Apparent Diffusion Coefficient Ratio Research Articles

MRI Scoring Systems for Predicting Isocitrate Dehydrogenase Mutation and Chromosome 1p/19q Codeletion in Adult-type Diffuse Glioma Lacking Contrast Enhancement.

Background According to 2021 World Health Organization criteria, adult-type diffuse gliomas include glioblastoma, isocitrate dehydrogenase (IDH)-wildtype; oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and astrocytoma, IDH-mutant, even when contrast enhancement is lacking. Purpose To develop and validate simple scoring systems for predicting IDH and subsequent 1p/19q codeletion status in gliomas without contrast enhancement using standard clinical MRI sequences. Materials and Methods This retrospective study included adult-type diffuse gliomas lacking contrast at contrast-enhanced MRI from two tertiary referral hospitals between January 2012 and April 2022 with diagnoses confirmed at pathology. IDH status was predicted primarily by using T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign, followed by 1p/19q codeletion prediction. A visual rating of MRI features, apparent diffusion coefficient (ADC) ratio, and relative cerebral blood volume was measured. Scoring systems were developed through univariable and multivariable logistic regressions and underwent calibration and discrimination, including internal and external validation. Results For the internal validation cohort, 237 patients were included (mean age, 44.4 years ± 14.4 [SD]; 136 male patients; 193 patients in IDH prediction and 163 patients in 1p/19q prediction). For the external validation cohort, 35 patients were included (46.1 years ± 15.3; 20 male patients; 28 patients in IDH prediction and 24 patients in 1p/19q prediction). The T2-FLAIR mismatch sign demonstrated 100% specificity and 100% positive predictive value for IDH mutation. IDH status prediction scoring system for tumors without mismatch sign included age, ADC ratio, and morphologic characteristics, whereas 1p/19q codeletion prediction for IDH-mutant gliomas included ADC ratio, cortical involvement, and mismatch sign. For IDH status and 1p/19q codeletion prediction, bootstrap-corrected areas under the receiver operating characteristic curve were 0.86 (95% CI: 0.81, 0.90) and 0.73 (95% CI: 0.65, 0.81), respectively, whereas at external validation they were 0.99 (95% CI: 0.98, 1.0) and 0.88 (95% CI: 0.63, 1.0). Conclusion The T2-FLAIR mismatch sign and scoring systems using standard clinical MRI predicted IDH and 1p/19q codeletion status in gliomas lacking contrast enhancement. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Badve and Hodges in this issue.

Differentiation between adrenocortical carcinoma and lipid-poor adrenal adenoma using a multiparametric MRI-based diagnostic algorithm

PurposeThe purpose of this study was to evaluate the capabilities of multiparametric magnetic resonance imaging (MRI) in differentiating between lipid-poor adrenal adenoma (LPAA) and adrenocortical carcinoma (ACC). Materials and methodsPatients of two centers who underwent surgical resection of LPAA or ACC after multiparametric MRI were retrospectively included. A training cohort was used to build a diagnostic algorithm obtained through recursive partitioning based on multiparametric MRI variables, including apparent diffusion coefficient and chemical shift signal ratio (i.e., tumor signal intensity index). The diagnostic performances of the multiparametric MRI-based algorithm were evaluated using a validation cohort, alone first and then in association with adrenal tumor size using a cut-off of 4 cm. Performances of the diagnostic algorithm for the diagnosis of ACC vs. LPAA were calculated using pathology as the reference standard. ResultsFifty-four patients (27 with LPAA and 27 with ACC; 37 women; mean age, 48.5 ± 13.3 [standard deviation (SD)] years) were used as the training cohort and 61 patients (24 with LPAA and 37 with ACC; 47 women; mean age, 49 ± 11.7 [SD] years) were used as the validation cohort. In the validation cohort, the diagnostic algorithm yielded best accuracy for the diagnosis of ACC vs. LPAA (75%; 46/61; 95% CI: 55–88) when used without lesion size. Best sensitivity was obtained with the association of the diagnostic algorithm with tumor size (96%; 23/24; 95% CI: 80–99). Best specificity was obtained with the diagnostic algorithm used alone (76%; 28/37; 95% CI: 60–87). ConclusionA multiparametric MRI-based diagnostic algorithm that includes apparent diffusion coefficient and tumor signal intensity index helps discriminate between ACC and LPAA with high degrees of specificity and accuracy. The association of the multiparametric MRI-based diagnostic algorithm with adrenal lesion size helps maximize the sensitivity of multiparametric MRI for the diagnosis of ACC.

Ultra-high b-value DWI accurately identifies isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas.

To distinguish isocitrate dehydrogenase (IDH) genotypes and tumor subtypes of adult-type diffuse gliomas based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5) in 2021 using standard, high, and ultra-high b-value diffusion-weighted imaging (DWI). This prospective study enrolled 70 patients with adult-type diffuse gliomas who underwent multiple b-value DWI. Apparent diffusion coefficient (ADC) values including ADCb500/b1000, ADCb500/b2000, ADCb500/b3000, ADCb500/b4000, ADCb500/b6000, ADCb500/b8000, and ADCb500/b10000 in tumor parenchyma (TP) and contralateral normal-appearing white matter (NAWM) were calculated. The ADC ratios of TP/NAWM were assessed for correlations with IDH genotypes, tumor subtypes, and Ki-67 status; diagnostic performances were compared. All ADCs were significantly higher in IDHmutant gliomas than in IDH wild-type gliomas (p < 0.01 for all); ADCb500/b8000 had the highest area under the curve (AUC) of 0.866. All ADCs were significantly lower in glioblastoma than in astrocytoma (p < 0.01 for all). ADCs other than ADCb500/b1000 were significantly lower in glioblastoma than in oligodendroglioma (p < 0.05 for all). ADCb500/b8000 and ADCb500/b10000 were significantly higher in oligodendroglioma than in astrocytoma (p = 0.034 and 0.023). The highest AUCs were 0.818 for ADCb500/b6000 when distinguishing glioblastoma from astrocytoma, 0.979 for ADCb500/b8000 and ADCb500/b10000 when distinguishing glioblastoma from oligodendroglioma, and 0.773 for ADCb500/b10000 when distinguishing astrocytoma from oligodendroglioma. Additionally, all ADCs were negatively correlated with Ki-67 status (p < 0.05 for all). Ultra-high b-value DWI can reliably separate IDH genotypes and tumor subtypes of adult-type diffuse gliomas using WHO CNS5 criteria. Ultra-high b-value diffusion-weighted imaging can accurately distinguish isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas, which may facilitate personalized treatment and prognostic assessment for patients with glioma. • Ultra-high b-value diffusion-weighted imaging can accurately distinguish subtle differences in water diffusion among biological tissues. • Ultra-high b-value diffusion-weighted imaging can reliably separate isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas. • Compared with standard b-value diffusion-weighted imaging, high and ultra-high b-value diffusion-weighted imaging demonstrate better diagnostic performances.

Notch appearance as a novel radiological predictor of transient expansion and good outcome of expanding schwannoma after radiotherapy

ObjectivesSchwannoma expansion after radiotherapy has not been well-studied despite the clinical importance of distinguishing transient increase from permanent expansion. Thus, this study aimed to identify the underlying mechanism and novel radiological predictors of schwannoma expansion after radiotherapy.Materials & methodsWe retrospectively examined the therapeutic effects of radiotherapy on schwannomas and magnetic resonance images of 43 patients with vestibular schwannomas who underwent stereotactic radiotherapy or radiosurgery at our facility between June 1, 2012 and September 1, 2018. Based on the size change pattern, the treated tumors were classified into six groups, including transient-expansion and consistent-increase groups. The apparent diffusion coefficient (ADC) ratio and appearance of any notch were included as evaluation items based on our hypothesis that transient expansion is due to edema with increased extracellular free water. A log-rank test was performed to evaluate the relationship between the local control rate and radiological signs.ResultsThe mean overall 5-year local control rate was 90%, and the median follow-up period was 62 (24–87) months. Approximately 28% of the tumors showed transient expansion; all ADC ratios synchronized with size change, and 75% showed a new notch appearance. Approximately 9% of tumors showed consistent increase, with no notch on the outline. The log-rank test revealed a difference in the local control rate with or without notch appearance in expanding irradiated schwannomas. All tumors with notch appearance showed a significant regression 5 years after radiation.ConclusionsNew notch appearance on the outline could indicate favorable long-term outcomes of expanding schwannomas post-treatment. Clinical relevance statementNotch appearance can help differentiate a transient schwannoma from a real tumor expansion, and it is a novel predictor of better outcomes of expanding schwannomas after radiotherapy.Graphical

Halka Şekilli Lateral Ventrikül Nodüllerinin Konvansiyonel ve Diffüzyon MR Görüntüleme Özellikleri

Objective: The aim of this study is to evaluate the conventional and diffusion MRI findings of ring-shaped lateral ventricular nodules (RSLVN) along with clinical features.&#x0D; Methods: MR images of all patients who underwent contrast-enhanced brain MRI between 2019 and 2023 were retrospectively evaluated. The number, shape, maximal diameter, and signal intensity of RSLVNs on T1-weighted (T1W), T2-weighted (T2W), fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging (DWI), and contrast-enhancement status were evaluated. Apparent diffusion coefficient (ADC) values and normalized ADC ratios of nodules were also determined. If follow-up MRIs were performed, morphological changes of RSLVNs were evaluated. &#x0D; Results: RSLVN was observed in fifteen (0.51%) of 2920 patients. Multiple RSLVNs were observed in five patients and therefore a total of 23 RSLVNs were identified in fifteen patients. Nodules were located on the roof of the lateral ventricle in eight nodules (34.8%), in the frontal horn in twelve nodules (52.2%), and in the septum pellucidum in three. 6 of 23 RSLVNs (26.1%) were larger than 1 cm. All RSLVNs were isointense on T1W and T2W, while hyperintense on FLAIR. On DWI, 20 of 23 RSLVNs had isointense signal and the remaining 3 lesions were hyperintense. The mean ADC value and nADC ratio were 1.42 ± 0.29 x 10-3mm2 and 1.87 ± 0.31, respectively.&#x0D; Conclusion: RSLVNs may be more frequent than previously reported. Their uniform MRI appearance and typical localizations are distinctive, and they can reach relatively large sizes. Morphological stability during follow-up and the ADC values of these lesions suggest a possible benign nature.

Prediction of vessels encapsulating tumor clusters pattern and prognosis of hepatocellular carcinoma based on preoperative gadolinium-ethoxybenzyl-diethylenetriaminepentaacetic acid magnetic resonance imaging

Vessels encapsulating tumor clusters (VETC) is a novel vascular pattern distinct from microvascular invasion that is significantly associated with poor prognosis in patients with hepatocellular carcinoma (HCC). This study aimed to predict the VETC pattern and prognosis of patients with HCC based on preoperative gadolinium-ethoxybenzyl-diethylenetriaminepentaacetic acid (Gd-EOB-DTPA) magnetic resonance imaging (MRI). Patients with HCC who underwent surgical resection and preoperative Gd-EOB-DTPA MRI between January 1, 2016 and August 31, 2022 were retrospectively included. The variables associated with VETC were evaluated using logistic regression. A nomogram model was constructed on the basis of independent risk factors. COX regression was used to determine the variables associated with recurrence-free survival (RFS). A total of 98 patients with HCC were retrospectively included. Peritumoral hypointensity on the hepatobiliary phase (HBP) (odd ratio [OR], 2.58; 95% CI, 1.05-6.33; P=.04), tumor-to-liver signal intensity ratio on HBP of ≤0.75 (OR, 27.80; 95% CI, 1.53-502.91; P=.02), and tumor-to-liver apparent diffusion coefficient ratio of ≤1.23 (OR, 4.65; 95% CI, 1.01-21.38; P=.04) were independent predictors of VETC pattern. A nomogram was constructed by combining the aforementioned 3 significant variables. The accuracy, sensitivity, and specificity were 69.79%, 71.74%, and 68.00%, respectively, with an area under the receiver operating characteristic curve of 0.75 (95% CI, 0.65-0.83). The variables significantly associated with RFS of patients with HCC after surgery were Barcelona Clinic Liver Cancer stage (hazard ratio [HR], 2.15; 95% CI, 1.09-4.22; P=.03) and VETC pattern (HR, 2.28; 95% CI, 1.29-4.02; P=.004). The preoperative imaging features based on Gd-EOB-DTPA MRI can be used to predict the VETC pattern, which has prognostic significance for postoperative RFS of patients with HCC.

Diagnosis of dysthyroid optic neuropathy: combined value of orbital MRI and intracranial visual pathway diffusion kurtosis imaging.

To evaluate the combined performance of orbital MRI and intracranial visual pathway diffusion kurtosis imaging (DKI) in diagnosing dysthyroid optic neuropathy (DON). We retrospectively enrolled 61 thyroid-associated ophthalmopathy (TAO) patients, including 25 with DON (40 eyes) and 36 without DON (72 eyes). Orbital MRI-based apical muscle index (MI), diameter index (DI) of the optic nerve (ON), area index (AI) of the ON, apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) of the ON, DKI-based kurtosis fractional anisotropy (KFA) and mean kurtosis (MK) of the optic tract (OT), optic radiation (OR), and Brodmann areas (BAs) 17, 18, and 19 were measured and compared between groups. The diagnostic performances of models were evaluated using receiver operating characteristic curve analyses and compared using the DeLong test. TAO patients with DON had significantly higher apical MI, apical AI, and SIR of the ON, but significantly lower ADC of the ON than those without DON (p < 0.05). Meanwhile, the DON group exhibited significantly lower KFA across the OT, OR, BA17, BA18, and BA19 and lower MK at the OT and OR than the non-DON group (p < 0.05). The model integrating orbital MRI and intracranial visual pathway DKI parameters performed the best in diagnosing DON (AUC = 0.926), with optimal diagnostic sensitivity (80%) and specificity (94.4%), followed by orbital MRI combination (AUC = 0.890), and then intracranial visual pathway DKI combination (AUC = 0.832). Orbital MRI and intracranial visual pathway DKI can both assist in diagnosing DON. Combining orbital and intracranial imaging parameters could further optimize diagnostic efficiency. The novel finding could bring novel insights into the precise diagnosis and treatment of dysthyroid optic neuropathy, accordingly, contributing to the improvement of the patients' prognosis and quality of life in the future. • Orbital MRI and intracranial visual pathway diffusion kurtosis imaging can both assist in diagnosing dysthyroid optic neuropathy. • Combining orbital MRI and intracranial visual pathway diffusion kurtosis imaging optimized the diagnostic efficiency of dysthyroid optic neuropathy.

Radiologic Features of Well-circumscribed Orbital Tumors With Histopathologic Correlation: A Multi-center Study.

To delineate specific imaging characteristics of solitary fibrous tumors, schwannomas, cavernous venous malformations, and well-circumscribed orbital lymphoma. Patients undergoing excisional biopsy of solitary fibrous tumor, schwannomas, cavernous venous malformations, or well-circumscribed orbital lymphoma with preoperative MRIs available for review were identified at 3 academic centers in the United States and Australia. An exploratory statistical analysis was performed to identify important radiologic features, which were subsequently included in a random forest model. Histopathologic correlates were evaluated in representative cases. A total of 91 cases were included with a mean age of 52.9 ± 17.2 years. Nearly all solitary fibrous tumors were located in the anterior or mid orbit (87.5%) and they more commonly demonstrated intralesional heterogeneity on T2-weighted imaging (45.5%) (p < 0.01). Compared with the other tumors, schwannomas tended to be intraconal (66.7%) and were often in the mid or posterior orbit (83.4%) (p < 0.01). Cavernous venous malformations characteristically demonstrated progressive contrast enhancement (93.9%; p < 0.01). Most lesions in all 4 groups were hypointense on T1-weighted imaging (80%-100%; p = 0.14) and only well-circumscribed orbital lymphoma tended to also be hypointense on T2 (81.8%) (p < 0.01). Finally, cases of lymphoma had significantly lower apparent diffusion coefficient ratios (0.9 ± 0.2) (p < 0.001), while the other 3 groups were not significantly different from one another (cavernous venous malformations: 1.8 ± 0.4; schwannomas: 1.8 ± 0.5; and solitary fibrous tumor: 1.6 ± 0.6) (p = 0.739). Key features that aid in the differentiation of these 4 tumors from one another include T2 intensity and homogeneity, early contrast-enhancement pattern, and ADC ratio.

How to manage type 2 curve dilemma in dynamic contrast-enhanced magnetic resonance imaging of the breast: diffusion-weighted imaging or early phase enhancement kinetics?

Type 2 time-intensity curves can indicate both malignant and benign breast lesions in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). To investigate whether diffusion-weighted imaging (DWI) or early phase kinetics of DCE-MRI is practical to discriminate breast masses that depict type 2 curve in DCE-MRI. We retrospectively included 107 lesions in 97 patients with type 2 curves in DCE-MRI. Morphological characteristics, early phase dynamic parameters on DCE-MRI, and apparent diffusion coefficient (ADC) values on DWI were evaluated. Diagnostic thresholds of ADC and early phase maximum enhancement ratio (EPMER) to distinguish between benign and malignant masses were calculated. Strongest predictors of malignancy were determined to build the most effective diagnostic model. DWI, EPMER, and all morphological features were found statistically significant to discriminate malignancy (P <0.05). The thresholds of ADC and EPMER were assigned as 1.0 ×10-3 mm2/s and 72%, respectively. The sensitivity and specificity were 80% and 97% for ADC, and 93% and 60% for EPMER, respectively. Two models were established. Model 1 comprised ADC and the lesion margin. Model 2 consisted of ADC, margin, and EPMER with a high specificity (99%) and positive predictive value (97%). When combined with DWI, early phase wash-in data provide diagnostic improvement of breast masses presenting type 2 curve in the late phase of DCE-MRI, especially for specificity. Future studies are required to support our findings for the need of a cross-validation.

Preoperative Dynamic Contrast-Enhanced and Diffusion-Weighted Breast Magnetic Resonance Imaging Findings for Prediction of Lymphovascular Invasion of the Lesions in Node-Negative Invasive Breast Cancer.

Purpose: Our single-center retrospective study aimed to investigate the relationship between preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) findings and apparent diffusion coefficient (ADC) values and lymphovascular invasion (LVI) status of the lesions in patients with clinically-radiologically lymph node-negative invasive breast cancer. Methods: A total of 250 breast lesions diagnosed in preoperative magnetic resonance imaging were identified. All patients were divided into 2 subgroups: LVI-negative and LVI-positive according to the pathological findings of surgical specimens. The 2 groups' DCE-MRI findings, ADC values, and histopathological results of lesions were compared. Results: LVI was detected in 100 of 250 lesions. Younger age than 45 years and larger lesion size than 20 mm were found to be associated with the presence of LVI (P < .001). High histological and nuclear grade (P = .001), HER2-enriched molecular subtype (P = .001), and Ki-67 positivity (P = .016) were significantly associated with LVI. The LVI positivity rate was significantly higher in the lesions with medium-rapid initial phase kinetic curve and washout delayed phase kinetic curve (P = .001). The presence of LVI was significantly associated with the presence of peritumoral edema, sentinel lymph node metastasis, adjacent vessel sign, and increased whole breast vascularity (P < .001). When diffusion-weighted imaging findings were evaluated, it was determined that tumoral ADC values lower than 1068 × 10-6 mm2/second (P = .002) and peritumoral-tumoral ADC ratios higher than 1.5 (P = .001) statistically increased the probability of LVI. Conclusion: The patient's age, various histopathological and DCE-MRI findings, tumoral ADC value, and peritumoral-tumoral ADC ratio may be useful in the preoperative prediction of LVI status in breast cancer lesions.

Analysis of Diffusion-Weighted and T2-Weighted Imaging in the Prediction of Distinct Granulation Patterns of Somatotroph Adenomas

ObjectiveThe heterogeneity of the somatotroph adenomas, especially for SG and DG subtypes, has attracted great attention in identifying the imaging biomarker of them. The purpose of current study was to compare the diagnostic performance of diffusion-weighted and T2-weighted MRI sequences for preoperatively distinguishing the granulation patterns of somatotroph adenomas. Methods32 patients with clinical diagnosis of somatotroph adenomas from October 2018 to March 2023 were included in this study. Coronal diffusion-weighted imaging (DWI) and T2-weighted MRI sequences data was collected from 3.0T MRI and compared between SG and DG groups. The immunohistochemistry (IHC) was used to confirm the EM pathological subtypes and Ki67 expression levels of somatotroph adenomas postoperatively. ResultsPatients in the SG group had significantly higher signal intensity (SI) ratio of DWI (rDWI) (P<0.001), lower SI ratio of apparent diffusion coefficient (ADC) (rADC) (P<0.001), and higher SI ratio of T2-weighted imaging (rT2) (P=0.011). The combined diagnose index of rDWI and rADC had the highest diagnostic efficiency predicting SG adenomas (sensitivity, 93.3%; specificity, 88.2%; P < 0.001). The rDWI and rADC value had positive and negative correlations with Ki67 index and tumor maximum diameter, respectively. Lower rADC×103 was an independent predictor for SG adenomas. ConclusionsOur results indicated that compared with previously used T2-weighted imaging, the DWI sequence, especially the combined diagnosis index of rDWI and rADC could more efficiently distinguish the granulation patterns of somatotroph adenomas preoperatively.

Advanced multiparametric magnetic resonance imaging of intra-axial posterior fossa tumors

Background: For early treatment planning, it is required that accurate diagnosis of intra-axial posterior fossa tumors can be done. However, imaging diagnosis can be challenging due to analogous magnetic resonance imaging (MRI) features. Aims and Objectives: The aim of the study was to determine the accuracy of advanced MRI sequences such as diffusion-weighted imaging and magnetic resonance spectroscopy (MRS) in diagnosis of intra-axial posterior fossa masses in a tertiary care center. Materials and Methods: This was a retrospective observational study including 43 patients with posterior fossa intra-axial space-occupying tumors. Mean of minimum apparent diffusion coefficient (ADC) values (mean ADCmin) was derived in tumor, and normal white matter regions and ADC ratio was estimated. On MRS, choline/creatinine (Cho/Cr) and Cho/N-acetyl aspartate (NAA) ratios were noted. Receiver operating characteristic (ROC) curve was used to determine cut-off values for mean tumor ADCmin, ADC ratio, Cho/Cr ratio, and Cho/NAA ratio. Results: The most common tumor was medulloblastoma (MB) (30.23%), followed by metastasis (25.58%), pilocytic astrocytoma (16.28%), brainstem glioma (9.3%), hemangioblastoma (6.98%), glioneuronal tumor (6.98%), and ependymoma (4.65%). MBs showed lowest mean tumor ADCmin (0.57±0.12×10-3 mm2/s) and ADC ratio (0.92±0.18) and highest Cho/Cr ratio (8.26±3.9) and Cho/NAA ratio (6.4±1.83) with significant difference from the group of remaining tumors. ROC curve analysis revealed cutoff values of ≤0.71×10-3mm2/s for ADCmin; ≤ 1.02 for ADC ratio; &gt;3.76 for Cho/Cr ratio, and &gt;3.2 for Cho/NAA ratio for the differentiation of MBs from other tumors. Conclusion: The combined use of ADCmin values, ADC ratio, Cho/Cr ratio, and Cho/NAA ratio can help in better non-invasive analysis of similarly appearing intra-axial posterior fossa tumors.

The magnetic resonance imaging and age-adjusted matrix metalloproteinase-7 assist the diagnosis of biliary atresia.

We investigated the utilities of the liver-to-psoas apparent diffusion coefficient ratios (LTPAR) yielded by diffusion-weighted magnetic resonance imaging (DWMRI) and the age-adjusted serum matrix metalloproteinase-7 (MMP-7) for the diagnosis of biliary atresia (BA) in cholestatic infants. In total, 170 cholestatic infants were recruited, of whom 50 (29.41%) were diagnosed with BA after cholestatic workups. The LTPAR and MMP7 levels were assessed. The LTPAR was significantly lower in BA infants, and the age-adjusted MMP7 ratio was significantly higher, compared to other cholestatic infants (both p < 0.001). Receiver operating characteristic curve analysis yielded a cutoff > 0.1ng/mL.day for the age-adjusted MMP-7 ratio, and an LTPAR < 1.01 for the optimal prediction of BA (both p < 0.001). Univariate logistic regression analysis revealed that both an age-adjusted MMP-7 ratio > 0.1ng/mL.day and an LTPAR < 1.01 were significant predictors of BA among cholestatic infants (odds ratio = 30.98 and 13.28; p < 0.001 and < 0.001, respectively). The significance of the age-adjusted MMP-7 ratio and the LTPAR persisted on multivariate logistic regression analysis after adjusting for sex and the serum gamma-glutamyl transferase level (p < 0.001 and < 0.001, respectively). The negative predictive values (NPVs) for BA were 91.49% and 94.17%, respectively, for the LTPAR and age-adjusted MMP-7 ratio. The age-adjusted MMP-7 ratio and the LTPAR are both significant non-invasive predictors of BA. The consideration of both serum and imaging parameters may enhance BA diagnostic performance in cholestatic infants.

Oscillating Gradient Diffusion-Weighted MRI for Risk Stratification of Uterine Endometrial Cancer.

Oscillating gradient diffusion-weighted imaging (DWI) enables elucidation of microstructural characteristics in cancers; however, there are limited data to evaluate its utility in patients with endometrial cancer. To investigate the utility of oscillating gradient DWI for risk stratification in patients with uterine endometrial cancer compared with conventional pulsed gradient DWI. Retrospective. Sixty-three women (mean age: 58 [range: 32-85] years) with endometrial cancer. 3 T MRI including DWI using oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) research sequences. Mean value of the apparent diffusion coefficient (ADC) values for OGSE (ADCOGSE ) and PGSE (ADCPGSE ) as well as the ADC ratio (ADCOGSE /ADCPGSE ) within endometrial cancer were measured using regions of interest. Prognostic factors (histological grade, deep myometrial invasion, lymphovascular invasion, International Federation of Gynecology and Obstetrics [FIGO] stage, and prognostic risk classification) were tabulated. Interobserver agreement was analyzed by calculating the intraclass correlation coefficient. The associations of ADCOGSE , ADCPGSE , and ADCOGSE /ADCPGSE with prognostic factors were examined using the Kendall rank correlation coefficient, Mann-Whitney U test, and receiver operating characteristic (ROC) curve. A P value of <0.05 was statistically significant. Compared with ADCOGSE and ADCPGSE , ADCOGSE /ADCPGSE was significantly and strongly correlated with histological grade (observer 1, τ = 0.563; observer 2, τ = 0.456), FIGO stage (observer 1, τ = 0.354; observer 2, τ = 0.324), and prognostic risk classification (observer 1, τ = 0.456; observer 2, τ = 0.385). The area under the ROC curves of ADCOGSE /ADCPGSE for histological grade (observer 1, 0.92, 95% confidence intervals [CIs]: 0.83-0.98; observer 2, 0.84, 95% CI: 0.73-0.92) and prognostic risk (observer 1, 0.80, 95% CI: 0.68-0.89; observer 2, 0.76, 95% CI: 0.63-0.86) were significantly higher than that of ADCOGSE and ADCPGSE . The ADC ratio obtained via oscillating gradient and pulsed gradient DWIs might be useful imaging biomarkers for risk stratification in patients with endometrial cancer. 3 TECHNICAL EFFICACY: Stage 2.

A Prospective Observational Study of Diagnostic Reliability of Semiquantitative and Quantitative High b-Value Diffusion-Weighted MRI in Distinguishing between Benign and Malignant Lung Lesions at 3 Tesla.

Aim  The aim of this study was to evaluate the usefulness of high b-value diffusion-weighted imaging (DWI) to differentiate benign and malignant lung lesions in 3 Tesla magnetic resonance imaging (MRI). Materials and Methods  Thirty-one patients with lung lesions underwent a high b-value (b= 1000 s/mm 2 ) DW MRI in 3 Tesla. Thirty lesions were biopsied, followed by histopathological analysis, and one was serially followed up for 2 years. Statistical analysis was done to calculate the sensitivity, specificity, and accuracy of different DWI parameters in distinguishing benign and malignant lesions. Receiver operating characteristic (ROC) curves were used to determine the cutoff values of different parameters. Results  The qualitative assessment of signal intensity on DWI based on a 5-point rank scale had a mean score of 2.71 ± 0.75 for benign and 3. 75 ± 0.60 for malignant lesions. With a cutoff of 3.5, the sensitivity, specificity, and accuracy were 75, 86, and 77.6%, respectively. The mean ADC min (minimum apparent diffusion coefficient) value of benign and malignant lesions was 1. 49 ± 0.38 × 10-3 mm 2 /s and 1.11 ± 0.20 ×10-3 mm 2 /s, respectively. ROC curve analysis showed a cutoff value of 1.03 × 10-3 mm 2 /s; the sensitivity, specificity, and accuracy were 87.5, 71.4, and 83.3%, respectively. For lesion to spinal cord ratio and lesion to spinal cord ADC ratio with a cutoff value of 1.08 and 1.38, the sensitivity, specificity, and accuracy were 83.3 and 87.5%, 71.4 and 71.4%, and 80.6 and 83.8%, respectively. The exponential ADC showed a low accuracy rate. Conclusion  The semiquantitative and quantitative parameters of high b-value DW 3 Tesla MRI can differentiate benign from malignant lesions with high accuracy and make it a reliable nonionizing modality for characterizing lung lesions.

Pretreatment diffusion-weighted imaging for prediction of relapsed and refractory primary central nervous system lymphoma.

A subset of primary central nervous system lymphoma (PCNSL) has been shown to undergo an early relapsed/refractory (R/R) period after first-line chemotherapy. This study investigated the pretreatment clinical and MRI features to predict R/R in PCNSL, emphasizing the apparent diffusion coefficient (ADC) values in diffusion-weighted imaging (DWI). This retrospective study investigated the pretreatment MRI features for predicting R/R in PCNSL. Only patients who had undergone complete preoperative and postoperative MRI follow-up studies were included. From January 2006 to December 2021, 52 patients from two medical institutions with a diagnosis of PCNSL were included (median follow-up time, 26.3 months). Among these, 24 (46.2%) had developed R/R (median time to relapse, 13 months). Cox proportional hazard regression analyses were performed to determine hazard ratios for all parameters. Significant predictors of R/R in PCNSL were female sex, complete response (CR) to first-line chemotherapy, and ADC value/ratio (p < 0.05). Cut-off points of ADC values and ADC ratios for prediction of R/R were 0.68 × 10-3 mm2/s and 0.97, with AUCs of 0.78 and 0.77, respectively (p < 0.05). Multivariate Cox proportional hazards analysis showed that failure of CR to first-line chemotherapy and low ADC values (<0.68 × 10-3 mm2/s) were significant risk factors for R/R, with hazard ratios of 5.22 and 14.45, respectively (p < 0.05). Kaplan-Meier analysis showed that lower ADC values and ratios predicted significantly shorter progression-free survival (p < 0.05). Pretreatment ADC values in DWI offer quantitative valuable information for the treatment planning in PCNSL.

Predictive Value of Magnetic Resonance Imaging Multi-parametric Analysis for Malignant Transformation of Sinonasal Inverted Papilloma: A Comprehensive Prediction Model.

Accurate preoperative prediction of sinonasal inverted papilloma (SNIP) malignant transformation is essential and challenging. In this study, 3.0T magnetic resonance was used for qualitative, quantitative, and multi-parametric analysis to evaluate the predictive value of magnetic resonance imaging (MRI) in malignant transformation. The data of patients with SNIP (n=83) or SNIP-transformed squamous cell carcinoma (SNIP-SCC) (n=21) were analysed retrospectively. Univariate analysis and multivariate logistic regression were used to establish models to predict the risk factors for the malignant transformation of SNIP. Receiver operating characteristic (ROC) curves were used to evaluate the ability of independent risk factors and related combination models to predict the malignant transformation of SNIP. Convoluted cerebriform pattern (CCP) mutation, apparent diffusion coefficient ratio (ADCr), and wash-in index (WII) 2 and 3 were independent risk factors for predicting malignant transformation of SNIP, with area under the ROC curve (AUC) values of 0.845, 0.862, 0.727, and 0.704, respectively. The AUC of the quantitative parameter model combined with ADCr and WII 2 and 3 was 0.910 for diagnosing malignant transformation. The AUC of the comprehensive model comprising all independent risk factors was 0.937, with a sensitivity, specificity, and accuracy of 90.48%, 90.36%, and 92.31%, respectively. Compared with assessing independent risk factors of CCP mutation, ADCr and WII, and the quantitative parameter model, the comprehensive model could improve the differential diagnosis ability of SNIP and SNIP-SCC, which provides an important imaging basis for the possible accurate preoperative evaluation of the malignant transformation of SNIP.

Transition Point Estimation Using RC-Filtered Square Wave for Calibration of SAR ADC

Successive-approximation register (SAR) ADCs are susceptible to non-linearities due to capacitor mismatch. This paper proposes a transition points-based calibration of the SAR ADC using an RC-filtered square wave by looking at the histogram of output digital codes to improve the linearity without any additional analog circuitry. The proposed method is validated with an 8-bit SAR ADC fabricated in UMC 180-nm CMOS. The proposed calibration algorithm improves the signal-to-noise and distortion ratio (SNDR) of the 8-bit ADC from 42.87 dB to 46.91 dB, and the spurious-free dynamic range (SFDR) from 51.95 dB to 60.61 dB.

Diagnostic performance of multiparametric magnetic resonance imaging in the differentiation of clear cell renal cell cancer.

This study aimed to evaluate the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI) in the differentiation of renal cell carcinoma (RCC) subtypes. This is a retrospective diagnostic performance study, in which the diagnostic performances of mpMRI features were evaluated to differentiate clear cell RCC (ccRCC) from non-clear cell RCC (non-ccRCC). Adult patients who were evaluated using a 3-Tesla dynamic contrast-enhanced mpMRI before undergoing partial or radical nephrectomy for possible malignant renal tumors were included in the study. Signal intensity change percentages (SICP) between contrast-enhanced phases and pre-administration period for both the tumor and normal renal cortex, and tumor-to-cortex enhancement index (TCEI); tumor apparent diffusion coefficient (ADC) values; tumor-to-cortex ADC ratio; and a scale which was developed according to the tumor signal intensities on the axial fat-suppressed T2-weighted Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE) images were used in ROC analysis to estimate the presence of ccRCC in the patients. The reference test positivity was the histopathologic examination of the surgical specimens. Ninety-eight tumors from 91 patients were included in the study, and 59 of them were ccRCC, 29 were pRCC, and 10 were chRCC. The mpMRI features that had the three highest sensitivity rates were excretory phase SICP, T2-weighted HASTE scale score, and corticomedullary phase TCEI (93.2%, 91.5%, and 86.4%, respectively). However, those with the three highest specificity rates were nephrographic phase TCEI, excretory phase TCEI, and tumor ADC value (94.9%, 94.9%, and 89.7%, respectively). Several parameters on mpMRI showed an acceptable performance to differentiate ccRCC from non-ccRCC.

Preoperative prediction of macrotrabecular-massive hepatocellular carcinoma through dynamic contrast-enhanced magnetic resonance imaging-based radiomics.

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is closely related to aggressive phenotype, gene mutation, carcinogenic pathway, and immunohistochemical markers and is a strong independent predictor of early recurrence and poor prognosis. With the development of imaging technology, successful applications of contrast-enhanced magnetic resonance imaging (MRI) have been reported in identifying the MTM-HCC subtype. Radiomics, as an objective and beneficial method for tumour evaluation, is used to convert medical images into high-throughput quantification features that greatly push the development of precision medicine. To establish and verify a nomogram for preoperatively identifying MTM-HCC by comparing different machine learning algorithms. This retrospective study enrolled 232 (training set, 162; test set, 70) hepatocellular carcinoma patients from April 2018 to September 2021. A total of 3111 radiomics features were extracted from dynamic contrast-enhanced MRI, followed by dimension reduction of these features. Logistic regression (LR), K-nearest neighbour (KNN), Bayes, Tree, and support vector machine (SVM) algorithms were used to select the best radiomics signature. We used the relative standard deviation (RSD) and bootstrap methods to quantify the stability of these five algorithms. The algorithm with the lowest RSD represented the best stability, and it was used to construct the best radiomics model. Multivariable logistic analysis was used to select the useful clinical and radiological features, and different predictive models were established. Finally, the predictive performances of the different models were assessed by evaluating the area under the curve (AUC). The RSD values based on LR, KNN, Bayes, Tree, and SVM were 3.8%, 8.6%, 4.3%, 17.7%, and 17.4%, respectively. Therefore, the LR machine learning algorithm was selected to construct the best radiomics signature, which performed well with AUCs of 0.766 and 0.739 in the training and test sets, respectively. In the multivariable analysis, age [odds ratio (OR) = 0.956, P = 0.034], alpha-fetoprotein (OR = 10.066, P < 0.001), tumour size (OR = 3.316, P = 0.002), tumour-to-liver apparent diffusion coefficient (ADC) ratio (OR = 0.156, P = 0.037), and radiomics score (OR = 2.923, P < 0.001) were independent predictors of MTM-HCC. Among the different models, the predictive performances of the clinical-radiomics model and radiological-radiomics model were significantly improved compared to those of the clinical model (AUCs: 0.888 vs 0.836, P = 0.046) and radiological model (AUCs: 0.796 vs 0.688, P = 0.012), respectively, in the training set, highlighting the improved predictive performance of radiomics. The nomogram performed best, with AUCs of 0.896 and 0.805 in the training and test sets, respectively. The nomogram containing radiomics, age, alpha-fetoprotein, tumour size, and tumour-to-liver ADC ratio revealed excellent predictive ability in preoperatively identifying the MTM-HCC subtype.