Contrast-enhanced Magnetic Resonance Imaging Research Articles

Apparently Benign 131I Adrenal Uptake.

A 60-year-old man suffering from papillary thyroid cancer (pT2 pN0(0/21) cM0) underwent diagnostic 131I whole-body scintigraphy with recombinant thyroid-stimulating hormone for follow-up after thyroidectomy and adjuvant 131I therapy with 4.2 GBq. A focal uptake of radioiodine was found in the right adrenal gland, which had not been seen on the initial posttherapeutic images; therefore, an adrenal metastasis was suspected. However, the diagnostic workup including contrast-enhanced MRI as well as endocrine laboratory tests indicated a benign etiology showcasing a very rare case of false-positive radioiodine uptake in the adrenal gland. The imaging follow-up after 1 year showed no significant changes.

Arterial Mucosal Linear Enhancement at Contrast-enhanced MRI to Exclude Residual Tumor after Neoadjuvant Chemotherapy and Radiation Therapy for Rectal Cancer.

Background A watch-and-wait regimen for locally advanced rectal cancer after neoadjuvant chemotherapy and radiation therapy (NCRT) relies on identifying complete tumor response. However, the concordance between a complete response at combined T2-weighted and diffusion-weighted MRI (T2DWI) and pathologic complete response (pCR; ie, ypT0N0) in the tumor is unsatisfactory. Purpose To assess whether identification of mucosal linear enhancement (MLE) at arterial-phase contrast-enhanced (CE) T1-weighted MRI is associated with ypT0 status in patients with locally advanced rectal cancer after NCRT and to evaluate whether combining MLE at CE T1-weighted MRI and negative lymph node metastasis (LNM) at T2DWI can improve identification of pCR. Materials and Methods This retrospective study included patients with locally advanced rectal cancer who underwent total mesorectal excision after NCRT between July 2020 and July 2023 at a tertiary referral academic center. Restaging MRI included T2DWI and arterial-phase CE T1-weighted MRI for primary tumor assessment and T2DWI for evaluation of LNM status. Imaging features associated with ypT0 status were identified at multivariable regression analysis. Results In total, 239 patients (mean age, 58 years ± 12 [SD]; 180 male patients) were assessed. MLE was more common in the ypT0 group than in the ypT1-4 group after NCRT (73% vs 4%, respectively; P < .001). MLE was associated with higher odds of ypT0 status in an adjusted analysis (odds ratio, 137; 95% CI: 25, 767; P < .001). The combination of MLE and negative LNM status achieved an area under the receiver operating characteristic curve of 0.84 (95% CI: 0.79, 0.88) for pCR. Conclusion MLE at CE MRI was associated with higher odds of complete tumor response. Combining MLE and negative LNM status showed good performance for identifying complete tumor response and may exclude residual tumors after NCRT in patients with locally advanced rectal cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Schoellnast in this issue.

The usefulness of contrast-enhanced subtraction magnetic resonance imaging for detecting endoleaks after endovascular aortic repair with prophylactic intraoperative sac embolization.

Metallic and hyperdense artifacts and T1-shortening substances in the abdominal aortic aneurysm (AAA) sac generated by embolic materials and lipiodol pose challenges in the identification of endoleaks on follow-up computed tomography (CT) or magnetic resonance imaging (MRI). To evaluate the usefulness of contrast-enhanced subtraction MRI (CES-MRI) for detecting endoleaks after endovascular abdominal aortic aneurysm repair (EVAR) with intraoperative AAA sac embolization compared with CE-CT, this study was conducted. In this study, 28 consecutive patients who underwent EVAR with prophylactic AAA sac embolization were included. All patients underwent CES-MRI and CE-CT to detect endoleaks. The definitive diagnosis of endoleaks was a consensus reading of CE-CT and CES-MRI by two certified radiologists, in addition to angiography or reproducible radiological findings in the observational examination. Analysis was performed to evaluate which examination was better for detecting endoleaks. The sensitivity, specificity, and area under the curve of CE-CT and CES-MRI according to observer 1 were 50%, 100%, and 0.813 (95% confidence interval [CI] = 0.625-1.00) and 100%, 95%, and 0.997 (95% CI = 0.984-1.00), respectively, and those according to observer 2 were 50%, 100%, and 0.750 (95% CI = 0.514-0.986) and 100%, 95%, and 0.969 (95% CI = 0.903-1.00), respectively. Intolerable artifacts were significantly observed on CE-CT. The severity of the artifacts did not depend on the stent graft on CT and MRI. Although no significant difference was observed, CES-MRI tended to have better accuracy for endoleak detection in EVAR with intraoperative AAA sac embolization than CE-CT.

Peptide-based immuno-PET/CT monitoring of dynamic PD-L1 expression during glioblastoma radiotherapy

Real-time, noninvasive programmed death-ligand 1 (PD-L1) testing using molecular imaging has enhanced our understanding of the immune environments of neoplasms and has served as a guide for immunotherapy. However, the utilization of radiotracers in the imaging of human brain tumors using positron emission tomography/computed tomography (PET/CT) remains limited. This investigation involved the synthesis of [18F]AlF-NOTA-PCP2, which is a novel peptide-based radiolabeled tracer that targets PD-L1, and evaluated its imaging capabilities in orthotopic glioblastoma (GBM) models. Using this tracer, we could noninvasively monitor radiation-induced PD-L1 changes in GBM. [18F]AlF-NOTA-PCP2 exhibited high radiochemical purity (>95%) and stability up to 4 hours after synthesis. It demonstrated specific, high-affinity binding to PD-L1 in vitro and in vivo, with a dissociation constant of 0.24 nM. PET/CT imaging, integrated with contrast-enhanced magnetic resonance imaging, revealed significant accumulation of [18F]AlF-NOTA-PCP2 in orthotopic tumors, correlating with blood–brain barrier disruption. After radiotherapy (15 Gy), [18F]AlF-NOTA-PCP2 uptake in tumors increased from 9.51% ± 0.73% to 12.04% ± 1.43%, indicating enhanced PD-L1 expression consistent with immunohistochemistry findings. Fractionated radiation (5 Gy × 3) further amplified PD-L1 upregulation (13.9% ± 1.54% ID/cc) compared with a single dose (11.48% ± 1.05% ID/cc). Taken together, [18F]AlF-NOTA-PCP2 may be a valuable tool for noninvasively monitoring PD-L1 expression in brain tumors after radiotherapy.

Phase-resolved MRI for measurement of pulmonary perfusion and ventilation defects in comparison with dynamic contrast-enhanced MRI and 129Xe MRI

IntroductionThis meta-analysis aims to evaluate the agreement and correlation between phase-resolved functional lung MRI (PREFUL MRI) and dynamic contrast-enhanced (DCE) MRI in evaluating perfusion defect percentage (QDP), as well as...

Deep learning models for rapid discrimination of high-grade gliomas from solitary brain metastases using multi-plane T1-weighted contrast-enhanced (T1CE) images.

High-grade gliomas (HGG) and solitary brain metastases (SBM) are two common types of brain tumors in middle-aged and elderly patients. HGG and SBM display a high degree of similarity on magnetic resonance imaging (MRI) images. Consequently, differential diagnosis using preoperative MRI remains challenging. This study developed deep learning models that used pre-operative T1-weighted contrast-enhanced (T1CE) MRI images to differentiate between HGG and SBM before surgery. By comparing various convolutional neural network models using T1CE image data from The First Medical Center of the Chinese PLA General Hospital and The Second People's Hospital of Yibin (Data collection for this study spanned from January 2016 to December 2023), it was confirmed that the GoogLeNet model exhibited the highest discriminative performance. Additionally, we evaluated the individual impact of the tumoral core and peritumoral edema regions on the network's predictive performance. Finally, we adopted a slice-based voting method to assess the accuracy of the validation dataset and evaluated patient prediction performance on an additional test dataset. The GoogLeNet model, in a five-fold cross-validation using multi-plane T1CE slices (axial, coronal, and sagittal) from 180 patients, achieved an average patient accuracy of 92.78%, a sensitivity of 95.56%, and a specificity of 90.00%. Moreover, on an external test set of 29 patients, the model achieved an accuracy of 89.66%, a sensitivity of 90.91%, and a specificity of 83.33%, with an area under the curve of 0.939 [95% confidence interval (CI): 0.842-1.000]. GoogLeNet performed better than previous methods at differentiating HGG from SBM, even for core and peritumoral edema in both. HGG and SBM could be fast screened using this end-to-end approach, improving workflow for both tumor treatments.

Venous malformations in children: comparison between magnetic resonance imaging and histopathological findings.

Among low-flow vascular malformations, venous malformations are relatively frequent. The pathological patterns vary in severity and are generally characterized by dilated vessels and low-flow blood that over time can organize into phleboliths. Sometimes small capillary and/or lymphatic vessels may be associated, micro- and/or macro-shunts may form alone or in different combinations, and finally adipose tissue may be interposed between the malformed vessels. Magnetic resonance imaging (MRI) is a crucial examination for confirming venous malformations because it can accurately identify different features of the lesions. The aim of our study was to compare MRI and histopathological findings of venous malformations in childrento assess thepossibilities and limitationsof MRI. In a retrospective study, two observers independently evaluated the contrast-enhanced MRI of 26 children with venous malformations. Several radiological parameters were considered and compared with histopathological findings. The agreement between the interobserver radiological evaluation and between histopathological and radiological diagnosis was verified using Cohen's kappa. MRI interobserver agreement was excellent for micro-shunts and good for the remaining findings. The radiological-pathological agreement was perfect for the presence/absence of phleboliths and of macro-shunts and almost perfect for the presence of intralesional adipose tissue, lymphatic component, and micro-shunts. MRI in venous malformations can detect the presence of phleboliths, adipose tissue, and lymphatic components with excellent accuracyand good to excellent interobserver agreement. Furthermore, MR angiography can detect micro-shunts in simple and combined venous malformations with substantial agreement with histopathological findings.

Whole-liver histogram analysis of hepatocyte-specific contrast-enhanced magnetic resonance imaging for predicting progression in patients with cirrhosis.

Liver cirrhosis, as the terminal phase of chronic liver disease fibrosis, is associated with high morbidity and mortality. Traditional methods for assessing liver function, such as clinical scoring systems, offer only a global evaluation and may not accurately reflect regional liver function variations. This study aimed at evaluating the diagnostic potential of whole-liver histogram analysis of gadobenate dimeglumine (Gd-BOPTA)-enhanced magnetic resonance imaging (MRI) for predicting the progression of cirrhosis. In this retrospective study, 265 consecutive patients with cirrhosis admitted to the Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University from August 2012 to September 2019 were enrolled. After the exclusion criteria were applied, 117 patients (84 males and 33 females) were divided into Child-Pugh A cirrhosis (n=43), Child-Pugh B cirrhosis (n=49), and Child-Pugh C cirrhosis (n=25). After correction for liver signal intensity with the spleen was completed, 19 histogram features of the whole liver were extracted and modeled to evaluate liver function, with the Child-Pugh class being incorporated as a clinical parameter. Receiver operating characteristic (ROC) curves were used to assess the diagnosis capability and determine the optimal cutoffs after a mean follow-up of 42.3±19.1 (range, 8-93) months. The association between significant histogram features and the cumulative incidence of hepatic insufficiency was analyzed with the adjusted Kaplan-Meier curve model. Among 117 patients (12%), 14 developed hepatic insufficiency through a period of follow-up. Five features, including the median (P<0.01), 90th percentile (P<0.01), root mean squared (P<0.01), mean (P<0.01), and 10th percentile (P<0.05), were significantly different between the groups with and without hepatic insufficiency according to the Kruskal-Wallis test; in the ROC curve analysis, the area under the curve (AUC) of these features was 0.723 [95% confidence interval (CI): 0.653-0.793], 0.722 (95% CI: 0.652-0.792), 0.722 (95% CI: 0.652-0.792), 0.721 (95% CI: 0.651-0.791), and 0.674 (95% CI: 0.600-0.748) after correction, respectively (all P values <0.05). Median, 90th percentile, root mean squared, and mean were found to be significant factors in predicting liver insufficiency. The adjusted Kaplan-Meier curves revealed that patients with a feature level less than the cutoff, as compared to those with a level above the cutoff, showed a statistically shorter progression-free survival and higher incidences of hepatic insufficiency for significant features of median (cutoff =26.001; 21.28% versus 5.71%; P=0.02), 90th percentile (cutoff =86.263; 20.41% versus 5.88%; P<0.01), root mean squared (cutoff =1,028.477; 19.15% versus 7.14%; P=0.049), and mean (cutoff =27.484; 19.15% versus 7.14%; P=0.049). Patients with a 10th percentile less than -39.811 also showed a higher cumulative incidence of hepatic insufficiency than did those with a value higher than the cutoff (0.18% versus 7.46%; P=0.22). Whole-liver histogram analysis of Gd-BOPTA-enhanced MRI may serve as a noninvasive analytical method to predict hepatic insufficiency in patients with cirrhosis.

Preoperative prediction of microvascular invasion risk in hepatocellular carcinoma with MRI: peritumoral versus tumor region

ObjectivesTo explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI).MethodsA total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC).ResultsThe XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80.ConclusionCompared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted.Clinical relevance statementThe 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region.Key PointsWe investigated tumor and different peritumoral regions, as well as their fusion.MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region.The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI.Graphical

Spontaneous Intracranial Hypotension: Role of Computed Tomography-guided Cervical Epidural Blood Patch.

Lumbar epidural blood patch (EBP) is not successful in all cases of cerebrospinal fluid (CSF) leak, particularly in the cervicothoracic region. The present study is a retrospective analysis of a cohort of patients who had undergone computed tomography (CT)-guided cervical EBP for spontaneous intracranial hypotension (SIH) due to CSF leak in the cervical region. We retrospectively collected data from March 2009 to 2020. Our inclusion criteria were (1) clinical syndrome associated with CSF leak, (2) headache coming on shortly after assuming the erect position and relief achieved by lying down, (3) CT myelography evidence of CSF leak in the cervical region, and (4) patient not responding to conservative management for 7 days. Exclusion criteria were patients with bleeding diathesis and infection. There were six females and four males. Ages ranged from 32 to 57, with an average of 42 years. On presentation, all patients underwent contrast-enhanced magnetic resonance imaging (MRI) and CT myelography. Cervical EBP was done under CT scan guidance. Assessment of headache was done on a 10-point numerical rating scale (NRS) before and after the procedure. Results are categorized into complete relief, partial relief, and no relief categories. Nine out of 10 patients were completely recovered. One patient was partially recovered. The average NRS scale was 9.6 before treatment, which became 0.4 after EBP. No neurological or vascular complications were seen. Computed tomography-guided cervical EBP is an optimum and effective way of treating SIH due to a leak in the cervical region. It has a higher success rate than lumbar EBP. However, prospective randomized controlled trials of cervical vs lumbar EBP will further validate our observation.

A Comprehensive Model Outperformed the Single Radiomics Model in Noninvasively Predicting the HER2 Status in Patients with Breast Cancer

This study aimed to develop predictive models based on conventional magnetic resonance imaging (cMRI) and radiomics features for predicting human epidermal growth factor receptor 2 (HER2) status of breast cancer (BC) and compare their performance. A total of 287 patients with invasive BC in our hospital were retrospectively analyzed. All patients underwent preoperative breast MRI consisting of fat-suppressed T2-weighted imaging, axial dynamic contrast-enhanced MRI, and diffusion-weighted imaging sequences. From these sequences, radiomics features were derived. Three distinct models were established utilizing cMRI features, radiomics features, and a comprehensive model that amalgamated both. The predictive capabilities of these models were assessed using the receiver operating characteristic curve analysis. The comparative performance was then determined through the DeLong test and net reclassification improvement (NRI). In a randomized split, the 287 patients with BC were allotted to either training (234; 46 HER2-zero, 107 HER2-low, 81 HER2-positive) or test (53; 8 HER2-zero, 27 HER2-low, 18 HER2-positive) at an 8:2 ratio. The mean area under the curve (AUCs) for cMRI, radiomics, and comprehensive models predicting HER2 status were 0.705, 0.819, and 0.859 in training set and 0.639, 0.797, and 0.842 in test set, respectively. DeLong's test indicated that the combined model's AUC surpassed the radiomics model significantly (p<0.05). NRI analysis verified superiority of the combined model over the radiomics for BC HER2 prediction (NRI 25.0) in the test set. The comprehensive model based on the combination of cMRI and radiomics features outperformed the single radiomics model in noninvasively predicting the three-tiered HER2 status in patients with BC.

Comparison of golden-angle radial sparse parallel (GRASP) and conventional cartesian sampling in 3D dynamic contrast-enhanced mri for bladder cancer: a preliminary study.

To compare the image quality, inter-reader agreement, and diagnostic capability for muscle-invasive bladder cancer (MIBC) of the reconstructed images in sections orthogonal to the bladder tumor obtained by 3D Dynamic contrast-enhanced (DCE)-MRI using the Golden-angle Radial Sparse Parallel (GRASP) technique with the images directly captured using the Cartesian sampling. This study involved 68 initial cases of bladder cancer examined with DCE-MRI (GRASP: n = 34, Cartesian: n = 34) at 3 Tesla. Four radiologists conducted qualitative evaluations (overall image quality, absence of motion artifact, absence of streak artifact, and tumor conspicuity) using a five-point Likert scale (5 = Excellent/None) and quantitative signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurements. The areas under the receiver-operating characteristic curves (AUCs) for the Vesical Imaging-Reporting and Data System (VI-RADS) DCE score for MIBC assessment were calculated. Inter-reader agreement was also assessed. GRASP notably enhanced overall image quality (pooled score: GRASP 4 vs. Cartesian 3, P < 0.0001), tumor conspicuity (5 vs. 3, P < 0.05), SNR (Median 38.2 vs. 19.0, P < 0.0001), and CNR (7.9 vs. 6.0, P = 0.005), with fewer motion artifacts (5 vs. 3, P < 0.0001) and minor streak artifacts (5 vs. 5, P > 0.05). Although no significant differences were observed, the GRASP group tended to have higher AUCs for MIBC (pooled AUCs: 0.92 vs. 0.88) and showed a trend toward higher inter-reader agreement (pooled kappa-value: 0.70 vs. 0.63) compared to the Cartesian group. Using the GRASP for 3D DCE-MRI, the reconstructed images in sections orthogonal to the bladder tumor achieved higher image quality and improve the clinical work flow, compared to the images directly captured using the Cartesian. GRASP tended to have higher diagnostic ability for MIBC and showed a trend toward higher inter-reader agreement compared to the Cartesian.

Study on the value of MRI in locating the internal OS of the cervix and influencing factors

The position of the internal os of the cervix reported in the literature was inconsistent on MRI images. Additionally, the practical impactful data influencing the internal os located by MRI is limited. We aimed to confirm the position of the internal os of the cervix on MRI images, and the influencing factors locating the the internal os by MRI. A single-center retrospective study was conducted. Data from 175 patients who underwent total hysterectomy for stage I endometrial cancer were collected. The internal os of the cervix is positioned as the starting point for measuring the length of the cervix on MRI images. On dynamic contrast-enhanced MRI (DCE-MRI), the section formed by the enhancement difference between the uterus and cervix, and on T2-weighted imaging(T2WI), the section formed by the physiological curvature of the uterus and the low signal intensity of the cervical stroma were used as starting points. The results showed no statistically significant difference compared with the removed uterus specimens (p = 0.208, p = 0.571, p = 0.804). A history of cesarean section(p < 0.001), irregular vaginal bleeding for more than three months(p < 0.001), cervical adenomyosis(p = 0.043), and premenopause(p = 0.001) were not conducive to locating the internal os of the cervix by MRI. Our findings provide valuable information and confirm the position of the internal os of the cervix on MRI images, and the several important infuencing factors. We hope that some patients will benefit from our study.

Value of Dynamic Contrast-Enhanced MRI for Grade Group Prediction in Prostate Cancer: A Radiomics Pilot Study

Rationale and objectivesTo determine the role of dynamic contrast-enhanced (DCE) MRI-radiomics in predicting the International Society of Urological Pathology Grade Group (ISUP-GG) in therapy-naïve prostate cancer (PCa) patients. Materials and MethodsIn this ethics review board-approved retrospective study on two prospective clinical trials between 2017 and 2020, 73 men with suspected/confirmed PCa were included. All participants underwent multiparametric MRI. On MRI, dominant lesions (per PI-RADS) were identified. DCE-MRI radiomic features were extracted from the segmented volumes following the image biomarker standardization initiative (IBSI) guidelines through 14 time points. Histopathology evaluation on the cognitive-fusion targeted biopsies was set as the reference standard. Univariate regression was done to evaluate potential predictors across all calculated features. Random forest imputation was used for multivariate modelling. ResultsSeventy-three index lesions were reviewed. Histopathology revealed 28, 16, 13 and 16 lesions with ISUP-GG-Negative/1/2, ISUP-GG-3, ISUP-GG-4 and ISUP-GG-5, respectively. From the extracted features, total lesion enhancement (TLE), minimum enhancement intensity and Grey-Level Run Length Matrix (GLRLM) were the most significantly different parameters among ISUP-GGs (Neg/1/2 vs 3/4 vs 5). Sixteen features with significant cross-sectional associations with ISUP-GGs entered the multivariate analysis. The final DCE partitioning model used only four features (lesion sphericity, TLE, GLRLM and Grey-Level Zone Length Matrix [GLZLM]). For the binarized diagnosis (ISUP-GG≤2 vs ISUP-GG>2), the accuracy reached 81%. ConclusionDCE-MRI radiomics might be used as a non-invasive tool for aiding pathological grade group prediction in therapy-naïve PCa patients, potentially adding complementary information to PI-RADS for supporting tailored diagnostic pathways and treatment planning.

A CASE OF PHEOCROMOCYTOMA ARISING FROM HETEROTOPIC ADRENAL GLAND IN CHILDREN

Pheochromocytoma is a rare tumor in children. We present the case of a 9-year-old female child with heterotopic retroperitoneal localized pheochromocytoma, clinically manifesting hypertension, tachycardia and headache. The diagnosis was based on abdominal ultrasound, CT and contrast-enhanced MRI, confirmed by evaluation of free plasma catecholamine metabolites and testing of fractionated urinary metanephrines. This case is of interest due to an atypical position and vascularization of the pheochromoctioma, located retroperitoneally on the right, casuistical described in the literature, which created some diagnostic confusions. The use of the transperitoneal approach, in this case, allowed an excellent exposure and radical removal of the tumor without injuring the kidney and ureter attached to the tumor.

Assessing blood-brain barrier dysfunction and its association with Alzheimer’s pathology, cognitive impairment and neuroinflammation

BackgroundBlood-brain barrier (BBB) alterations may contribute to AD pathology through various mechanisms, including impaired amyloid-β (Aβ) clearance and neuroinflammation. Soluble platelet-derived growth factor receptor beta (sPDGFRβ) has emerged as a potential biomarker for BBB integrity. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) offers a direct assessment of BBB permeability. However, the relationship between BBB dysfunction, cognitive impairment, and AD pathology remains unclear, with inconsistent findings in the literature.MethodsWe conducted a cross-sectional study using data from the DELCODE and DESCRIBE cohorts to investigate BBB dysfunction in participants with normal cognition (NC), mild cognitive impairment (MCI), and AD dementia. BBB function was assessed using DCE-MRI and sPDGFRβ levels in cerebrospinal fluid and AD biomarkers Aβ and tau were measured. In a subset of patients, the CSF/plasma-ratio of albumin (QAlb) as a standard marker of BBB integrity and markers of neuroinflammation were analyzed.Results91 participants (NC: 44, MCI: 21, AD: 26) were included in the analysis. The average age was 74.4 years, 42% were female. Increased hippocampal BBB disruption was observed in the AD-group (Ktrans: 0.55 × 10− 3 min− 1 ± 0.74 × 10− 3 min− 1) but not the MCI-group (Ktrans: 0.177 × 10− 3 min− 1 ± 0.22 × 10− 3 min− 1), compared to the NC group (Ktrans: 0.19 × 10− 3 min− 1 ± 0.37 × 10− 3 min− 1, p < .01). sPDGFRβ was not significantly different between the cognitive groups. However, sPDGFRβ levels were significantly associated with age (r = .33, p < .01), independent of vascular risk factors. Further, sPDGFRβ showed significant positive associations with soluble Aβ levels (Aβ40: r = .57, p < .01; Aβ42: r = .39, p < .01) and YKL-40 (r = .53, p < .01), a marker of neuroinflammation. sPDGFRβ/DCE-MRI was not associated with overall AD biomarker positivity or APOE-status.ConclusionIn dementia, but not MCI, hippocampal BBB disruption was observed. sPDGFRβ increased with age and was associated with neuroinflammation independent of cognitive impairment. The association between Aβ and sPDGFRβ may indicate a bidirectional relationship reflecting pericytes’ clearance of soluble Aβ and/or vasculotoxic properties of Aβ.

Phosphoglyceride crystal deposition with suspected malignant ovarian tumor: a case report and literature review.

Phosphoglyceride crystal deposition disease is a rare condition occurring in soft tissues, resulting in scarring and affecting the bones, making preoperative differentiation from malignant tumors challenging. Here, we describe a case of phosphoglyceride crystal deposition disease initially suspected to be a malignant ovarian tumor before surgery. A 50-year-old woman with a history of three cesarean sections presented with lower abdominal pain. Transvaginal ultrasonography revealed a 54 × 58mm tumor in the lower right abdomen. Pelvic contrast-enhanced magnetic resonance imaging showed a thickened cystic wall with diffusion restriction, a low signal intensity region on T1-weighted images, and a slightly high signal intensity region on T2-weighted images. The tumor markers, cancer antigen 125 and carbohydrate antigen 19-9 levels, were within normal ranges; however, positron emitting tomography-computed tomography revealed fluorodeoxyglucose accumulation (SUVmax 31.28) in the tumor wall. Suspecting a malignant ovarian tumor, a laparoscopy was performed to observe the abdominal cavity. A 10cm white solid tumor was identified in the midline of the lower abdominal wall, leading to an open surgery recommendation. The tumor, adhering to the pubic bone, was excised. The tumor measured 9 × 7cm, with the cut surface showing a yellow brownish solid periphery and central region with liquefied degeneration. Histologically, radial basophilic deposits, dense infiltration of macrophages, multinucleated giant cells, and foam-like tissue spheres were observed. The central region exhibited cholesterol clefts, fibrin exudation, and necrosis, leading to a diagnosis of phosphoglyceride crystal deposition disease. This disease is rare, occurring in patients with atypical fluorodeoxyglucose accumulation on positron emission tomography-computed tomography or with a history of tissue damage, such as abdominal surgery.

The value of diffusion kurtosis imaging and dynamic contrast-enhanced magnetic resonance imaging in the differential diagnosis of parotid gland tumors.

Parotid gland tumors (PGTs) are the most common benign tumors of salivary gland tumors. However, the diagnostic value of relative values of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion kurtosis imaging (DKI) parameters for PGTs has not been extensively studied. Therefore, this study aimed to evaluate the diagnostic performance of combined DKI and DCE-MRI for differentiating PGTs by introducing the concept of relative value. The DCE-MRI and DKI imaging data of 142 patients with PGTs between June 2018 and August 2022 were collected. Patients were divided into four groups by histopathology: malignant tumors (MTs), pleomorphic adenomas (PAs), Warthin tumors (WTs), and basal cell adenomas (BCAs). All MRI examinations were conducted using a 3 T MRI scanner with a 20-channel head and neck coil. Quantitative parameters of DCE-MRI and DKI and their relative values were determined. Kruskal-Wallis H test, post-hoc test with Bonferroni correction, one-way analysis of variance (ANOVA) and post-hoc test with least significant difference (LSD) method, and the receiver operating characteristic (ROC) curve were used for statistical analysis. Statistical significance was set at P<0.05. Only the combination of DKI and DCE-MRI parameters could reliably distinguish BCAs from other PGTs. PAs demonstrated the lowest transfer constant from plasma to extravascular extracellular space (Ktrans) value [0.09 (0.06, 0.20) min-1], relative Ktrans (rKtrans) [-0.24 (-0.64, 1.00)], rate constant from extravascular extracellular space to plasma (Kep) value [0.32 (0.22, 0.53) min-1], relative Kep (rKep) [0.32 (0.22, 0.53) min-1], and initial area under curve (iAUC) value [0.15 (0.09, 0.26) mmol·s/kg] compared with WTs, BCAs, and MTs (all P<0.05). The Ktrans values for MTs were substantially lower [0.17 (0.10, 0.31) min-1] than those for WTs (P=0.01). The Kep values for MTs [0.71 (0.52, 1.28) min-1] were substantially lower (all P<0.05) than those for WTs and BCAs. PAs and BCAs had higher diffusion coefficient (D) values and lower diffusion kurtosis (K) values and relative K (rK) values than MTs and WTs. However, the D and K values did not differ significantly even in their relative values of PAs and BCAs (all P>0.05). By using logistic regression, the combination of K value and rKep value further enhanced their discriminatory power between PAs and WTs [area under the ROC curve (AUC), 0.986], the combination of K and rKep value further enhanced their discriminatory power between PAs and MTs (AUC, 0.915), and the combination of D and Kep value further enhanced their discriminatory power between BCAs and MTs (AUC, 0.909). DKI and DCE-MRI can be used to differentiate PGTs quantitatively and can complement each other. The combined use of DKI and DCE-MRI parameters can improve the diagnostic accuracy of distinguishing PGTs.

Can dynamic contrast-enhanced MR imaging based on radiomics improve the diagnostic efficiency of clinically significant prostate cancer?

Aims/Background Prostate cancer stands out as one of the most prevalent malignant tumours among males. The non-invasive identification of clinically significant prostate cancer via magnetic resonance imaging plays a critical role in circumventing unnecessary biopsies and determining suitable treatment strategies for patients. Our study aimed to evaluate the potential improvement in predictive accuracy for clinically significant prostate cancer by incorporating perfusion data obtained from dynamic contrast-enhanced magnetic resonance imaging acquisition protocols into multiparametric magnetic resonance imaging parameters. Methods Radiomics extracted from perfusion parameters (Ktrans, Kep, Ve) of dynamic contrast-enhanced magnetic resonance imaging were analysed in patients suspected of prostate cancer who underwent 3T multiparametric magnetic resonance imaging between January 2017 and June 2023 in this retrospective study. The pathological findings obtained from biopsy or therapy were categorised into groups based on the Gleason sum score as either clinically significant prostate cancer (Gleason sum score > 7) or non-clinically significant prostate cancer (Gleason sum score ≤ 6). Diagnostic models were constructed using logistic regression analysis, incorporating prostate imaging reporting and data system V2.1 scores and clinical data, with or without radiomics extracted from dynamic contrast-enhanced. The area under curve (AUC) values were compared using the DeLong test. Results Overall, 214 men (clinically significant prostate cancer [n=78] and non-clinically significant prostate cancer [n=136]) were included. The clinical-prostate imaging reporting and data system model demonstrated an AUC of 0.89 (95% confidence interval: 0.84-0.95) in the training cohort and 0.91 (95% confidence interval: 0.84-0.98) in the test cohort. For the clinical-prostate imaging reporting and data system-radscore model, the AUC values were 0.97 (95% confidence interval: 0.95-0.99) for Ktrans, 0.98 (95% confidence interval: 0.96-1.00) for Ve, and 0.96 (95% confidence interval: 0.93-0.98) for Kep in the training cohort, and 0.97 (95% confidence interval: 0.94-1.00) for Ktrans, 0.95 (95% confidence interval: 0.91-1.00) for Ve, and 0.97 (95% confidence interval: 0.94-1.00) for Kep in the test cohort. Radiomics based on perfusion parameters exhibited good diagnostic performance in predicting clinically significant prostate cancer. The clinical-prostate imaging reporting and data system-radscore model demonstrated superior diagnostic capability compared to perfusion-based radiomics or clinical-prostate imaging reporting and data system models alone. Conclusion The application of radiomics, which involves extracting perfusion parameters from dynamic contrast-enhanced imaging, has the potential to enhance diagnostic accuracy for clinically significant prostate cancer.

Pre-operative prediction of histopathological growth patterns of colorectal cancer liver metastasis using MRI-based radiomic models.

Histopathological growth patterns (HGPs) of colorectal liver metastases (CRLMs) have prognostic value. However, the differentiation of HGPs relies on postoperative pathology. This study aimed to develop a magnetic resonance imaging (MRI)-based radiomic model to predict HGP pre-operatively, following the latest guidelines. This retrospective study included 93 chemotherapy-naïve patients with CRLMs who underwent contrast-enhanced liver MRI and a partial hepatectomy between 2014 and 2022. Radiomic features were extracted from the tumor zone (RTumor), a 2-mm outer ring (RT+2), a 2-mm inner ring (RT-2), and a combined ring (R2+2) on late arterial phase MRI images. Analysis of variance method (ANOVA) and least absolute shrinkage and selection operator (LASSO) algorithms were used for feature selection. Logistic regression with five-fold cross-validation was used for model construction. Receiver operating characteristic curves, calibrated curves, and decision curve analyses were used to assess model performance. DeLong tests were used to compare different models. Twenty-nine desmoplastic and sixty-four non-desmoplastic CRLMs were included. The radiomic models achieved area under the curve (AUC) values of 0.736, 0.906, 0.804, and 0.794 for RTumor, RT-2, RT+2, and R2+2, respectively, in the training cohorts. The AUC values were 0.713, 0.876, 0.785, and 0.777 for RTumor, RT-2, RT+2, and R2+2, respectively, in the validation cohort. RT-2 exhibited the best performance. The MRI-based radiomic models could predict HGPs in CRLMs pre-operatively.