of commercial SPECT/CT in the late 1990 s, the field has seen rapid expansion and development toward multidetector CT subsystems, establishing the role of SPECT/CT as a routine imaging tool. It is, however, important to discuss possible challenges and technical limitations of such systems and how these influence imaging outcomes. In particular, the issues of patient motion and spatial misalignment of the SPECT and CT modalities, data corrections such as those for photon attenuation, and the choice of CT acquisition protocols in relation to radiation exposure are discussed in the article.

CT restaging of testicular germ cell tumors: The incidence of isolated pelvic metastases

PURPOSE

We determined the incidence of isolated pelvic metastases at restaging computed tomography (CT) in patients with testicular germ cell tumors to consider if imaging the pelvis could be omitted.

METHODS

After receiving IRB approval for this HIPAA-compliant retrospective study, medical records of 560 men (mean age 32.8) with 583 testicular germ cell tumors who underwent 3683 restaging CT scans of the abdomen and pelvis were reviewed to determine the proportion of patients with metastatic disease in the pelvis alone, as verified by histology or by resolution after therapy. Chi-square statistical analysis tested the association between factors currently thought to predispose patients to pelvic metastases. Patients were also categorized by clinical stage, tumor histology, and initial treatment.

RESULTS

Isolated pelvic metastases were detected in nine (1.6%) of 560 men. Neither bulky abdominal disease (p=0.85) nor extratesticular invasion by the primary tumor (p=0.37) were statistically significant in predicting which patients were more likely to have isolated pelvic metastases. Among the nine patients with isolated pelvic recurrence, only three (0.7%) of 408 men with no known pelvic disease at initial staging and no tumor marker elevation at restaging had isolated pelvic metastases. Isolated pelvic recurrence was not statistically different when analyzed by initial stage and treatment.

CONCLUSION

The incidence of isolated pelvic metastases in testicular germ cell tumors at restaging CT is low, but no group of patients was found to be without risk. Therefore, given the small, if any, risk of radiation-induced harm, the decision about whether to include routine pelvic CT in surveillance protocols should be individualized.

Multicentre chest computed tomography standardisation in children and adolescents with cystic fibrosis: the way forward

Progressive cystic fibrosis (CF) lung disease is the main cause of mortality in CF patients. CF lung disease starts in early childhood. With current standards of care, respiratory function remains largely normal in children and more sensitive outcome measures are needed to monitor early CF lung disease. Chest CT is currently the most sensitive imaging modality to monitor pulmonary structural changes in children and adolescents with CF. To quantify structural lung disease reliably among multiple centres, standardisation of chest CT protocols is needed. SCIFI CF (Standardised Chest Imaging Framework for Interventions and Personalised Medicine in CF) was founded to characterise chest CT image quality and radiation doses among 16 participating European CF centres in 10 different countries. We aimed to optimise CT protocols in children and adolescents among several CF centres. A large variety was found in CT protocols, image quality and radiation dose usage among the centres. However, the performance of all CT scanners was found to be very similar, when taking spatial resolution and radiation dose into account. We conclude that multicentre standardisation of chest CT in children and adolescents with CF can be achieved for future clinical trials.

Radiation Dose Survey for Common Computed Tomography Exams: 2013 British Columbia Results

In 2013 Health Canada conducted a national survey of computed tomography (CT) radiation usage. We analysed contributions from all 7 public health authorities in the province of British Columbia, which covered scanner age, number of slices, and common adult protocols (≥19 years: 70 ± 20 kg, head, chest, abdomen/pelvis, and trunk). Patient doses were recorded for common protocols. Diagnostic reference levels (DRLs) was calculated using scanner data with >10 patient doses recorded for each protocol. Data was analysed based on image reconstruction (filtered backprojection vs iterative reconstruction [IR] vs IR available but not in use). Provincial response was 92%, with 59 of 64 CT data used for analysis. The average scanner age was 5.5 years old, with 39% of scanners installed between 2008-2013; 78.5% of scanners were multislice (>64 slices), and 44% of scanners had IR available. Overall British Columbia DRLs were: head = 1305, chest = 529, abdomen/pelvis = 819, and trunk = 1225. DRLs were consistent with Health Canada recommendations and other Canadian published values, but above international standards. For sites with IR available, less than 50% used this technology routinely for head, chest and trunk exams. Overall, use of IR reduced radiation usage between 11%-32% compared to filtered backprojection, while sites using IR vs IR available used 30%/43% less radiation for head/chest exams ( P < .05). No significant difference was observed for abdomen/pelvis exams ( P = .385). With the fast pace of CT technical advancement, DRLs should reflect the technology used, instead of just globally applied to anatomical regions. Federal guidelines should be updated at a higher frequency to reflect new technology. In addition, new technologies must be utilised to optimize image quality vs radiation usage.

Ultra-low dose abdominal MDCT: using a knowledge-based Iterative Model Reconstruction technique for substantial dose reduction in a prospective clinical study

PURPOSE

To assess lesion detection and image quality parameters of a knowledge-based Iterative Model Reconstruction (IMR) in reduced dose (RD) abdominal CT examinations.

MATERIALS AND METHODS

This IRB-approved prospective study included 82 abdominal CT examinations performed for 41 consecutive patients (mean age, 62 ± 12 years; F:M 28:13) who underwent a RD CT (SSDE, 1.5 mGy ± 0.4 [∼ 0.9 mSv] at 120 kV with 17-20 mAs/slice) immediately after their standard dose (SD) CT exam (10 mGy ± 3 [∼ 6 mSv] at 120 kV with automatic exposure control) on 256 MDCT (iCT, Philips Healthcare). SD data were reconstructed using filtered back projection (FBP). RD data were reconstructed with FBP and IMR. Four radiologists used a five-point scale (1=image quality better than SD CT to 5=image quality unacceptable) to assess both subjective image quality and artifacts. Lesions were first detected on RD FBP images. RD IMR and RD FBP images were then compared side-by-side to SD-FBP images in an independent, randomized and blinded fashion. Friedman's test and intraclass correlation coefficient were used for data analysis. Objective measurements included image noise and attenuation as well as noise spectral density (NSD) curves to assess the noise in frequency domain were obtained. In addition, a low-contrast phantom study was performed.

RESULTS

All true lesions (ranging from 32 to 55) on SD FBP images were detected on RD IMR images across all patients. RD FBP images were unacceptable for subjective image quality. Subjective ratings showed acceptable image quality for IMR for organ margins, soft-tissue structures, and retroperitoneal lymphadenopathy, compared to RD FBP in patients with a BMI ≤ 25 kg/m(2) (median-range, 2-3). Irrespective of patient BMI, subjective ratings for hepatic/renal cysts, stones and colonic diverticula were significantly better with RD IMR images (P<0.01). Objective image noise for RD FBP was 57-66% higher, and for RD IMR was 8-56% lower than that for SD-FBP (P<0.01). NSD showed significantly lower noise in the frequency domain with IMR in all patients compared to FBP.

CONCLUSION

IMR considerably improved both objective and subjective image quality parameters of RD abdominal CT images compared to FBP in patients with BMI less than or equal to 25 kg/m(2).