Journal of Computer Assisted Tomography最新文献

Objective: This study aimed to evaluate the image quality and visualization of hepatocellular carcinoma (HCC) on arterial phase computed tomography (CT) using the contrast enhancement (CE)-boost technique.

Methods: This retrospective study included 527 consecutive patients who underwent dynamic liver CT between June 2021 and February 2022. Quantitative and qualitative image analyses were performed on 486 patients after excluding 41 patients. HCC conspicuity was evaluated in 40 of the 486 patients with at least one HCC in the liver. Iodinated images obtained by subtracting nonenhanced images from arterial phase images were combined to generate CE-boost images. For quantitative image analysis, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured for the liver, pancreas, muscles, and aorta. For qualitative analysis, the overall image quality and noise were graded using a 3-point scale. Artifact, sharpness, and HCC lesion conspicuity were assessed using a 5-point scale. The paired-sample t test was used to compare quantitative measures, whereas the Wilcoxon signed-rank test was used to compare qualitative measures.

Results: The mean SNR and CNR of the aorta, liver, pancreas, and muscle were significantly higher, and the image noise was significantly lower in the CE-boost images than in the conventional images (P < 0.001). The mean CNR of HCC was also significantly higher in the CE-boost images than in the conventional images (P < 0.001). In the qualitative analysis, CE-boost images showed higher scores for HCC lesion conspicuity than conventional images (P < 0.001).

Conclusions: The overall image quality and visibility of HCC were improved using the CE-boost technique.

Objective: The purpose of this study was to compare radiation dose reduction capability for accurate liver tumor measurements of a computer-aided volumetry (CADv) software for filtered back projection (FBP), hybrid-type iterative reconstruction (IR), mode-based iterative reconstruction (MBIR), and deep learning reconstruction (DLR) at a phantom study.

Methods: A commercially available anthropomorphic abdominal phantom was scanned five times with a 320-detector row CT at 600 mA, 400 mA, 200 mA, and 100 mA and reconstructed by four methods. Signal-to-noise ratios (SNRs) of all lesions within the arterial and portal-venous phase inserts were calculated, and SNR of the lesion phantom was compared with that of all reconstruction methods by means of Tukey's honestly significant difference (HSD) test. Then, tumor volume (V) of each nodule was automatically measured using commercially available CADv software. To compare dose reduction capability for each reconstruction method at both phases, mean differences between measured V and standard references were compared by Tukey's honestly significant difference test among the four different reconstruction methods on CT obtained at each of the four tube currents.

Results: With each of the tube currents, SNRs for MBIR and DLR were significantly higher than those for FBP and hybrid-type IR (p < 0.05). At the arterial phase, the mean difference in V for the CT protocol obtained at 600 or 100 mA and reconstructed with DLR was significantly smaller than that for others (p < 0.05). At the portal-venous phase, the mean differences in V for the CT protocol obtained at 100 mA and reconstructed with hybrid-type IR, MBIR, and DLR were significantly smaller than that for FBP (p < 0.05).

Conclusions: Findings of our phantom study show that reconstruction method had influence on CADv merits for abdominal CT with not only standard but also reduced dose examinations and that DLR can potentially yield better image quality and CADv measurements than FBP, hybrid-type IR, or MBIR in this setting.

Abstract: Tumor-induced osteomalacia (TIO) is a rare paraneoplastic syndrome characterized by renal phosphate wasting and impaired bone mineralization secondary to secretion of fibroblast growth factor 23 (FGF23) from mesenchymal tumors (phosphaturic mesenchymal tumors, PMTs). PMTs have wide anatomical distribution but typically affect extremities and craniofacial bones. Diagnosis of TIO/PMT is often delayed, and a high index of suspicion is essential in patients with unexplained fractures, but many physicians lack familiarity with TIO/PMT and simply attribute fractures to the more common diagnosis of osteoporosis. We present 5 cases of TIO, with 4 having long histories of multiple insufficiency fractures prior to recognition of TIO and localization of a PMT. Four patients were treated surgically, while 1 preferred medical management. Two patients had lesions localized to the skull base, both of which showed marked hypervascularity on arterial spin label perfusion imaging. Thus, arterial spin label may not only help to localize these tumors, but may also be a helpful supplemental imaging finding in supporting this diagnosis. PMT should be considered in the differential diagnosis for hypervascular skull base masses, especially if the patient has any history of insufficiency fracture or imaging evidence of osteopenia, as early diagnosis of TIO can help prevent disabling complications.

Objective: Contrast-enhanced imaging, including magnetic resonance imaging and, more recently, contrast-enhanced digital mammography (CEM), is indicated for the precise diagnosis of invasive lobular carcinoma (ILC). The aim of our study was to further validate the use of CEM for evaluation of extent of disease in ILC cases, with digital breast tomosynthesis (DBT) as an adjunct.

Methods: A retrospective, institutional review board approved study was conducted in a tertiary medical center. All CEM examinations performed on ILC patients between 2017 and 2023 were reread by 2 dedicated breast radiologists. Clinical data and pathology reports were retrieved from electronic medical records. The longest diameter of the enhancing lesion was correlated to pathology findings. In addition, for each case, the readers provided brief commentary on the added value of DBT.

Results: Twenty-four CEM examinations were evaluated. The subjects in the study cohort were on average older than expected for ILC patients (74 vs 63 years) and were unable to undergo breast magnetic resonance imaging due to advanced age and comorbidities. Three subjects were treated with neoadjuvant therapy and thus were excluded from the correlation to pathology analysis. Enhancing lesions, ranging from 4-75 mm, strongly correlated to pathology results, with statistical significance. This was demonstrated for mass and nonmass lesions (r = 0.94, P < 0.001 and r = 0.99, P = 0.002, respectively). For most lesions (17/24, 71%), readers remarked that the addition of DBT allowed for improved characterization of lesion margins, mainly detecting architectural distortion.

Conclusions: When compared with the pathology findings, ILC was accurately diagnosed and assessed using CEM. The addition of DBT was reported by the interpreting radiologists as a valuable adjunct for margin analysis.

Objective: To evaluate whether the extracellular volume (ECV) fraction can be used to identify splenic involvement in lymphoma patients and whether it can be used to improve the diagnostic performance of conventional computed tomography (CT) in the diagnosis of splenic diffuse involvement.

Methods: Consecutive patients with newly diagnosed lymphoma who underwent abdomen contrast-enhanced CT and 18F-fluorodeoxyglucose positron emission tomography/CT for diagnosis or staging were retrospectively enrolled. Patients were divided into the splenic involvement (diffuse or focal) and noninvolvement groups. The ECV fraction was obtained in all patients. In the splenic diffuse involvement and noninvolvement groups, spleen vertical length (SVL) >13 cm and obliteration of normal heterogeneous enhancement of the spleen in arterial phase were recorded. Receiver operating characteristic curve was used to analyze the diagnostic performance, and area under the curve (AUC) comparison was performed using the Delong test.

Results: A total of 135 patients were included, 56 patients with splenic involvement (36 diffuse and 20 focal) and 79 patients with noninvolvement. Splenic involvement can be identified via the ECV fraction (AUC = 0.839). In distinguishing splenic diffuse involvement, the AUC of the ECV fraction was superior to the SVL >13 cm (0.788 vs 0.627, P = 0.007) and obliteration of normal heterogeneous enhancement of the spleen (0.788 vs 0.596, P = 0.001). The combination of ECV fraction and SVL >13 cm demonstrated superior diagnostic performance, with an AUC of 0.830, surpassing all other parameters.

Conclusion: The ECV fraction can be used to identify splenic involvement. The ECV fraction combined with SVL >13 cm is recommended for the prediction of splenic diffuse involvement.

Objectives: To investigate the diagnostic performance of Node Reporting and Data System (Node-RADS) combined with computed tomography (CT) radiomics for assessing nonenlargement regional lymph nodes in gastric cancer (GC).

Methods: Preoperative CT images were retrospectively collected from 376 pathologically confirmed of gastric adenocarcinoma from January 2019 to December 2023, with 605 lymph nodes included for analysis. They were divided into training (n = 362) and validation (n = 243) sets. Radiomics features were extracted from venous-phase, and the radiomics score was obtained. Clinical information, CT parameters, and Node-RADS classification were collected. A combined model was built using machine-learning approach and tested in validation set using receiver operating characteristic curve analysis. Further validation was conducted in different subgroups of lymph node short-axis diameter (SD) range.

Results: Node-RADS score, SD, maximum diameter of thickness of tumor, and radiomics were identified as the most predictive factors. The results demonstrated that the integrated model combining SD, maximum diameter of thickness of tumor, Node-RADS, and radiomics outperformed the model excluding radiomics, yielding an area under the receiver operating characteristic curve of 0.82 compared with 0.79, with a statistically significant difference (P < 0.001). Subgroup analysis based on different SDs of lymph nodes also revealed enhanced diagnostic accuracy when incorporating the radiomics score for the 4- to 7.9-mm subgroups, all P < 0.05. However, for the 8- to 9.9-mm subgroup, the combination of the radiomics did not significantly improve the prediction, with an area under the receiver operating characteristic curve of 0.85 versus 0.85, P = 0.877.

Conclusion: The integration of radiomics scores with Node-RADS assessments significantly enhances the accuracy of lymph node metastasis evaluation for GC. This combined model is particularly effective for lymph nodes with smaller standard deviations, yielding a marked improvement in diagnostic precision.

Clinical relevance statement: The findings of this study indicate that a composite model, which incorporates Node-RADS, radiomics features, and conventional parameters, may serve as an effective method for the assessment of nonenlarged lymph nodes in GC.

Objective: The aim of this study was to assess the effectiveness of a deep learning-based image contrast-boosting algorithm by enhancing the image quality of low-dose computed tomography pulmonary angiography at reduced iodine load.

Methods: This study included 179 patients who underwent low-dose computed tomography pulmonary angiography with a reduced iodine load using 64 mL of a 1:1 mixture of contrast medium from January 1 to June 30, 2023. For single-energy computed tomography, the noise index was set at 15.4 to maintain a CTDIvol of <2 mGy at 80 kVp, and for dual-energy computed tomography, fast kV-switching between 80 and 140 kVp was employed with a fixed tube current of 145 mA. Images were reconstructed by 50% adaptive statistical iterative reconstruction (AR50) and a commercially available deep learning image reconstruction (TrueFidelity) package at a high strength level (TFH). In addition, AR50 images were further processed using a deep learning-based contrast-boosting algorithm (AR50-CB). Quantitative and qualitative image qualities and numbers of involved vessels with thrombus at each pulmonary artery level were compared in the 3 image types using the Friedman test and Wilcoxon signed rank test.

Results: Five hundred thirty-seven reconstructed image datasets of 179 patients were analyzed. Quantitative image analysis showed AR50-CB (30.8 ± 10.0 and 28.1 ± 9.6, respectively) had significantly higher signal-to-noise ratio and contrast-to-noise ratio values than AR50 (20.2 ± 6.2 and 17.8 ± 6.2, respectively) (P < 0.001) or TFH (28.3 ± 8.3 and 24.9 ± 8.1, respectively) (P < 0.001). Qualitative image analysis showed that contrast enhancement and noise scores of AR50-CB were significantly greater than those of AR50 (P < 0.001) and that AR50-CB enhancement scores were significantly higher than TFH enhancement scores (P < 0.001). The number of subsegmental pulmonary arteries affected by thrombus detected was significantly greater for AR50-CB (30 for AR50, 30 for TFH, and 55 for AR50-CB, P < 0.001).

Conclusions: The use of a deep learning-based contrast-boosting algorithm improved image quality in terms of signal-to-noise ratio and contrast-to-noise ratio values and the detection of thrombi in subsegmental pulmonary arteries.

Objectives: We aimed to develop a predictive model based on textural features of noncontrast cardiac magnetic resonance (CMR) imaging for risk stratification toward adverse events in patients with cardiac amyloidosis (CA).

Methods: A cohort of 78 patients with CA was grouped into training (n = 54) and validation (n = 24) sets at a ratio of 7:3. A total of 275 textural features were extracted from the CMR images. MaZda and a support vector machine (SVM) were used for feature selection and model construction. An SVM model incorporating radiological and textural features was built to predict endpoint events by evaluating the area under the curve.

Results: In the entire cohort, 52 patients experienced major adverse cardiovascular events and 26 patients did not. By combining 2 radiological features and 8 texture features, extracted from cine and T2-weighted imaging images, the SVM model achieved area under the curves of the receiver operating characteristic and precision-recall curves of 0.930 and 0.962 in the training cohort and that of 0.867 and 0.941 in the validated cohort, respectively. The Kaplan-Meier curve of this SVM model criterion significantly stratified the CA outcomes (log-rank test, P < 0.0001).

Conclusions: The SVM model based on radiological and textural features derived from noncontrast CMR images can be a reliable biomarker for adverse events prognostication in patients with CA.

Objective: This study aimed to evaluate a vendor-specific correction software for apparent diffusion coefficient (ADC) bias due to gradient nonlinearity in breast diffusion-weighted magnetic resonance imaging using an ice-water phantom.

Methods: The phantom consists of 5 plastic tubes with a length of 100 mm and a diameter of 15 mm, filled with distilled water and immersed in an ice-water bath. Diffusion-weighted images were acquired by echo-planar imaging sequence on a 3.0-T scanner. ADC maps with and without correction were calculated using 4 b -values (0, 100, 600, and 800 s/mm 2 ). The mean ADCs were measured using a rectangular profile with 5 × 40 pixels in the anterior-posterior (AP) and a square region of interest with 5 × 5 pixels in the right-left (RL) and superior-inferior (SI) directions on the ADC map. ADC was compared with and without correction using a paired t test. Additionally, ADC of the ice-water phantom was measured at the magnet isocenter.

Results: ADC increased in the AP and RL directions and decreased in the SI direction with increasing distance from the isocenter before correction. After the correction, ADC at the off-center positions in the AP, RL, and SI directions was reduced to within 5% of the expected value. There were significant differences in the ADC at the off-center positions without and with correction ( P < 0.001); however, ADC at the magnet isocenter did not vary after correction (1.08 ± 0.02 × 10 -3 mm 2 /s).

Conclusions: The vendor-specific software corrected the ADC bias due to gradient nonlinearity at the off-center positions in the AP, RL, and SI directions. Therefore, the software will contribute to the accurate ADC assessment in breast DWI.

Purpose: The aim of the study is to assess the efficacy of computed tomography (CT) and positron emission tomography (PET)/CT findings in differentiating between cardiac sarcoma and cardiac hematologic neoplasms, which are rare but potentially lethal primary cardiac malignancies.

Materials and methods: We searched the electronic medical record for pathology-proven cases from 2012 to 2023, finding 69 patients (46 sarcomas, 23 cardiac hematologic neoplasms). Imaging features including tumor size, atrioventricular (AV) groove involvement, right coronary artery (RCA) encasement by 180°, pericardial effusion, lymphadenopathy, and metabolic activity on fluorodeoxyglucose PET were reviewed by a radiology fellow. Statistical analysis was performed using Fisher exact test and Wilcoxon test.

Results: Cardiac sarcoma patients were younger (median age 49 years) compared to patients with cardiac hematologic malignancies (66 years, P = 0.006). While tumor size and chamber involvement were similar between the 2 categories, hematologic malignancies exhibited a notable predilection for AV groove involvement (70% vs 43%, P = 0.04) and RCA encasement (52% vs 26%, P = 0.02). Pulmonary metastases were more frequent in sarcoma cases (33% vs 4%, P = 0.006). There was no significant difference in fluorodeoxyglucose uptake. Lymphadenopathy was similar between the 2 disease groups. A decision tree constructed using AV groove involvement and patient age achieved 75% accuracy in predicting the diagnosis of the mass.

Conclusions: Overall, there is a substantial overlap in imaging features of cardiac sarcomas and hematologic malignancies involving the heart. Involvement of the AV groove and RCA encasement can allow a radiologist to favor hematologic malignancy. Ultimately, biopsy is required to establish a diagnosis.