Investigative Radiology最新文献

Objectives: The aim of this study was to assess the diagnostic value and accuracy of a deep learning (DL)-accelerated fluid attenuated inversion recovery (FLAIR) sequence with fat saturation (FS) in patients with inflammatory synovitis of the knee.

Materials and methods: Patients with suspected knee synovitis were retrospectively included between January and September 2023. All patients underwent a 3 T knee magnetic resonance imaging including a DL-accelerated noncontrast FLAIR FS sequence (acquisition time: 1 minute 38 seconds) and a contrast-enhanced (CE) T1-weighted FS sequence (acquisition time: 4 minutes 50 seconds), which served as reference standard. All knees were scored by 2 radiologists using the semiquantitative modified knee synovitis score, effusion synovitis score, and Hoffa inflammation score. Diagnostic confidence, image quality, and image artifacts were rated on separate Likert scales. Wilcoxon signed rank test was used to compare the semiquantitative scores. Interreader and intrareader reproducibility were calculated using Cohen κ.

Results: Fifty-five patients (mean age, 52 ± 17 years; 28 females) were included in the study. Twenty-seven patients (49%) had mild to moderate synovitis (synovitis score 6-13), and 17 patients (31%) had severe synovitis (synovitis score >14). No signs of synovitis were detected in 11 patients (20%) (synovitis score <5). Semiquantitative assessment of the whole knee synovitis score showed no significant difference between the DL-accelerated FLAIR sequence and the CE T1-weighted sequence (mean FLAIR score: 10.69 ± 8.83, T1 turbo spin-echo FS: 10.74 ± 10.32; P = 0.521). Both interreader and intrareader reproducibility were excellent (range Cohen κ [0.82-0.96]).

Conclusions: Assessment of inflammatory knee synovitis using a DL-accelerated noncontrast FLAIR FS sequence was feasible and equivalent to CE T1-weighted FS imaging.

Objectives: The aim of this study was to compare the effectiveness and clinical utility of virtual monoenergetic image (VMI) reconstructions in computed tomography (CT) scans with and without tin prefiltration on a photon-counting detector (PCD) CT system to reduce metal implant artifacts in the postoperative ankle.

Materials and methods: This retrospective study included patients with internal fixation of the ankle scanned with and without tin prefiltration (Sn) on a PCD CT scanner between March and October 2023. Virtual monoenergetic images between 60 and 190 keV were reconstructed with a 10-keV increment in a bone kernel for both acquisitions (VMI Sn and VMI Std , respectively). Noise measurements assessed artifact reduction in the most prominent near-metal image distortions and were compared between acquisitions modes as well as between polychromatic images and VMIs. Three readers assessed the visibility of osseous healing along with interpretability and artifact extent for 5 reconstruction levels.

Results: A total of 48 patients (21 females, 27 males; mean age, 55.1 ± 19.4 years) were included in this study. Tin-prefiltered acquisitions (n = 30) had a lower artifact level for polychromatic images and VMIs compared with non-tin-prefiltered acquisitions (n = 18; P ≤ 0.043). A significant reduction of metal artifacts was observed for VMI Sn ≥120 keV compared with polychromatic images (hyperdense artifacts: 40.2 HU [interquartile range (IQR) 39.8] vs 14.0 HU [IQR 11.1]; P ≤ 0.01 and hypodense artifacts: 91.2 HU [IQR 82.4] vs 29.7 HU [IQR 39.6]; P ≤ 0.001). For VMI Std , this applied to reconstructions ≥100 keV (hyperdense artifacts: 57.7 HU [IQR 33.4] vs 19.4 HU [IQR 27.6]; P ≤ 0.001 and hypodense artifacts: 106.9 HU [IQR 76.1] vs 57.4 HU [IQR 55.7]; P ≤ 0.021). For visibility of osseous healing, VMI Sn at 120 keV yielded higher ratings compared with polychromatic images ( P ≤ 0.001), whereas image interpretability was rated better ( P = 0.023), and artifact extent was rated lower ( P ≤ 0.001) compared with polychromatic images.

Conclusions: Tin-prefiltered VMI at 120 keV showed a significant reduction in metal artifacts compared with polychromatic images, whereas visibility of osseous healing and image interpretability was improved. Therefore, tin-prefiltration PCD CT with VMI reconstructions may be a helpful complement to postsurgical CT imaging of the ankle in patients with metal implants.

Objectives: The aim of this study was to evaluate the optimal energy level of virtual monoenergetic images (VMIs) from photon-counting detector computed tomography (CT) for the detection of liver lesions as a function of phantom size and radiation dose.

Materials and methods: An anthropomorphic abdominal phantom with liver parenchyma and lesions was imaged on a dual-source photon-counting detector CT at 120 kVp. Five hypoattenuating lesions with a lesion-to-background contrast difference of -30 HU and -45 HU and 3 hyperattenuating lesions with +30 HU and +90 HU were used. The lesion diameter was 5-10 mm. Rings of fat-equivalent material were added to emulate medium- or large-sized patients. The medium size was imaged at a volume CT dose index of 5, 2.5, and 1.25 mGy and the large size at 5 and 2.5 mGy, respectively. Each setup was imaged 10 times. For each setup, VMIs from 40 to 80 keV at 5 keV increments were reconstructed with quantum iterative reconstruction at a strength level of 4 (QIR-4). Lesion detectability was measured as area under the receiver operating curve (AUC) using a channelized Hotelling model observer with 10 dense differences of Gaussian channels.

Results: Overall, highest detectability was found at 65 and 70 keV for both hypoattenuating and hyperattenuating lesions in the medium and large phantom independent of radiation dose (AUC range, 0.91-1.0 for the medium and 0.94-0.99 for the large phantom, respectively). The lowest detectability was found at 40 keV irrespective of the radiation dose and phantom size (AUC range, 0.78-0.99). A more pronounced reduction in detectability was apparent at 40-50 keV as compared with 65-75 keV when radiation dose was decreased. At equal radiation dose, detection as a function of VMI energy differed stronger for the large size as compared with the medium-sized phantom (12% vs 6%).

Conclusions: Detectability of hypoattenuating and hyperattenuating liver lesions differed between VMI energies for different phantom sizes and radiation doses. Virtual monoenergetic images at 65 and 70 keV yielded highest detectability independent of phantom size and radiation dose.

Objectives: The Centers for Medicare and Medicaid Services funded the development of a computed tomography (CT) quality measure for use in pay-for-performance programs, which balances automated assessments of radiation dose with image quality to incentivize dose reduction without compromising the diagnostic utility of the tests. However, no existing quantitative method for assessing CT image quality has been validated against radiologists' image quality assessments on a large number of CT examinations. Thus to develop an automated measure of image quality, we tested the relationship between radiologists' subjective ratings of image quality with measurements of radiation dose and image noise.

Materials and methods: Board-certified, posttraining, clinically active radiologists rated the image quality of 200 diagnostic CT examinations from a set of 734, representing 14 CT categories. Examinations with significant distractions, motion, or artifact were excluded. Radiologists rated diagnostic image quality as excellent, adequate, marginally acceptable, or poor; the latter 2 were considered unacceptable for rendering diagnoses. We quantified the relationship between ratings and image noise and radiation dose, by category, by analyzing the odds of an acceptable rating per standard deviation (SD) increase in noise or geometric SD (gSD) in dose.

Results: One hundred twenty-five radiologists contributed 24,800 ratings. Most (89%) were acceptable. The odds of an examination being rated acceptable statistically significantly increased per gSD increase in dose and decreased per SD increase in noise for most categories, including routine dose head, chest, and abdomen-pelvis, which together comprise 60% of examinations performed in routine practice. For routine dose abdomen-pelvis, the most common category, each gSD increase in dose raised the odds of an acceptable rating (2.33; 95% confidence interval, 1.98-3.24), whereas each SD increase in noise decreased the odds (0.90; 0.79-0.99). For only 2 CT categories, high-dose head and neck/cervical spine, neither dose nor noise was associated with ratings.

Conclusions: Radiation dose and image noise correlate with radiologists' image quality assessments for most CT categories, making them suitable as automated metrics in quality programs incentivizing reduction of excessive radiation doses.

Background: Neoadjuvant therapy regimens have significantly improved the prognosis of GEJ (gastroesophageal junction) cancer; however, there are a significant percentage of patients who benefit from earlier resection or adapted therapy regimens, and the true response rate can only be determined histopathologically. Methods that allow preoperative assessment of response are lacking.

Purpose: The purpose of this retrospective study is to assess the potential of pretherapeutic and posttherapeutic spectral CT iodine density (IoD) in predicting histopathological response to neoadjuvant chemotherapy in patients diagnosed with adenocarcinoma of the GEJ.

Methods: In this retrospective cohort study, a total of 62 patients with GEJ carcinoma were studied. Patients received a multiphasic CT scan at diagnosis and preoperatively. Iodine-density maps were generated based on spectral CT data. All tumors were histopathologically analyzed, and the tumor regression grade (TRG) according to Becker et al ( Cancer . 2003;98:1521-1530) was determined. Two experienced radiologists blindly placed 5 defined ROIs in the tumor region of highest density, and the maximum value was used for further analysis. Iodine density was normalized to the aortic iodine uptake. In addition, tumor response was assessed according to standard RECIST measurement. After assessing interrater reliability, the correlation of IoD values with treatment response and with histopathologic TRG was evaluated.

Results: The normalized ΔIoD (IoD at diagnosis - IoD after neoadjuvant treatment) and the normalized IoD after neoadjuvant treatment correlated significantly with the TRG. For the detection of responders and nonresponders, the receiver operating characteristic (ROC) curve for normalized ΔIoD yielded the highest area under the curve of 0.95 and achieved a sensitivity and specificity of 92.3% and 92.1%, respectively. Iodine density after neoadjuvant treatment achieved an area under the curve of 0.88 and a sensitivity and specificity of 86.8% and 84.6%, respectively (cutoff, 0.266). Iodine density at diagnosis and RECIST did not provide information to distinguish responders from nonresponders. Using the cutoff value for IoD after neoadjuvant treatment, a reliable classification of responders and nonresponders was achieved for both readers in a test set of 11 patients. Intraclass correlation coefficient revealed excellent interrater reliability (intraclass correlation coefficient, >0.9). Lastly, using the cutoff value for normalized ΔIoD as a definition for treatment response, a significantly longer survival of responders was shown.

Conclusions: Changes in IoD after neoadjuvant treatment of GEJ cancer may be a potential surrogate for therapy response.

Objectives: This project aims to model an optimal scanning environment for breast magnetic resonance imaging (MRI) screening based on real-life data to identify to what extent the logistics of breast MRI can be optimized.

Materials and methods: A novel concept for a breast MRI screening facility was developed considering layout of the building, workflow steps, used resources, and MRI protocols. The envisioned screening facility is person centered and aims for an efficient workflow-oriented design. Real-life data, collected from existing breast MRI screening workflows, during 62 scans in 3 different hospitals, were imported into a 3D simulation software for designing and testing new concepts. The model provided several realistic, virtual, logistical pathways for MRI screening and their outcome measures: throughput, waiting times, and other relevant variables.

Results: The total average appointment time in the baseline scenario was 25:54 minutes, with 19:06 minutes of MRI room occupation. Simulated improvements consisted of optimizing processes and resources, facility layout, and scanning protocol. In the simulation, time spent in the MRI room was reduced by introducing an optimized facility layout, dockable tables, and adoption of an abbreviated MRI scanning protocol. The total average appointment time was reduced to 19:36 minutes, and in this scenario, the MRI room was occupied for 06:21 minutes. In the most promising scenario, screening of about 68 people per day (10 hours) on a single MRI scanner could be feasible, compared with 36 people per day in the baseline scenario.

Conclusions: This study suggests that by optimizing workflow MRI for breast screening total appointment duration and MRI occupation can be reduced. A throughput of up to 6 people per hour may be achieved, compared with 3 people per hour in the current setup.

Objectives: The aim of this study was to introduce and evaluate a new metal artifact reduction framework (iMARv2) that addresses the drawbacks (residual artifacts after correction and user preferences for image quality) associated with the current clinically applied iMAR.

Materials and methods: A new iMARv2 has been introduced, combining the current iMAR with new modular components to remove residual metal artifacts after image correction. The postcorrection image impression is adjustable with user-selectable strength settings. Phantom scans from an energy-integrating and a photon-counting detector CT were used to assess image quality, including a Gammex phantom and anthropomorphic phantoms. In addition, 36 clinical cases (with metallic implants such as dental fillings, hip replacements, and spinal screws) were reconstructed and evaluated in a blinded and randomized reader study.

Results: The Gammex phantom showed lower HU errors compared with the uncorrected image at almost all iMAR and iMARv2 settings evaluated, with only minor differences between iMAR and the different iMARv2 settings. In addition, the anthropomorphic phantoms showed a trend toward lower errors with higher iMARv2 strength settings. On average, the iMARv2 strength 3 performed best of all the clinical reconstructions evaluated, with a significant increase in diagnostic confidence and decrease in artifacts. All hip and dental cases showed a significant increase in diagnostic confidence and decrease in artifact strength, and the improvements from iMARv2 in the dental cases were significant compared with iMAR. There were no significant improvements in the spine.

Conclusions: This work has introduced and evaluated a new method for metal artifact reduction and demonstrated its utility in routine clinical datasets. The greatest improvements were seen in dental fillings, where iMARv2 significantly improved image quality compared with conventional iMAR.