Acta radiologica最新文献

Background: SynthesiZed Improved Resolution and Concurrent nOise reductioN (ZIRCON) is a multi-kernel synthesis method that creates a single series of thin-slice computed tomography (CT) images displaying low noise and high spatial resolution, increasing reader efficiency and minimizing partial volume averaging.

Purpose: To compare the diagnostic performance of a single set of ZIRCON images to two routine clinical image series using conventional CT head and bone reconstruction kernels for diagnosing intracranial findings and fractures in patients with trauma or suspected acute neurologic deficit.

Material and methods: In total, 50 patients underwent clinically indicated head CT in the ER (15 normal, 35 abnormal cases). A non-reader neuroradiologist established the reference standard. Three neuroradiologists reviewed two routine clinical series (head and bone kernels) and a single ZIRCON series, detecting intracranial findings or fractures and rating confidence (0-100). Sensitivity, specificity, and jackknife free-response receiver operating characteristic (JAFROC) figure of merit (FOM) were compared (limit of non-inferiority: -0.10).

Results: ZIRCON and conventional images demonstrated comparable performance for fractures (sensitivity: 51.5% vs. 54.5%; specificity: 40.2% vs. 34.2%) and intracranial findings (sensitivity: 88.2% vs. 91.4%; specificity: 77.2% vs. 73.7%).The estimated difference of JAFROC FOM demonstrated ZIRCON non-inferiority for acute pathologies overall (0.003 [95% CI=-0.051-0.057]) and fractures (0.048 [95% CI=-0.050-0.145]) but not for intracranial findings alone (-0.024 [95% CI=-0.100-0.052]).

Conclusion: Thin-slice, low noise, and high spatial resolution images can be created to display intracranial findings and fractures replacing multiple images series in head CT with similar performance. Future studies in more patients and further algorithmic development are warranted.

Empirical evidence for radiomics predicting the malignant potential and Ki-67 expression in gastrointestinal stromal tumors (GISTs) is lacking. The aim of this review article was to explore the preoperative discriminative performance of radiomics in assessing the malignant potential, mitotic index, and Ki-67 expression levels of GISTs. We systematically searched PubMed, EMBASE, Web of Science, and the Cochrane Library. The search was conducted up to 30 September 2023. Quality assessment was performed using the Radiomics Quality Score (RQS). A total of 35 original studies were included in the analysis. Among them, 26 studies focused on determining malignant potential, three studies on mitotic index discrimination, and six studies on Ki-67 discrimination. In the validation set, the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of radiomics in the determination of high malignant potential were 0.74 (95% CI=0.69-0.78), 0.90 (95% CI=0.83-0.94), and 0.81 (95% CI=0.14-0.99), respectively. For moderately to highly malignant potential, the sensitivity, specificity, and AUC were 0.86 (95% CI=0.83-0.88), 0.73 (95% CI=0.67-0.78), and 0.88 (95% CI=0.27-0.99), respectively. Regarding the determination of high mitotic index, the sensitivity, specificity, and AUC of radiomics were 0.86 (95% CI=0.83-0.88), 0.73 (95% CI=0.67-0.78), and 0.88 (95% CI=0.27-0.99), respectively. When determining high Ki-67 expression, the combined sensitivity, specificity, and AUC were 0.74 (95% CI=0.65-0.81), 0.81 (95% CI=0.74-0.86), and 0.84 (95% CI=0.61-0.95), respectively. Radiomics demonstrates promising discriminative performance in the preoperative assessment of malignant potential, mitotic index, and Ki-67 expression levels in GISTs.

Background: Recent guidelines recommend direct patient observation, pressure monitoring, and sensor devices to prevent extravasation during contrast media (CM) injection. However, it is impractical in terms of time and cost to install sensors for all patients.

Purpose: To identify risk factors for CM extravasations during contrast-enhanced computed tomography (CECT) in a large population and to establish criteria for placing the sensor device on patients.

Material and methods: This retrospective study included 143,556 patients who underwent CECT at our hospital between April 2012 and July 2022. We performed multivariable logistic regression analysis between patients with (n = 350) and randomly selected patients without CM extravasation (n = 350). We investigated the percentage of patients with sensor devices and their sensitivity for detecting extravasation using receiver operating characteristic curve analysis.

Results: The extravasation rate was 0.27%. Multivariable logistic regression analysis showed that the injection rate (adjusted odds ratio [AOR] = 1.61, 95% confidence interval [CI] = 1.33-1.95: P <0.001), catheter gauge (AOR = 3.86, 95% CI = 1.92-7.76; P <0.001), the use of anticancer drugs (AOR = 1.81, 95% CI = 1.32-2.50; P <0.001), and existing catheters (AOR = 1.52, 95% CI = 1.10-2.11; P = 0.009) were significantly associated with extravasation. To achieve a sensitivity of 90%, 80%, 70%, 60%, and 50%, 80%, 65%, 50%, 40%, and 28% of all patients required the placement of a sensor device, respectively.

Conclusion: Sensitivity analysis established criteria for effective placing sensor devices.

Background: Distinguishing between tumor recurrence and pseudoprogression (PsP) in high-grade glioma postoperatively is challenging. This study aims to enhance this differentiation using a combination of intratumoral and peritumoral radiomics.

Purpose: To assess the effectiveness of intratumoral and peritumoral radiomics in improving the differentiation between high-grade glioma recurrence and pseudoprogression after surgery.

Material and methods: A total of 109 cases were randomly divided into training and validation sets, with 1316 features extracted from intratumoral and peritumoral volumes of interest (VOIs) on conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps. Feature selection was performed using the mRMR algorithm, resulting in intratumoral (100 features), peritumoral (100 features), and combined (200 features) subsets. Optimal features were then selected using PCC and RFE algorithms and modeled using LR, SVM, and LDA classifiers. Diagnostic performance was compared using area under the receiver operating characteristic curve (AUC), evaluated in the validation set. A nomogram was established using radscores from intratumoral, peritumoral, and combined models.

Results: The combined model, utilizing 14 optimal features (8 peritumoral, 6 intratumoral) and LR as the best classifier, outperformed the single intratumoral and peritumoral models. In the training set, the AUC values for the combined model, intratumoral model, and peritumoral model were 0.938, 0.921, and 0.847, respectively; in the validation set, the AUC values were 0.841, 0.755, and 0.705. The nomogram model demonstrated AUCs of 0.960 (training set) and 0.850 (validation set).

Conclusion: The combination of intratumoral and peritumoral radiomics is effective in distinguishing high-grade glioma recurrence from pseudoprogression after surgery.

Background: Fracture healing complications remain a major problem in trauma monitoring. An open wedge osteotomy of the distal radius provides a unique way of evaluating fracture healing. Since the introduction of cone-beam computed tomography (CBCT) at our institution, it has become the method of choice for assessing hand and wrist bones. To date, CT volumetry has been validated for multidetector CT (MDCT) but not for CBCT.

Purpose: To assess osteotomy healing using CBCT volumetry and to evaluate two different segmentation techniques.

Material and methods: A total of 36 patients were surgically treated for malunited distal radius fractures with open-wedge osteotomy either leaving the void empty (open wedge empty [OWE]) or filled with bone graft substitutes (BGS). They were scanned using CBCT and MDCT postoperatively and after 3, 6, and 12 months. Segmentation was performed both manually and semi-automatically for volumetric measurement. Inter- and intra-observer reliability were assessed using intraclass correlation (ICC).

Results: The median osteotomy volume in the OWE group postoperatively was 0.87 cm³ (range=0.42-2.72). At 3 months, all but one of the OWE volumes had diminished to half or less of their initial volume. In the BGS group, the median postoperative volume was 1.30 cm³ (range=0.73-1.81) and at 12 months, 76% of the initial volume remained. Reliability between CBCT and MDCT volumetry expressed as ICC was ≥0.96. ICC for the two segmentation techniques was ≥0.99 and ICC for inter-observer reliability ≥0.97.

Conclusion: CBCT volumetry is a reliable tool and comparable to MDCT to quantify bone healing of an osteotomy.

Background: Temporal bone pneumatization (TBP) is influenced by age, sex, and race, and it seems to progress rapidly to puberty. However, the extent of TBP in childhood remains unclear.

Purpose: To investigate the progression of TBP in children aged 1-18 years via three-dimensional (3D) reconstruction of high-resolution computed tomography (CT) images.

Material and methods: A total of 432 temporal bones of 216 individuals aged 1-18 years with well-pneumatized mastoid antra on both sides were included in this retrospective work. We created 18 age groups, each with six boys and six girls. Surface rendering of air density was performed using -290 HU to obtain TBP. Statistical analysis employed SPSS version 24.0 software (IBM Corp., Armonk, NY, USA).

Results: The linear regression equations that considered age and volume for all cases (y_a), male (y_m) and female (y_f) were y_a= 384.42x + 1790.40, R²= 0.425; y_m= 431.54x + 1440.9, R²= 0.501; and y_f= 337.26 x + 2140.5, R²= 0.355. Both male and female individuals showed an increase in the average value of pneumatization until the age of 17, and the values ​​of pneumatization at specific ages for boys and girls showed differences. The mean male and female TBP levels differed significantly at 3, 11, and 18 years of age (P < 0.05).

Conclusion: TBP in boys was greater than that of girls at adolescence. It was possible to identify the specific periods of significant variation in the degree of pneumatization of temporal bone.

Background: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign and malignant VCFs.

Purpose: To explore the value of multiple machine learning (ML) models based on CT radiomics features for differentiating benign and malignant VCFs in patients with malignant tumors.

Material and methods: This study retrospectively analyzed 78 patients with malignant tumors accompanied by VCFs, 45 patients with benign VCFs, and 33 patients with malignant VCFs. A total of 140 lesions (86 benign lesions, 54 malignant lesions) were ultimately included in this study. All patients were divided into training sets (n = 98) and validation sets (n = 42) according to the 7:3 ratio. The radiomics features were screened and dimensioned, and multiple radiomics ML models were constructed. The receiver operating characteristic (ROC) curve was performed to assess the diagnostic performance.

Results: Five radiomics features were included in the model. All the ML models built have good diagnostic efficiency, among which the support vector machine (SVM) model performs better. The area under the curve (AUC), sensitivity, specificity, and accuracy in the training set were 0.908, 0.816, 0.883, and 0.857, respectively, while those in the validation set were 0.911, 0.647, 0.92, and 0.81, respectively.

Conclusion: A variety of ML models built based on CT radiomics features have good value for differentiating benign and malignant VCFs in malignant tumor patients, and the SVM model has a better performance.

Background: Anal fistula (AF) is an abnormal tunnel under the skin connecting the anal canal in the colon to the skin of buttocks. Fat-suppressed (FS) proton density-weighted (PDW) imaging is mainly used for the diagnosis of diseases involving bones and joints. Until now, its value in the diagnosis of anal fistula has been rarely reported.

Purpose: To compare three magnetic resonance imaging (MRI) sequences - diffusion-weighted imaging (DWI), FS-PDW), and contrast-enhanced (CE) T1-weighted (T1W) imaging - for the diagnostic value of the internal opening of AF.

Material and methods: MRI scans of 132 patients suspected of having AF between December 2021 and April 2023 were retrospectively analyzed. In total, 65 patients who underwent preoperative MRI and were treated surgically were included. The lesion conspicuity and accuracy for featuring AF were calculated by evaluating the three imaging datasets DWI, FS-PDW, and CE-T1W imaging, with surgical findings serving as the reference standard for the presence of fistulas. The statistical analysis included the application of the chi-square test and Kruskal-Wallis test.

Results: In 65 patients with AF, 87 internal openings of AF were confirmed. In terms of the diagnostic accuracy of the internal openings, both FS-PDW and CE-T1W imaging sequences were significantly better than DWI sequences, and the difference was statistically significant (P < 0.05).

Conclusion: The FS-PDW imaging sequence showed comparable diagnostic performance of the internal opening of AF to CE-T1W imaging, which can provide an important diagnostic basis for clinical procedures.

Background: Hydatid disease is a parasitic infection seen in endemic areas. Musculoskeletal hydatid disease is rarely reported.

Purpose: To describe the magnetic resonance imaging (MRI) features of musculoskeletal hydatid disease and to highlight the specific findings in the diagnosis of hydatid cysts.

Material and methods: The MRI scans of 29 cases diagnosed as musculoskeletal hydatid disease between 2000 and 2022 were retrospectively analyzed. The localization, size, appearance (unilocular or multilocular), signal characteristics, rim sign, presence of internal septa and membrane, and gadolinium enhancement pattern of hydatid cysts were evaluated.

Results: A total of 29 patients diagnosed with hydatid cyst were included in the study. Of the lesions, 18 were localized in bone and 11 were in soft tissue. The bone hydatid cysts on MRI showed heterogeneous low to intermediate signal intensity on T1-weighted images and high signal intensity on T2-weighted images in the medullary bone. In 15/18 patients, there was also cortical destruction and extension into the adjacent soft tissue planes. In 8/11 cases where the cyst was located in muscle tissue, the "cyst or cysts within a cyst" appearance was observed on MRI. The rim sign was observed in 7/11 cases and the "water lily" sign was noted in 2/11 cases.

Conclusion: MRI provides valuable information for the diagnosis of hydatid disease with its distinctive imaging features. Knowledge of the different patterns of hydatid cysts on MRI may be helpful in the diagnosis of this disease.

Background: Placenta previa is an obstetric complication related to severe maternal morbidity and mortality. Magnetic resonance imaging (MRI) can be used for the preoperative evaluation of postpartum hemorrhage.

Purpose: To investigate the value of MRI-based radiomics analysis in predicting postpartum hemorrhage among pregnant women with placenta previa.

Material and methods: Preoperative T2-weighted MRI and related clinical data of 371 patients were retrospectively collected, and these patients were randomly allocated into two subsets: the training dataset (n = 260) and the validation dataset (n = 111). The logistic regression (LR) classifier was used for the development of the radiomics model and the calculation of the radiomics score (Radscore).

Results: A total of eight radiomics features and five clinical features were selected for model development. The area under the receiver operating characteristic curve (AUC) of the radiomics model in the training and validation datasets were 0.929 (95% confidence interval [CI] = 0.891-0.957) and 0.914 (95% CI = 0.846-0.959), respectively. Combined with clinical factors, nomograms demonstrated improved diagnostic efficacy, with an AUC of 0.968 (95% CI = 0.939-0.986) in the training dataset and 0.947 (95% CI = 0.888-0.981) in the validation dataset.

Conclusion: The MRI-based model has certain value in predicting postpartum hemorrhage in pregnant women with placenta previa.