Mean Apparent Diffusion Coefficient Research Articles

Can maximum, mean or minimum ADC values of the cervix-parametrium boundary estimate parametrial invasion for cervical carcinoma?

Purpose: Diffusion weighted imaging (DWI), which is quantified by apparent diffusion coefficient (ADC), can predict tissue microstructure. It has become an essential part of the gynecological magnetic resonance imaging (MRI) protocol. In our study it was aimed to evaluate the value of the maximum, mean, and minimum ADC values of the cervix-parametrium boundary to estimate parametrial invasion for cervix carcinoma. Material and Method: Totally 50 patients with cervical carcinoma, 18 of which had no parametrial invasion (4811-year-old) and 32 had parametrial invasion (5812-year-old) according to conventional T2 weighted imaging were enrolled. Maximum, mean, and minimum ADC values of cervix-parametrium boundary of primary tumors were statistically compared between the groups without and with parametrial invasion. The diagnostic performances of the maximum, mean and minimum ADC values were evaluated by ROC analysis in terms of estimating parametrial invasion. Results: The mean maximum, mean and minimum ADC values were lower for the patients with parametrial invasion. However, only the minimum ADC values had statistically significant differences between the groups. ROC analysis showed an AUC value of 0.726 for minimum ADC in estimating parametrial invasion. A minimum ADC cut-off value of 0.553x10-3 mm2/s had a sensitivity of 63%, specificity of 73%, negative predictive value of 52% and positive predictive value of 80% and accuracy of 66%. Conclusions: ADC values can be applied for the determination of parametrial invasion of cervical carcinoma. Lower minimum ADC values obtained from cervix-parametrium boundary of primary cervical carcinoma may help parametrial invasion. Especially positive predictive value of the cervix-parametrium boundary ADC is remarkable.

The impact of diffusion and perfusion-weighted imaging on glioma grading

Abstract Objectives Determining the grade of a glioma is extremely important for treatment planning and prognosis prediction. The study aimed to evaluate the usefulness of multiparametric perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI) in preoperative glioma grading. Methods In this retrospective study, 63 individuals with brain tumors histologically confirmed, of which 23 had low-grade gliomas (LGGs) and 40 had high-grade gliomas (HGGs) were involved. We conducted this paper on apparent diffusion coefficient (ADC) maps using the entire tumor volume method, allowing us to use all ADC values of the tumor. Small-sample regions of interest (ROIs) were drawn to collect parameters of relative cerebral blood flow (rCBF), cerebral blood flow (CBF), and relative cerebral blood volume (rCBV), from both the tumor core and peritumoral edema. The PWI and DWI metrics were compared to identify the most accurate distinguishing HGGs and LGGs, analyze receiver operating characteristics (ROC), and evaluate the diagnostic performance using solitary parameters and combined. Results In diffusion MRI, there were significant differences in minimum ADC and mean ADC between LGGs and HGGs (p<0.05), with the larger area under the curve (AUC) of 0.898 found for mean ADC at a cut-off value of 1.275, with sensitivity of 82.6 % and specificity of 90 %. The maximum ADC value did not differ significantly (p>0.05). All perfusion parameters in both the tumor core and peritumoral edema area were significantly greater values in cases of HGG compared to LGG (p<0.001), with the highest AUC of 0.946 found for solid tumor rCBV value (rCBVt), the cut-off is 3.585, sensitivity of 85 % and specificity of 100 %. Combining mean ADC and rCBVt provided an excellent AUC of 0.975, a sensitivity of 92.5 %, and a specificity of 91.3 % for differentiating between HGGs and LGGs. Conclusions Perfusion and diffusion MRI are valuable in discriminating between high-grade and low-grade gliomas, with the major criterion in the decision-making process being the combined mean ADC and rCBVt parameters.

Apparent diffusion coefficient and tissue stiffness are associated with different tumor microenvironment features of hepatocellular carcinoma.

To investigate associations between tissue diffusion, stiffness, and different tumor microenvironment features in resected hepatocellular carcinoma (HCC). Seventy-two patients were prospectively included for preoperative magnetic resonance (MR) diffusion-weighted imaging and MR elastography examination. The mean apparent diffusion coefficient (ADC) and stiffness value were measured on the central three slices of the tumor and peri-tumor area. Cell density, tumor-stroma ratio (TSR), lymphocyte-rich HCC (LR-HCC), and CD8 + T cell infiltration were estimated in resected tumors. The interobserver agreement of MRI measurements and subjective pathological evaluation was assessed. Variables influencing ADC and stiffness were screened with univariate analyses, and then identified with multivariable linear regression. The potential relationship between explored imaging biomarkers and histopathological features was assessed with linear regression after adjustment for other influencing factors. Seventy-two patients (male/female: 59/13, mean age: 56 ± 10.2 years) were included for analysis. Inter-reader agreement was good or excellent regarding MRI measurements and histopathological evaluation. No correlation between tumor ADC and tumor stiffness was found. Multivariable linear regression confirmed that cell density was the only factor associated with tumor ADC (Estimate = -0.03, p = 0.006), and tumor-stroma ratio was the only factor associated with tumor stiffness (Estimate = -0.18, p = 0.03). After adjustment for fibrosis stage (Estimate = 0.43, p < 0.001) and age (Estimate = 0.04, p < 0.001) in the multivariate linear regression, intra-tumoral CD8 + T cell infiltration remained a significant factor associated with peri-tumor stiffness (Estimate = 0.63, p = 0.02). Tumor ADC surpasses tumor stiffness as a biomarker of cellularity. Tumor stiffness is associated with tumor-stroma ratio and peri-tumor stiffness might be an imaging biomarker of intra-tumoral immune microenvironment. Tissue stiffness could potentially serve as an imaging biomarker of the intra-tumoral immune microenvironment of hepatocellular carcinoma and aid in patient selection for immunotherapy. Apparent diffusion coefficient reflects cellularity of hepatocellular carcinoma. Tumor stiffness reflects tumor-stroma ratio of hepatocellular carcinoma and is associated with tumor-infiltrating lymphocytes. Tumor and peri-tumor stiffness might serve as imaging biomarkers of intra-tumoral immune microenvironment.

The performance of the node reporting and data system 1.0 (Node-RADS) and DWI-MRI in staging patients with cervical carcinoma according to the new FIGO classification (2018).

To evaluate the diagnostic accuracy of the Node-RADS score and the utility of apparent diffusion coefficient (ADC) values in predicting metastatic lymph nodes (LNs) involvement in cervical cancer (CC) patients using magnetic resonance imaging (MRI). The applicability of the Node RADS score across three readers with different years of experience in pelvic imaging was also assessed. Among 140 patients, 68 underwent staging MRI, neoadjuvant chemotherapy and radical surgery, forming the study cohort. Node-RADS scores of the main pelvic stations were retrospectively determined to assess LN metastatic likelihood and compared with the histological findings. Mean ADC, relative ADC (rADC), and correct ADC (cADC) values of LNs classified as Node-RADS ≥ 3 were measured and compared with histological reports, considered as gold standard. Sensitivity, specificity, positive and negative predictive values (PPVs and NPVs), and accuracy were calculated for different Node-RADS thresholds. Node RADS ≥ 3 showed a sensitivity of 92.8% and specificity of 72.5%. Node RADS ≥ 4 yielded a sensitivity of 71.4% and specificity of 100%, while Node RADS 5 yielded 42.9% and 100%, respectively. The diagnostic performance of mean ADC, cADC and rADC values from 78 LNs with Node-RADS score ≥ 3 was assessed, with ADC demonstrating the highest area under the curve (AUC 0.820), compared to cADC and rADC values. The Node-RADS score provides a standardized LNs assessment, enhancing diagnostic accuracy in CC patients. Its ease of use and high inter-observer concordance support its clinical utility. ADC measurement of LNs shows promise as an additional tool for optimizing patient diagnostic evaluation.

Effects of Photon versus Carbon-Ion Irradiation in the Rat Cervical Spinal Cord - a Serial T2 and Diffusion-weighted Magnetic Resonance Imaging Study.

Carbon-ion irradiation is increasingly used at the skull base and spine near the radiation-sensitive spinal cord. To better characterize the invivo radiation response of the cervical spinal cord, radiogenic changes in the high-dose area were measured in rats using magnetic resonance imaging (MRI) diffusion measurements in comparison to conventional photon irradiations. In this longitudinal MRI study, we examined the gray matter (GM) of the cervical spinal cord in 16 female Sprague-Dawley rats after high-dose photon (n = 8) or carbon-ion (12C) irradiation (n = 8) and in 6 sham-exposed rats until myelopathy occurred. The differences in the diffusion pattern of the GM of the cervical spinal cord were examined until the endpoint of the study, occurrence of paresis grade II of both forelimbs was reached. In both radiation techniques, the same order of the occurrence of MR-morphological pathologies was observed - from edema formation to a blood spinal cord barrier (BSCB) disruption to paresis grade II of both forelimbs. However, carbon-ion irradiation showed a significant increase of the mean apparent diffusion coefficient (ADC; P = 0.031) with development of a BSCB disruption in the GM. Animals with paresis grade II as a late radiation response had a highly significant increase in mean ADC (P = 0.0001) after carbon-ion irradiation. At this time, a tendency was observed for higher mean ADC values in the GM after 12C irradiation as compared to photon irradiation (P = 0.059). These findings demonstrated that carbon-ion irradiation leads to greater structural damage to the GM of the rat cervical spinal cord than photon irradiation due to its higher linear energy transfer (LET) value.

The Apparent Diffusion Coefficient of the Paraspinal and Psoas Muscles Are of Prognostic Relevance in Patients With Hepatocellular Carcinoma Undergoing Transarterial Radioembolization.

Transarterial radioembolization (TARE) is a treatment option for early or intermediate stage hepatocellular carcinoma (HCC). Sarcopenia is defined as loss of muscle strength and quality which can be estimated by imaging modalities and has been associated with prognosis and treatment response in HCC patients. Apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) can reflect the tissue composition and might be better to determine muscle changes of sarcopenia than the standard method of computed tomography (CT). The present study sought to elucidate ADC values of the abdominal wall muscles as a prognostic factor in patients undergoing TARE. A retrospective analysis was performed between 2016 and 2020. Overall, 52 patients, 9 women (17.3%) and 43 men (82.7%), with a mean age of 69±8.5 years were included into the analysis. In every case, the first pre-interventional magnetic resonance imaging (MRI) including DWI was used to measure the ADC values of paraspinal and psoas muscle. The 12-month survival after TARE was used as the primary study outcome. Overall, 40 patients (76.9%) of the patient cohort died within the 12-month observation period. Mean overall survival was 10.9 months after TARE for all patients. Mean ADC values for all muscles were 1.31±0.13×10-3mm2/s. The ADC values of the paraspinal muscles were statistically significantly higher compared to the ADC values of the psoas muscles (p=0.0031). A positive correlation was identified between mean ADC and the thrombocyte count (r=0.37, p=0.005) and serum bilirubin (r=-0.30, p=0.03). In the multivariate Cox regression analysis, the mean ADC values of all muscles were associated with the survival after 12 months (HR=0.98, 95% CI=0.97-0.99, p=0.04). ADC values of the abdominal wall muscles could be used as a prognostic biomarker in patients with HCC undergoing TARE. These preliminary results should be confirmed by further studies using external validation cohorts and other treatment modalities.

Abstract PS05-04: [89Zr]Trastuzumab-PET/MRI to Characterize HER2+ Breast Cancer: A Quantitative Approach on Tumor Heterogeneity

Abstract Introduction: Molecular imaging of human epidermal receptor 2 (HER2) aims to overcome limitations of traditional HER2 assessment through biopsy, including invasiveness and inability to detect intra and inter-tumoral spatial heterogeneity. Prior human studies suggest that [89Zr]Trastuzumab-positron emission tomography (PET) imaging can effectively differentiate HER2 lesions (Dehdashti et al, Breast Cancer Res. Treat. 2018). Commonly, CT complements PET for anatomical reference, however, integrating MRI enables the sensitivity of soft-tissue contrast required for anatomic and morphological breast imaging and can provide for quantitative multiparametric characterization. Diffusion weighted-MRI (DW-MRI) contributes to tumor characterization by assessing intratumoral cellularity via the apparent diffusion coefficient (ADC), and can be combined with molecular expression from HER2-PET. We present preliminary results in 13 patients with HER2 PET/MRI to define tumor and normal tissue imaging metrics. Methods: A phase II clinical trial assessing the feasibility of [89Zr]trastuzumab-PET with simultaneous quantitative DW-MRI to enhance understanding of tumor heterogeneity in patients with HER2-positive metastatic breast cancer. 13 patients (ages 40-70; mean 60) with HER2-positive breast cancer based on prior biopsy underwent whole-body [89Zr]trastuzumab-PET/MR imaging (5 ± 1 days post-injection of radiopharmaceutical) during the course of HER2-directed therapy. Normal organ and tumor regions of interest (ROI) were identified on concurrently acquired whole-body T1-weighted MRI for ADC (cellularity) and standardized uptake value (SUV, PET uptake) mean quantification. Tumor presence was confirmed via bone scintigraphy, FDG-PET/CT, or contrast-enhanced MRI. Non-parametric T-tests compared lesions to normal organs. Lesions greater than 30 mm in diameter underwent multiparametric intratumoral habitat analysis. Using the median HER2 values, tumors were evaluated for heterogeneity of high and low HER2 expression in conjunction with ADC. Long-term treatment response evaluation is ongoing. Results: Mean [89Zr]trastuzumab uptake, SUV, and ADC values for normal tissue were summarized in Table 1. All tumors demonstrated higher overall uptake of [89Zr]trastuzumab (bone: p=0.019, brain: p=0.014, breast: p=0.069, juxtapulmonary: p=0.026) and increased ADCmean values (bone: p=0.002, brain: p=0.5, breast: p=0.03, juxtapulmonary: p=0.037), in comparison to matched normal organs. Notably, one of five patients with a breast lesion, who completely responded to HER2 targeted therapy, exhibited the highest breast lesion SUVmean. Brain and lymph node lesions demonstrated intratumoral heterogeneity of HER2 expression. Conclusion: Our study demonstrates the potential value of quantitative MRI along with molecular imaging to characterize metastatic HER2+ breast cancer and evaluate intratumoral heterogeneity. We underscore the importance of standardizing processing techniques and contribute to this effort by summarizing [89Zr]trastuzumab uptake and cellularity values of normal physiological uptake. Higher SUVmean and ADC mean values observed in lesions, compared to normal tissue, highlight their potential roles in intratumoral classification. While studies have shown the utility of [89 Zr]trastuzumab-PET/CT, our findings demonstrate that integrated DW-MRI can aid in tumor classification. Table 1: Physiological 89Zr-Trastuzumab Uptake (SUVmean) and Apparent Diffusion Coefficient (ADCmean) in Healthy Tissues Citation Format: Ameer Mansur, Moozhan Nikpanah, Johnathan McConathy, Erica Stringer-Reasor, Gabrielle Rocque, Ahmed Elkhanany, Katia Khoury, Nusrat Jahan, Suzanne Lapi, Anna Sorace. [89Zr]Trastuzumab-PET/MRI to Characterize HER2+ Breast Cancer: A Quantitative Approach on Tumor Heterogeneity [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS05-04.

Abstract PS05-08: Restriction Spectrum Imaging MRI for automated evaluation of response to neoadjuvant therapy in breast cancer

Abstract Introduction: Dynamic contrast-enhanced MRI (DCE) is currently used to evaluate neoadjuvant therapy response of breast cancer (1). However, DCE requires expert radiologist readers to assess the change in longest tumor dimension during therapy, as well as administration of Gadolinium contrast agents. One MRI modality that does not require contrast agents is diffusion-weighted MRI (DWI), a method that detects the microscopic diffusion of water molecules. However, the commonly used DWI method apparent diffusion coefficient (ADC) is not fully optimised in the breast (2). The purpose of the current study was to evaluate the recent DWI method Restriction Spectrum Imaging (RSI) (2) to automatically monitor breast tumor size during neoadjuvant therapy. Methods: Twenty-seven women underwent 3T MRI at four time points during therapy at University of California San Diego; 17 received all four scans (see Table 1 for patient details). Inclusion criteria included biopsy-proven unilateral invasive breast cancer ≥2.5 cm (defined on clinical examination/imaging) with indication for neoadjuvant therapy. The therapy used was primarily paclitaxel (+/-experimental agent) followed by anthracycline. The MRI protocol included Gadolinium DCE and DWI (b-values 0, 500, 1500, 4000 s/mm2); TE/TR = 82/9000 ms. ADC was calculated using b-values &amp;lt; 1000 s/mm2 while signal from all available b-values were fitted to the previously-developed three-component RSI model (2). The tumor size by RSI was assessed against manual DCE tumor size and mean ADC values. Prediction of therapy response during therapy and residual tumor post-therapy were assessed using non-pathological complete response (non-pCR) as endpoint. pCR was defined as ypT0/is or ypN0. Results: Ten patients experienced pCR. Prediction of non-pCR by ROC AUC at the early-therapy time point was 0.65 for RSI, 0.64 for DCE and 0.45 for ADC (Table 2). Prediction of post-therapy residual tumor is given in Table 3. Discussion: The novel RSI cancer tissue classifier predicted response to neoadjuvant therapy after only 19 days. RSI could also identify 71% of cases with residual tumor at surgery with 90% specificity post-therapy. RSI performance was similar to performance by standard MRI by manual tumor measurement on DCE. In contrast to standard-of-care MRI by using DCE and ADC that requires manual user input, the RSI classifier is automatic. This suggests that RSI may aid to cost-efficiently evaluate neoadjuvant therapy of breast cancer, with the aim to help guide clinical decision-making and enable tailored therapy regimens.

Diffusion-Weighted Imaging for Skin Pathologies of the Breast-A Feasibility Study.

Several breast pathologies can affect the skin, and clinical pathways might differ significantly depending on the underlying diagnosis. This study investigates the feasibility of using diffusion-weighted imaging (DWI) to differentiate skin pathologies in breast MRIs. This retrospective study included 88 female patients who underwent diagnostic breast MRI (1.5 or 3T), including DWI. Skin areas were manually segmented, and the apparent diffusion coefficients (ADCs) were compared between different pathologies: inflammatory breast cancer (IBC; n = 5), benign skin inflammation (BSI; n = 11), Paget's disease (PD; n = 3), and skin-involved breast cancer (SIBC; n = 11). Fifty-eight women had healthy skin (H; n = 58). The SIBC group had a significantly lower mean ADC than the BSI and IBC groups. These differences persisted for the first-order features of the ADC (mean, median, maximum, and minimum) only between the SIBC and BSI groups. The mean ADC did not differ significantly between the BSI and IBC groups. Quantitative DWI assessments demonstrated differences between various skin-affecting pathologies, but did not distinguish clearly between all of them. More extensive studies are needed to assess the utility of quantitative DWI in supplementing the diagnostic assessment of skin pathologies in breast imaging.

Inter- and Intra-Patient Repeatability of Radiomic Features from Multiparametric Whole-Body MRI in Patients with Metastatic Prostate Cancer.

(1) Background: We assessed the test-re-test repeatability of radiomics in metastatic castration-resistant prostate cancer (mCPRC) bone disease on whole-body diffusion-weighted (DWI) and T1-weighted Dixon MRI. (2) Methods: In 10 mCRPC patients, 1.5 T MRI, including DWI and T1-weighted gradient-echo Dixon sequences, was performed twice on the same day. Apparent diffusion coefficient (ADC) and relative fat-fraction-percentage (rFF%) maps were calculated. Per study, up to 10 target bone metastases were manually delineated on DWI and Dixon images. All 106 radiomic features included in the Pyradiomics toolbox were derived for each target volume from the ADC and rFF% maps. To account for inter- and intra-patient measurement repeatability, the log-transformed individual target measurements were fitted to a hierarchical model, represented as a Bayesian network. Repeatability measurements, including the intraclass correlation coefficient (ICC), were derived. Feature ICCs were compared with mean ADC and rFF ICCs. (3) Results: A total of 65 DWI and 47 rFF% targets were analysed. There was no significant bias for any features. Pairwise correlation revealed fifteen ADC and fourteen rFF% feature sub-groups, without specific patterns between feature classes. The median intra-patient ICC was generally higher than the inter-patient ICC. Features that describe extremes in voxel values (minimum, maximum, range, skewness, and kurtosis) showed generally lower ICCs. Several mostly shape-based texture features were identified, which showed high inter- and intra-patient ICCs when compared with the mean ADC or mean rFF%, respectively. (4) Conclusions: Pyradiomics texture features of mCRPC bone metastases varied greatly in inter- and intra-patient repeatability. Several features demonstrated good repeatability, allowing for further exploration as diagnostic parameters in mCRPC bone disease.

Diffusion Mri in Intracranial Hypertension: Quantitative Assesment.

Intracranial hypertension (IH) is a neurological disease that is characterized by increased intracranial pressure. Idiopathic intracranial hypertension (IIH) is characterized by an increase in intracranial pressure without an underlying neuroradiological cause (1-3). The IH that is associated with a reason such as a mass, hydrocephalus, or drug use, is referred to as secondary intracranial hypertension (SIH). We aimed to detect determine whether the increased intracranial pressure causes a change in the diffusion values of brain in the diffusion MRI images. The study includes 24 consecutive patients that were diagnosed with IIH and 18 consecutive patients that were diagnosed with secondary intracranial hypertension (SIH). The control group included 24 patients. Measurement of apparent diffusion coefficient (ADC) was performed using DWI sections obtained from subcortical white matter and the cortex of the frontal lobe in the basal ganglia plane, caudate nucleus head, thalamus, the posterior leg of the internal capsule, corpus callosum splenium; in the centrum semiovale plane, from the central white matter region. with 1.5T MRI using b=500s/mm2 and b=1000s/mm2 values both in patients and control groups. Mean ADC values were compared between IIH, SIH patients and control groups. The ADC values from the head of the caudate nucleus and the cortex were significantly higher in the IIH group, compared to the control group. When the ADC values of the SIH and control groups were compared, it was found that some of the ADC measurements (subcortical white matter, cortex and semioval center) were significantly different. The comparison of the IIH and the SIH groups revealed that the ADC measurements central white matter in the centrum semiovale, the subcortical white matter and the posterior leg of the internal capsule were significantly different. Conclusıons: We have found increased diffusion IIH and SIH patients, which supports the development of brain edema. Even though the mechanism of the brain edema in IIH are not entirely clear, it is thought that the mechanism is different from the brain edema caused by a mass or a sinus thrombosis.

Association between programmed cell death ligand-1 expression in patients with cervical cancer and apparent diffusion coefficient values: a promising tool for patient´s immunotherapy selection.

To investigate the associations between apparent diffusion coefficient (ADC) values extracted from three different region of interest (ROI) position approaches and programmed cell death ligand-1 (PD-L1) expression, and evaluate the performance of the nomogram established based on ADC values and clinicopathological parameters in predicting PD-L1 expression in cervical cancer (CC) patients. Through retrospective recruitment, a training cohort of 683 CC patients was created, and a validation cohort of 332 CC patients was prospectively recruited. ROIs were delineated using three different methods to measure the mean ADC (ADCmean), single-section ADC (ADCss), and the minimum ADC of tumors (ADCmin). Logistic regression was employed to identify independent factors related to PD-L1 expression. A nomogram was drawn based on ADC values combined with clinicopathological features, its discrimination and calibration performances were estimated using the area under the curve (AUC) of receiver operating characteristic and calibration curve. The clinical benefits were evaluated by decision curve analysis. The ADCmin independently correlated with PD-L1 expression. The nomogram constructed with ADCmin and other independent clinicopathological-related factors: FIGO staging, pathological grade, parametrial invasion, and lymph node status demonstrated excellent diagnostic performance (AUC = 0.912 and 0.903, respectively), good calibration capacities, and greater net benefits compared to the clinicopathological model in both the training and validation cohorts. ADCmin independently correlated PD-L1 expression, and the nomogram established with ADCmin and clinicopathological independent prognostic factors had a strong predictive performance for PD-L1 expression, thereby serving as a promising tool for selecting cases eligible for immunotherapy. The minimum ADC can serve as a reliable imaging biomarker related to PD-L1 expression; the established nomogram combines the minimum ADC and clinicopathological factors that can assist clinical immunotherapy decisions.

Using Apparent Diffusion Coefficient (ADC) of Endometrial Cancer MRI to Determine P53 Molecular Subtypes.

Endometrial Cancer (EC) is a highly heterogeneous cancer comprising both histological and molecular subtypes. Using a non-invasive modality method to trigger these subtypes as early as possible can aid clinicians in establishing individualized treatment. The study aimed to clarify the value of the Apparent Diffusion Coefficient (ADC) of EC MRI in determining molecular subtypes. We retrospectively recruited 109 patients with pathologically proven EC (78 endometrioid cancers and 31 non-endometrioid cancers) with available molecular classification from a tertiary centre. MRI was prospectively performed a month prior to surgery; images were blindly interpreted by two experienced radiologists with consensus reading. The ADC value was measured by an experienced radiologist on the commercially available processing workstation. Interoperator measurement consistency was calculated. Our sample comprised 17 PLOE, 32 MSI-H, 31 NSMP, and 29 P53abn ECs. Clinical information did not differ significantly among the groups. The maximum diameter and volume of the lesions differed among the groups. The ADC value in the maximal area (ADCarea) or region of interest (ROI, ADCroi) in the P53abn group was higher than that in the other groups (894.0 ±12.6 and 817.5 ± 83.3 x10-6 mm2/s). The ADC mean values were significantly different between the P53abn group and the other groups (P = 0.000). The nomogram showed the highest discriminative ability to distinguish P53abn EC from other types (AUC: 0.859). Our results have suggested the quantitative MR characteristics (ADC values) derived from preoperative EC MRI to provide useful information in preoperatively determining P53abn cancer.

Comparison of MRI findings of hypothalamic-optic chiasmatic gliomas and craniopharyngiomas.

Differential diagnosis of hypothalamic-optic chiasmatic gliomas (HOCGs) and craniopharyngiomas on magnetic resonance imaging (MRI) can be quite challenging. To compare the MRI features of HOCGs and cranipharyngiomas. Patients diagnosed with HOCG or craniopharyngioma in histopathological evaluation between 2012 and 2022 and who underwent preoperative contrast-enhanced brain MRI were included. Various MRI features were retrospectively evaluated for each lesion: T2-weighted imaging and fluid attenuation inversion recovery hyperintensity, calcification, cystic change, T1-weighted (T1W) imaging hyperintensity of the cystic component, hemorrhage, involvement of sellar, suprasellar or other adjacent structures, lobulated appearance, presence of hydrocephalus, and contrast enhancement pattern. Apparent diffusion coefficient (ADC) values were also evaluated and compared. Among 38 patients included, 13 (34%) had HOCG and 25 (66%) had craniopharyngioma. Craniopharyngiomas had a significantly higher rate of cystic changes, calcification, and T1W imaging hyperintensity of the cystic component than HOCGs (P <0.05). Of HOCGs, 92% had chiasm involvement, 23% had optic nerve involvement, and 31% had brain stem involvement. On the other hand, chiasm involvement was observed in 8% of craniopharyngiomas, but none had optic nerve and/or brain stem involvement (P <0.05). While 62% (8/13) of HOCGs had diffuse homogeneous enhancement, 80% (20/25) of craniopharyngiomas had a diffuse heterogeneous enhancement pattern. Mean ADC values were significantly higher in craniopharyngiomas compared to HOCGs (2.1 vs. 1.6 ×10-3mm2/s, P <0.05). Although some neuroimaging findings may overlap, features such as presence of cyst and calcification, brain stem and optic pathway involvement, different enhancement patterns, and ADC values may be helpful in the differential diagnosis of HOCGs and craniopharyngiomas.

Comparison of conventional diffusion-weighted imaging, diffusion kurtosis imaging and intravoxel incoherent motion in characterization of sonographically indeterminate adnexal masses.

To evaluate the role of conventional diffusion weighted imaging, diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) in distinguishing benign from malignant adnexal masses. 38 patients with 45 adnexal masses were enrolled in this prospective study and assessed with multiparametric MRI, including the IVIM-DKI sequence, on a 3T MRI system. The mean apparent diffusion coefficient (ADC) from conventional DWI, the apparent diffusion coefficient derived from DKI (Dapp), the apparent kurtosis coefficient (Kapp), true diffusion coefficient (Dt), perfusion fraction (f) and pseudo-diffusion coefficient (Dp) were measured. The mean ADC, Dapp, and Dt were significantly higher in benign adnexal masses than in malignant adnexal masses (p < 0.001). f and Dp were also significantly higher in benign adnexal masses, with p values of 0.026 and 0.002, respectively. Kapp was higher in malignant masses (p < 0.001). Among mean ADC, Dapp, and Dt, mean ADC had the highest area under the curve (AUC) of 0.885. However, no statistically significant differences were observed between the ROCs of various diffusion parameters. The mean ADC, Dapp, and Kapp are useful parameters in discriminating between benign and malignant adnexal masses. Dt derived from IVIM also helps in distinguishing benign and malignant adnexal masses; however, no incremental role of IVIM and DKI over ADC could be identified in our study.

Usefulness of Diffusion-Weighted Imaging in Evaluating Acute Cellular Rejection and Monitoring Treatment Response in Liver Transplant Recipients.

Acute cellular rejection (ACR) is a significant immune issue among recipients following liver transplantation. Although diffusion-weighted magnetic resonance imaging (DWI) is widely used for diagnosing liver disease, it has not yet been utilized for monitoring ACR in patients after liver transplantation. Therefore, the aim of this study was to evaluate the efficacy of DWI in monitoring treatment response among recipients with ACR. This study enrolled 25 recipients with highly suspected ACR rejection, and all subjects underwent both biochemistry and DWI scans before and after treatment. A pathological biopsy was performed 4 to 24 h after the first MRI examination to confirm ACR and degree of rejection. All patients were followed up and underwent a repeated MRI scan when their liver function returned to the normal range. After data acquisition, the DWI data were post-processed to obtain the apparent diffusion coefficient (ADC) map on a voxel-by-voxel basis. Five regions of interest were identified on the liver parenchyma to measure the mean ADC values from each patient. Finally, the mean ADC values and biochemical markers were statistically compared between ACR and non-ACR groups. A receiver operating characteristic (ROC) curve was constructed to evaluate the performance of the ADC and biochemical data in detecting ACR, and correlation analysis was used to understand the relationship between the ADC values, biochemical markers, and the degree of rejection. The histopathologic results revealed that 20 recipients had ACR, including 10 mild, 9 moderate, and 1 severe rejection. The results demonstrated that the ACR patients had significantly lower hepatic ADC values than those in patients without ACR. After treatment, the hepatic ADC values in ACR patients significantly increased to levels similar to those in non-ACR patients with treatment. The ROC analysis showed that the sensitivity and specificity for detecting ACR were 80% and 95%, respectively. Furthermore, the correlation analysis revealed that the mean ADC value and alanine aminotransferase level had strong and moderate negative correlation with the degree of rejection, respectively (r = -0.72 and -0.47). The ADC values were useful for detecting hepatic ACR and monitoring treatment response after immunosuppressive therapy.

Does volumetric measurement of ADC values achieve higher diagnostic performance in bladder cancer MRI?

Apparent diffusion coefficient (ADC) value is an important part of bladder cancer magnetic resonance imaging (MRI) assessment and can predict the aggressive and invasive potentials. There is growing interest in whole tumor volume measurements. To investigate if the volumetric ADC measurement method will significantly exceed the diagnostic performance of the selected region of interest (ROI) method in everyday practice. A prospective evaluation was carried out of 50 patients with bladder cancer by two radiologists. The mean and the minimum ADC values were measured using both methods. The inter-reader agreement was determined by the intraclass correlation coefficient. The ADC values were compared between different grades, states of muscle invasion, and lympho-vascular invasion (LVI); then, validity was evaluated using receiver operating characteristic (ROC) curves. Areas under the curve (AUC) were then compared for the level of statistical significance. The inter-observer agreement was excellent for the ADC values using both methods. The volumetric measurement provides higher mean and lower minimum ADC values with statistically significant differences (P <0.00001). The highest diagnostic accuracy for differentiating tumor grade and predicting muscle invasion was for the minimum ADC by a selected ROI. However, the differences between the achieved AUCs were of no statistical significance. None of the ADC values predicted LVI with statistical significance. The selected ROI and volumetric measurement methods of mean and minimum ADC in bladder cancer yield different values, still having comparable diagnostic performance with accurate ROI sampling. The minimum ADC value by ROI is preferred in everyday clinical practice.

The Relationship between Breast Cancer Subtypes, Prognostic Factors, and Apparent Diffusion Coefficient Histogram Analysis.

Diffusion Magnetic Resonance Imaging (MRI) is a useful method to evaluate tumor biology and tumor microstructure. The apparent diffusion coefficient (ADC) value correlates negatively with the cellular density of the tumor. This study aimed to investigate the effectiveness of the ADC histogram analysis in showing the relationship between breast cancer prognostic factors and ADC parameters. This study is a retrospective observational descriptive study. ADC histogram parameters were evaluated in all tumor volumes of 67 breast cancer patients. Minimum, 5, 10, 25, 50, 75, 90, 95 percentiles, maximum, mean, median ADC values, kurtosis, and skewness were calculated. Breast MRI examinations were performed on a 3T MR scanner. We evaluated the fibroglandular tissue density of bilateral breasts, background enhancement, localization of masses, multifocality-multicentricity, shape, rim, internal contrast enhancement, and kinetic curve on breast MRI. BIRADS scoring was performed according to breast MRI. Pathologically, histologic type, histologic grade, HER 2, Ki 67, ER-, and PR status were evaluated. A significant correlation was found between tumor volume and ADC scores. There is a significant correlation between min ADC values (p< 0.031), max ADC (p< 0.001), and skewness (p< 0.019). A significant correlation was found between tumor kurtosis and lymph nodes (p< 0.029). There was a significant difference in ADC <sub<mean</sub<, ADC<sub<10%</sub<, ADC<sub<25%</sub<, ADC<sub<50%</sub<, ADC<sub<75%</sub<, ADC<sub<90%</sub<, ADC <sub<95%</sub< and ADC<sub<max</sub> values depending on ER-and PRstatus. (for ER p = 0.004, p = 0.018, p = 0.010, p = 0.008, p = 0.004, p = 0.004, p = 0.02, p = 0.02 and p = 0.038, for PR p &#60; 0.001, p = 0.028, p = 0.011, p = 0.001, p < 0.001, p =<0.001, p < 0.001, and p < 0.001, respectively; p < 0.05). These values were lower in ER-and PR-positive status than in ER-and PR-negative receptor status. According to HER2 status, there was a statistically significant difference in ADC<sub<5%</sub< and measurements of the lesions (p = 0.041; p < 0.05). Our study found no significant correlation between other prognostic factors, such as histological grade, Ki-67 indices, and ADC values. Our study found a significant difference between tumor volume, ER- and, PR status, HER2, and lymph node involvement, and some ADC values among prognostic factors for breast cancer. Furthermore, ADC histogram analysis can provide additional value in predicting some prognostic factors.

Factors associated with decreasing diffusion-weighted imaging-positive area volume after mechanical thrombectomy in patients with large early ischemic changes.

This study aimed to evaluate the factors associated with decreasing diffusion-weighted imaging (DWI) positive areas in patients with large early ischemic changes after mechanical thrombectomy (MT). This retrospective single-center clinical study was conducted between January 2013 and December 2022. We included consecutive patients who underwent MT for acute large-vessel occlusion of the anterior circulation with low pretreatment DWI-Alberta Stroke Program Early Computed Tomography Scores (ASPECTS) (0-5), effective recanalization [thrombolysis in cerebral infarction (TICI) 2b or TICI3], and magnetic resonance imaging (MRI) acquired before and after MT. We measured the DWI-positive area volume before and after MT. The primary endpoint was the after/before-MT DWI-positive area-volume ratio. In total, 28 patients were included in this study. Eight patients (29%) had an after/before-MT DWI-positive area-volume ratio of <1. The median mean apparent diffusion coefficient (ADC) levels of the DWI-positive areas in the groups with a ratio of <1 or >1 were 717 × 10⁶ mm2/s and 637 × 106 mm2/s, respectively (p = 0.011). Multivariate logistic regression analysis showed that ADC level (OR, 1.020 [95% confidence intervals (CIs), 1.001-1.040]; p = 0.040) was an independent predictor of a decreased DWI-positive area after MT. There was a negative correlation between the mean ADC level and the after/before-MT DWI-positive area-volume ratio (p < 0.001, |ρ| = 0.650), and the mean pretreatment ADC cutoff level was 649 × 106 mm2/s (area under the curve (AUC) = 0.806) for predicting a volume ratio of <1. The mean ADC level before-MT correlated with the after/before-MT DWI-positive area-volume ratio. A mean pretreatment ADC cutoff level of 649 × 106 mm2/s predicted a decreased DWI-positive area after MT.

Detecting High-Dose Methotrexate-Induced Brain Changes in Pediatric and Young Adult Cancer Survivors Using [18F]FDG PET/MRI: A Pilot Study.

Significant improvements in treatments for children with cancer have resulted in a growing population of childhood cancer survivors who may face long-term adverse outcomes. Here, we aimed to diagnose high-dose methotrexate-induced brain injury on [18F]FDG PET/MRI and correlate the results with cognitive impairment identified by neurocognitive testing in pediatric cancer survivors. Methods: In this prospective, single-center pilot study, 10 children and young adults with sarcoma (n = 5), lymphoma (n = 4), or leukemia (n = 1) underwent dedicated brain [18F]FDG PET/MRI and a 2-h expert neuropsychologic evaluation on the same day, including the Wechsler Abbreviated Scale of Intelligence, second edition, for intellectual functioning; Delis-Kaplan Executive Function System (DKEFS) for executive functioning; and Wide Range Assessment of Memory and Learning, second edition (WRAML), for verbal and visual memory. Using PMOD software, we measured the SUVmean, cortical thickness, mean cerebral blood flow (CBFmean), and mean apparent diffusion coefficient of 3 different cortical regions (prefrontal cortex, cingulate gyrus, and hippocampus) that are routinely involved during the above-specified neurocognitive testing. Standardized scores of different measures were converted to z scores. Pairs of multivariable regression models (one for z scores < 0 and one for z scores > 0) were fitted for each brain region, imaging measure, and test score. Heteroscedasticity regression models were used to account for heterogeneity in variances between brain regions and to adjust for clustering within patients. Results: The regression analysis showed a significant correlation between the SUVmean of the prefrontal cortex and cingulum and DKEFS-sequential tracking (DKEFS-TM4) z scores (P = 0.003 and P = 0.012, respectively). The SUVmean of the hippocampus did not correlate with DKEFS-TM4 z scores (P = 0.111). The SUVmean for any evaluated brain regions did not correlate significantly with WRAML-visual memory (WRAML-VIS) z scores. CBFmean showed a positive correlation with SUVmean (r = 0.56, P = 0.01). The CBFmean of the cingulum, hippocampus, and prefrontal cortex correlated significantly with DKEFS-TM4 (all P < 0.001). In addition, the hippocampal CBFmean correlated significantly with negative WRAML-VIS z scores (P = 0.003). Conclusion: High-dose methotrexate-induced brain injury can manifest as a reduction in glucose metabolism and blood flow in specific brain areas, which can be detected with [18F]FDG PET/MRI. The SUVmean and CBFmean of the prefrontal cortex and cingulum can serve as quantitative measures for detecting executive functioning problems. Hippocampal CBFmean could also be useful for monitoring memory problems.