Apparent Diffusion Coefficient Ratio Research Articles

Navigating the gray zone: Machine learning can differentiate malignancy in PI-RADS 3 lesions

IntroductionThe objective of this study is to predict the probability of prostate cancer in PI-RADS 3 lesions using machine learning methods that incorporate clinical and mpMRI parameters. MethodsThe study included patients who had PI-RADS 3 lesions detected on mpMRI and underwent fusion biopsy between January 2020 and January 2024. Radiological parameters (Apparent diffusion coefficient (ADC), tumour ADC/contralateral ADC ratio, Ktrans value, periprostatic adipose tissue thickness, lesion size, prostate volume) and clinical parameters (age, body mass index, total prostate specific antigen, free PSA, PSA density, systemic inflammatory index, neutrophil-lymphocyte ratio [NLR], platelet lymphocyte ratio, lymphocyte monocyte ratio) were documented. The probability of prostate cancer prediction in PI-RADS 3 lesions was calculated using 6 different machine-learning models, with the input parameters being the aforementioned variables. ResultsOf the 235 participants in the trial, 61 had malignant fusion biopsy pathology and 174 had benign pathology. Among 6 different machine learning algorithms, the random forest model had the highest accuracy (0.86±0.04; 95% CI 0.85–0.87), F1 score (0.91±0.03; 95% CI 0.91–0.92) and AUC value (0.92±0.06; 95% CI 0.88–0.90). In SHAP analysis based on random forest model, tumour ADC, tumour ADC/contralateral ADC ratio and PSA density were the 3 most successful parameters in predicting malignancy. On the other hand, systemic inflammatory index and neutrophil lymphocyte ratio showed higher accuracy in predicting malignancy than total PSA, age, free PSA/total PSA and lesion size in SHAP analysis. ConclusionAmong the machine learning models we developed, especially the random forest model can predict malignancy in PI-RADS 3 lesions and prevent unnecessary biopsy. This model can be used in clinical practice with multicentre studies including more patients.

The Predictive Role of Mammography, Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging and Diffusion-Weighted Imaging in Hormone Receptor Status of Pure Ductal Carcinoma In Situ Lesions.

The aim of this retrospective study was to analyze the predictive capabilities of preoperative mammography, dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI), and diffusion-weighted imaging (DWI) in determining hormone receptor (HRc) status for pure ductal carcinoma in situ (DCIS) lesions. The study included a total of 79 patients who underwent preoperative mammography (MG) and MRI between December 2018 and December 2023 and were subsequently diagnosed with pure DCIS after surgery. The correlation between MG, DCE-MRI, and DWI features and estrogen receptor (ER) and progesterone receptor (PR) status was examined. Among the lesions, 44 were double HRc-positive (ER and PR-positive), 13 were single HRc-positive (ER-positive and PR-negative or ER-negative and PR-positive) and 22 were double HRc-negative (ER and PR-negative). The presence of symptom (p = 0.029), the presence of comedo necrosis (p = 0.005) and high histological grade (p<0.001) were found to be associated with ER and PR negativity. Amorphous microcalcifications were more commonly observed in the double HRc-negative group, while linear calcifications were more prevalent in both double and single HRc-positive groups (p = 0.020). Non-mass enhancement (NME) with a linear distribution was significantly more common in double HRc-negative lesions (38%), and NME with a segmental distribution in both double (43%) and single (50%) receptor-positive lesions (p = 0.042). Evaluation of DWI findings revealed that a higher lesion-to-normal breast parenchyma apparent diffusion coefficient (ADC) ratio statistically increased the probability of HRc positivity (p = 0.033). Certain clinicopathological, mammography, and MRI features, along with the lesion-to-normal breast parenchyma ADC ratio, can serve as predictors for HRc status in DCIS lesions.

Differentiation between multifocal CNS lymphoma and glioblastoma based on MRI criteria

PurposeDifferentiating between glioblastoma (GB) with multiple foci (mGB) and multifocal central nervous system lymphoma (mCNSL) can be challenging because these cancers share several features at first appearance on magnetic resonance imaging (MRI). The aim of this study was to explore morphological differences in MRI findings for mGB versus mCNSL and to develop an interpretation algorithm with high diagnostic accuracy.MethodsIn this retrospective study, MRI characteristics were compared between 50 patients with mGB and 50 patients with mCNSL treated between 2015 and 2020. The following parameters were evaluated: size, morphology, lesion location and distribution, connections between the lesions on the fluid-attenuated inversion recovery sequence, patterns of contrast enhancement, and apparent diffusion coefficient (ADC) values within the tumor and the surrounding edema, as well as MR perfusion and susceptibility weighted imaging (SWI) whenever available.ResultsA total of 187 mCNSL lesions and 181 mGB lesions were analyzed. The mCNSL lesions demonstrated frequently a solid morphology compared to mGB lesions, which showed more often a cystic, mixed cystic/solid morphology and a cortical infiltration. The mean measured diameter was significantly smaller for mCNSL than mGB lesions (p < 0.001). Tumor ADC ratios were significantly smaller in mCNSL than in mGB (0.89 ± 0.36 vs. 1.05 ± 0.35, p < 0.001). The ADC ratio of perilesional edema was significantly higher (p < 0.001) in mCNSL than in mGB. In SWI / T2*-weighted imaging, tumor-associated susceptibility artifacts were more often found in mCNSL than in mGB (p < 0.001).ConclusionThe lesion size, ADC ratios of the lesions and the adjacent tissue as well as the vascularization of the lesions in the MR-perfusion were found to be significant distinctive patterns of mCNSL and mGB allowing a radiological differentiation of these two entities on initial MRI. A diagnostic algorithm based on these parameters merits a prospective validation.

Longitudinal Imaging of Injured Spinal Cord Myelin and White Matter with 3D Ultrashort Echo Time Magnetization Transfer (UTE-MT) and Diffusion MRI.

Quantitative MRI techniques could be helpful to noninvasively and longitudinally monitor dynamic changes in spinal cord white matter following injury, but imaging and postprocessing techniques in small animals remain lacking. Unilateral C5 hemisection lesions were created in a rat model, and ultrashort echo time magnetization transfer (UTE-MT) and diffusion-weighted sequences were used for imaging following injury. Magnetization transfer ratio (MTR) measurements and preferential diffusion along the longitudinal axis of the spinal cord were calculated as fractional anisotropy or an apparent diffusion coefficient ratio over transverse directions. The area of myelinated white matter was obtained by thresholding the spinal cord using mean MTR or diffusion ratio values from the contralesional side of the spinal cord. A decrease in white matter areas was observed on the ipsilesional side caudal to the lesions, which is consistent with known myelin and axonal changes following spinal cord injury. The myelinated white matter area obtained through the UTE-MT technique and the white matter area obtained through diffusion imaging techniques showed better performance to distinguish evolution after injury (AUCs > 0.94, p < 0.001) than the mean MTR (AUC = 0.74, p = 0.01) or ADC ratio (AUC = 0.68, p = 0.05) values themselves. Immunostaining for myelin basic protein (MBP) and neurofilament protein NF200 (NF200) showed atrophy and axonal degeneration, confirming the MRI results. These compositional and microstructural MRI techniques may be used to detect demyelination or remyelination in the spinal cord after spinal cord injury.

Noninvasive prediction of BRAF V600E mutation status of pleomorphic xanthoastrocytomas with MRI morphologic features and diffusion-weighted imaging

ObjectivesSeeking a noninvasive predictor for BRAF V600E mutation status of pleomorphic xanthoastrocytomas (PXAs) is essential for their prognoses and therapeutic use of BRAF inhibitors. We aimed to noninvasively diagnose BRAF V600E-mutated PXAs using MRI morphologic, DWI and clinical parameters.MethodsThe clinical findings, anatomical MRI characteristics, and diffusion parameters of 36 pathologically confirmed PXAs were retrospectively analyzed, and BRAF V600E-mutated (n = 16) and wild-type (n = 20) groups were compared. A binary logistic-regression analysis was performed, and a ROC curve was calculated to determine the independent predictors of BRAF V600E mutation status, diagnostic accuracy, and optimal cut-off value.ResultsA comparison of findings between groups showed that BRAF V600E-mutated PXAs were more frequent in children and young adults (≤ 35 years; P = 0.042) who often had histories of seizures (P = 0.004). Furthermore, BRAF V600E-mutated PXAs generally presented as solitary masses (P = 0.024), superficial locations with meningeal attachment (P < 0.001), predominantly cystic with mural nodules (P = 0.005), and had greater minimal ADC ratio (ADCratio) values of the tumor and peritumoral edema (P < 0.001). Binary logistic regression showed that age ≤ 35 years, solitary mass, superficial locations with meningeal attachment, and a greater minimal ADCratio of the tumor were independent predictors of BRAF V600E-mutated PXAs. The combination of all four independent predictors resulted in the highest sensitivity (100%) and specificity (90%), with AUC = 0.984.ConclusionThe BRAF V600E mutation status of PXAs could be noninvasively predicted using clinical and MRI characteristics.Critical relevance statementThe noninvasive diagnostic criteria for BRAF V600E-mutated PXAs could offer guidance for the administration of BRAF V600E mutation inhibitors in the future.

The role of MRI biomarkers in evaluation of symptomatic pineal cysts – a retrospective analysis

BackgroundOur aim was to determine whether the Apparent Diffusion Coefficient is able to predict the presence of a symptomatic pineal cyst by detecting cerebral edema.MethodsWe retrospectively analyzed MRIs of 45 patients with pineal cysts before and after resection and 51 patients without pineal cysts, comparing ADC values of thalamus, central, periventricular and subcortical white matter. Furthermore we evaluated cyst size and morphology and analyzed its correlation to ADC values in corresponding patients.ResultsDifferences between patients with symptomatic pineal cyst and control group were not significant (p = 0.200 – 0.968). ADC ratios did not change significantly after resection of the cyst (p = 0.575 – 0.862). Cyst size showed no significant correlation to ADC ratios (p = 0.071 – 0.918). Raw data analyses revealed more significance, especially periventricularly and in central white matter, which resulted in significant interhemispheric differences in ADC ratios in both subgroups (p < 0.001 and p = 0.031). MRI of 1.5T showed consistently higher values than 3T but mostly insignificant.ConclusionOur analysis revealed no evidence that pineal cysts lead to intracerebral edema caused by venous compression. Since variability was higher than the differences seen, ADC sequences do not appear to be an appropriate diagnostic tool for symptomatic pineal cysts.

Correlation of ADC values of adult brain tumors with the diagnosis and pathological grade: A cross-sectional multicenter study.

Brain tumors are common, requiring physicians to have a precise understanding of them for accurate diagnosis and treatment. Considering that various histological tumor types present different cellularity, we conducted this research to examine the role of apparent diffusion coefficient (ADC) values in the differential diagnosis and pathologic grading of brain tumor types. In this cross-sectional study, we gathered pathology reports of histological samples of adult brain tumors. The tissue sample of brain tumors were examined histologically by a pathologist. The magnetic resonance imaging data of these patients were interpreted by a neuroradiologist. The measured ADC values and ADC ratios were calculated. Standard mean ADC values were expressed as 10- 6 mm2/s. The findings were compared according to the histological diagnosis of each tumor. Sixty-eight patients were included in the study: 34 (50%) were male, and 34 (50%) were female. The average age of the patients was 51.69 + 16.40 years. In the examination of tumor type, 16 (23.5%) were astrocytoma, 9 (13.2%) were oligodendroglioma, 20 (29.4%) were glioblastoma, 4 (5.9%) were medulloblastoma, and 19 (27.9%) were metastatic tumors. the average value of ADC was statistically significantly different according to the pathological type of tumor (p < 0.001). The two-by-two comparison of average ADC among tumor types revealed significant differences, except for oligodendroglioma and glioblastoma (p-value = 0.87) and glioblastoma and medulloblastoma (p-value = 0.347). The average value of ADC and ADC ratio was statistically significantly different according to the pathological grade of the tumor (p < 0.001). In the two-by-two comparison of average ADC between all pathological grades of the tumor showed a significance difference except for Grade I and Grade II (p-value = 0.355). The mean value of ADC and ADC ratio for glioblastoma and metastatic tumors showed no significant difference. The assessment of brain tumor grade through ADC examination will help to estimate prognosis and devising suitable therapeutic strategies.

Prognostic implications of distinctive imaging characteristics in primary intracranial germ cell tumors: A retrospective analysis

PurposePrimary central nervous system (CNS) germ cell tumors (GCTs) are rare brain tumors that encompass two subtypes: germinomas and non-germinomatous germ cell tumors (NGGCTs), NGGCTs have less favorable outcome and require multi-modality treatment. Biopsy is recommended for disease diagnosis, the specimen may not adequately reflect the entire tumor. This study aimed to assess distinct imaging characteristics to differentiate between GCT subgroups and to identify possible initial image and subgroup features that influence survival. MethodThis retrospective study, conducted from January 2006 to March 2023, analyzed patient data and MRI findings of primary CNS GCTs. It evaluated tumor characteristics including cysts, seeding, multifocality, and hemorrhage. Tumor volumes and apparent diffusion coefficient (ADC) values of both tumoral and normal-appearing contralateral white matter were measured. These factors were correlated with overall and 5-year survival rates. ResultsThis study included 51 participants with CGTs, comprising 19 germinoma and 32 NGGCTs cases. GCTs with hemorrhage had worse overall (P = 0.03) and 5-year (P = 0.01) survival rates. No survival difference between germinoma and non-hemorrhagic NGGCT. NGGCTs were more likely to bleed (P < 0.001) than germ cell tumor, especially those with choriocarcinoma or yolk sac tumor components (P = 0.001). The ADC ratios of germinomas were significantly lower than those of NGGCTs (P = 0.03 for whole tumor; P < 0.01 or solid part), The ADC ratios of choriocarcinoma were also lower than mixed tumor (P = 0.01; P = 0.02). ConclusionHemorrhage indicates worse prognosis. Intratumoral hemorrhage and ADC ratios differentiate germinoma from NGGCTs. Larger cohorts and advanced MR techniques are needed for future study.

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-centre 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 peritumoural 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 tumoural ADC values lower than 1068 × 10-6 mm2/second (P = .002) and peritumoural-tumoural 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, tumoural ADC value, and peritumoural-tumoural 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.