Quantitative Apparent Diffusion Coefficient Values Research Articles

Volumetric apparent diffusion coefficient histogram analysis in term neonatal asphyxia treated with hypothermia.

Our aim is to estimate the long-term neurological sequelae and prognosis in term neonatal asphyxia treated with hypothermia via volumetric apparent diffusion coefficient (ADC) map histogram analysis (HA). Brain MRI studies of 83 term neonates with asphyxia who received whole-body hypothermia treatment and examined between postnatal (PN) fourth and sixth days were retrospectively re-evaluated by 2 radiologists. Volumetric HA was performed for the areas frequently affected in deep and superficial asphyxia (thalamus, lentiform nucleus, posterior limb of internal capsule, corpus callosum forceps major, and perirolandic cortex-subcortical white matter) on ADC map. The quantitative ADC values were obtained separately for each region. Qualitative-visual (conventional) MRI findings were also re-evaluated. Neonates were examined neurodevelopmentally according to the Revised Brunet-Lezine scale. The distinguishability of long-term neurodevelopmental outcomes was statistically investigated. With HA, the adverse neurodevelopmental outcomes could only be distinguished from mild-moderated impairment and normal development at the thalamus with 10th percentile ADC (P = .02 and P = .03, respectively) and ADCmin (P = .03 and P = .04, respectively). Also with the conventional MRI findings, adverse outcome could be distinguished from mild-moderated impairment (P = .04) and normal development (P = .04) via cytotoxic oedema of the thalamus, corpus striatum, and diffuse cerebral cortical. The long-term adverse neurodevelopmental outcomes in newborns with asphyxia who received whole-body hypothermia treatment can be estimated similarly with volumetric ADC-HA and the conventional assessment of the ADC map. This study compares early MRI ADC-HA with neurological sequelae in term newborns with asphyxia who received whole-body hypothermia treatment. We could not find any significant difference in predicting adverse neurological sequelae between the visual-qualitative evaluation of the ADC map and HA.

Impact on the image quality of modified reduced field-of-view diffusion-weighted magnetic resonance imaging of pancreatic adenocarcinoma using spatially tailored two-dimensional radiofrequency pulses with a tilted excitation plane: A comparison with conventional field-of-view imaging

PurposeModified reduced FOV diffusion-weighted imaging (DWI) using spatially-tailored 2D RF pulses with tilted excitation plane (tilted r-DWI) has been developed. The purpose of this study was to evaluate the impact on image quality and quantitative apparent diffusion coefficient (ADC) values of tilted r-DWI for pancreatic ductal adenocarcinomas (PDAC) in comparison to conventional full-FOV DWI (f-DWI). MethodsThis retrospective study included 21 patients (mean 70.7, range 50–85 years old) with pathologically confirmed PDAC. All MR images were obtained using 3 T systems. Two radiologists evaluated presence of blurring or ghost artifacts, susceptibility artifacts, and aliasing artifacts; anatomic visualization of the pancreas; interslice signal homogeneity; overall image quality; and conspicuity of the PDAC. For quantitative analysis, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), signal-intensity ratio (SIR) and ADC values were measured using regions of interest. ResultsAll image quality scores except aliasing artifacts in tilted r-DWI were significantly higher than those in f-DWI (p < 0.01). The CNR and SIR of PDAC were significantly higher in tilted r-DWI than in f-DWI (6.7 ± 4.4 vs. 4.7 ± 3.9, 2.02 ± 0.72 vs. 1.72 ± 0.60, p < 0.01). Conversely, the SNR of PDAC in tilted r-DWI was significantly lower than that in f-DWI (56.0 ± 33.1 vs. 113.6 ± 67.3, p < 0.01). No significant difference was observed between mean ADC values of the PDAC calculated from tilted r-DWI (tilted r-ADC) and those from f-DWI (f-ADC) (1225 ± 250 vs. 1294 ± 302, p = 0.11). ConclusionThe r-DWI using 2D RF techniques with a tilted excitation plane was shown to significantly improve the image quality and CNR and reduce image artifacts compared to f-DWI techniques in MRI evaluations of PDAC without significantly affecting ADC values.

Quantitative ADC: An Additional Tool in the Evaluation of Prostate Cancer?

Prostate cancer is one of the most common tumors among the male population. Magnetic resonance imaging (MRI), standardized by the PI-RADS version 2.1 scoring system, has a fundamental role in detecting prostate cancer and evaluating its aggressiveness. Diffusion-weighted imaging sequences and apparent diffusion coefficient values, in particular, are considered fundamental for the detection and characterization of lesions. In 2016 the International Society of Urological Pathology introduced a new anatomopathological 5-grade scoring system for prostate cancer. The aim of this study is to evaluate the correlation between quantitative apparent diffusion coefficient values (ADC) derived from diffusion-weighted imaging (DWI) sequences and the International Society of Urological Pathology (ISUP) and PI-RADS groups. Our retrospective study included 143 patients with 154 suspicious lesions, observed on prostate magnetic resonance imaging and compared with the histological results of the biopsy. We observed that ADC values can aid in discriminating between not clinically significant (ISUP 1) and clinically significant (ISUP 2-5) prostate cancers. In fact, ADC values were lower in ISUP 5 lesions than in negative lesions. We also found a correlation between ADC values and PI-RADS groups; we noted lower ADC values in the PI-RADS 5 and PI-RADS 4 groups than in the PI-RADS 3 group. In conclusion, quantitative apparent diffusion coefficient values can be useful to assess the aggressiveness of prostate cancer.

Diffusion-weighted Imaging in the Benign-malignant Differentiation of Endometrial Pathologies; Effectiveness of Visual Evaluation

To investigate the effectiveness of diffusion-weighted imaging (DWI) in the differentiation of benign and malignant endometrial pathologies by measuring the apparent diffusion coefficient (ADC) values and performing a visual evaluation. Cross-sectional study. Department of Radiology, Gaziosmanpasa Training and Research Hospital, Istanbul, Turkey, from January 2017 to September 2019. The inclusion criteria were women over 45 years of age with availability of the pelvic MRI in the PACS and the presence of pathological diagnosis by endometrial D and C or hysterectomy. Exclusion criteria were patients under 45 years of age, absence of histopathological results, hematoma or intrauterine device in the endometrial cavity, and endometrial thickness less than 5 mm. Quantitative ADC values were measured on ADC maps created automatically based on DWI data. DWI and ADC maps were also evaluated visually to differentiate between benign and malignant pathologies. Endometrial pathology was detected in a total of 88 patients, 36 of which were malignant and 52 benign lesions. The mean ADC values for both observers and the sensitivity and specificity in the differentiation of benign and malignant endometrial lesions were 81% - 75% and 88% - 90%, respectively (p<0.001 for both observers). The visual evaluation of b values and ADC map on DWI was also performed together, and the sensitivity and specificity in the differentiation of benign and malignant endometrial lesions were 81% - 86% and 69% - 56% for both observers, respectively (p <0.001 for both observers). ADC measurements are useful in differentiating benign and malignant endometrial pathologies, and visual evaluation of the ADC map and b values in DWI together also provides positive results. Diffusion-weighted imaging, Endometrial pathologies, ADC, Visual evaluation.

The Utility of Mean Apparent Diffusion Coefficient Value in Patients with Prostate Cancer Treated with Definitive Radiotherapy

<h3>Purpose/Objective(s)</h3> By providing more objective measurements, quantitative magnetic resonance imaging (MRI) has the potential to further improve prediction of treatment outcomes for prostate cancer patients. The purpose of this study was to determine whether quantitative multiparametric MRI performed prior to treatment can accurately predict the biochemical outcome of prostate cancer patients receiving definitive radiotherapy (RT). <h3>Materials/Methods</h3> The clinical data of 503 prostate cancer patients who received definitive radiation therapy (RT) between June 2008 and September 2021 were analyzed retrospectively. Prior to RT, all patients had a prostate multiparametric MRI on a 3T MRI scanner. A radiologist outlined the index lesion and measured the quantitative apparent diffusion coefficient (ADC). The Phoenix criteria were used to define biochemical failure. The primary endpoints were failure from biochemical failure (FFBF) and progression free survival (PFS). <h3>Results</h3> The median age of the population was 69 years (range: 47–87 years). According to D'Amico risk categories, there were 183 patients (36.4%) classified as low risk, 156 patients (31%) classified as intermediate risk, and 164 patients (32.6%) classified as high risk. The mean ADC values for tumor and normal prostate tissue were 0.712±0.158 µm²/ms and 1.365±0.227 µm²/ms, respectively (p<0.001). The ADC values were significantly lower in patients with higher PSA (≥20 ng/mL), advanced T stage (≥T3a), nodal metastasis, higher ISUP score (≥3) and high-risk group compared to their counterparts. The median duration of follow-up was 72.9 months (range, 4.3–170.6 months) for the entire cohort. The 5-year FFBF and PFS rates were 93.2% and 86.2%, respectively. Biochemical failure was observed in 42 patients (9.3%). After ‘Receiver Operating Characteristics' (ROC) curve analysis, the cut-off point of ADC for predicting high-risk progression was 0.653 µm²/ms with area under curve of 0.656 (95%CI 0.581 – 0.736; p<0.001). In univariate analysis, PSA, T stage, ISUP score, risk group were significant prognostic factors for FFBF and PFS. Additional prognostic factor for OS was N stage, and age was for PFS. The 5-year FFBF for lower and higher ADC values were 89.1% and 95.6%, respectively (p<0.001). The 5-year PFS was significantly less for patients with lower ADC compared to those with higher ADC (82.2% vs. 88.5%; p = 0.002). In multivariate analysis higher ISUP score and lower ADC values were independent predictors for worse FFBF and PFS rates. Additional predictive factor for dismal PFS was older age. <h3>Conclusion</h3> Our findings suggest that quantitative ADC values of the index lesion may be used to predict biochemical failure and disease progression in patients with prostate cancer following definitive RT. Inferior biochemical control was associated with lower ADC values and higher ISUP scores.

Biparametric prostate MRI: impact of a deep learning-based software and of quantitative ADC values on the inter-reader agreement of experienced and inexperienced readers

ObjectiveTo investigate the impact of an artificial intelligence (AI) software and quantitative ADC (qADC) on the inter-reader agreement, diagnostic performance, and reporting times of prostate biparametric MRI (bpMRI) for experienced and inexperienced readers.Materials and methodsA total of 170 multiparametric MRI (mpMRI) of patients with suspicion of prostate cancer (PCa) were retrospectively reviewed by one experienced and one inexperienced reader three times, following a wash-out period. First, only the bpMRI sequences, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) sequences, and apparent diffusion coefficient (ADC) maps, were used. Then, bpMRI and quantitative ADC values were used. Lastly, bpMRI and the AI software were used. Inter-reader agreement between the two readers and between each reader and the mpMRI original reports was calculated. Detection rates and reporting times were calculated for each group.ResultsInter-reader agreement with respect to mpMRI was moderate for bpMRI, Quantib, and qADC for both the inexperienced (weighted k of 0.42, 0.45, and 0.41, respectively) and the experienced radiologists (weighted k of 0.44, 0.46, and 0.42, respectively). Detection rate of PCa was similar between the inexperienced (0.24, 0.26, and 0.23) and the experienced reader (0.26, 0.27 and 0.27), for bpMRI, Quantib, and qADC, respectively. Reporting times were lower for Quantib (8.23, 7.11, and 9.87 min for the inexperienced reader and 5.62, 5.07, and 6.21 min for the experienced reader, for bpMRI, Quantib, and qADC, respectively).ConclusionsAI and qADC did not have a significant impact on the diagnostic performance of both readers. The use of Quantib was associated with lower reporting times.

Correlation of magnetic resonance imaging quantitative parameters and apparent diffusion coefficient value with pathological breast cancer.

BACKGROUNDChina ranks 120th worldwide for the incidence of breast cancer and 163rd for mortality. Early screening, diagnosis, and timely determination of the optimal treatment plan can help ensure clinical efficacy and prognosis.AIMTo investigate the relationship between quantitative magnetic resonance imaging parameters, apparent diffusion coefficient value, pathological immunohistochemical status, and patient prognosis.METHODSA total of 108 patients with breast cancer (breast cancer group) and 110 patients with benign breast tumors (benign group) confirmed by pathological examination at our Hospital from September 2013 to August 2016 were selected. All patients had undergone preoperative magnetic resonance imaging (MRI) examinations, and the quantitative parameters of MRI and apparent diffusion coefficient (ADC) values for the two groups were compared. The MRI quantitative parameters and ADC values of patients with different estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor-2 expression were statistically analyzed. The relationship between the quantitative parameters of MRI and ADC values and patient recurrence was analyzed using receiver operating curves.RESULTSThe measured values of the quantitative parameters of MRI- Ktrans, Kep, and Ve in the breast cancer group were higher than those in the benign group; the ADC value in the breast cancer group was lower than that in the benign group, and the difference was statistically significant (P < 0.05). The Ktrans, Ve, and ADC values in patients with ER-positive breast cancer were significantly lower than those in patients with negative ER expression (P < 0.05). After 5 years of follow-up, 22 patients with breast cancer experienced postoperative recurrence. The Kep, Ve, and ADC values of the recurrence group were significantly lower than those of the non-recurrence group, and the difference was statistically significant (P < 0.05). CONCLUSIONMRI quantitative parameters and ADC are related to the expression of breast cancer-related immunological receptor factors and have certain clinical value in assessing postoperative recurrence in patients.

Diagnostic performance of synthetic magnetic resonance imaging in the prognostic evaluation of rectal cancer.

Numerous factors are related to the prognosis of rectal cancer, including T stage, N stage, metastasis, extramural venous invasion (EMVI), circumferential resection margin (CRM), and tumor differentiation. However, it is still a challenge to precisely evaluate them before therapy; therefore, we investigate whether synthetic magnetic resonance imaging and apparent diffusion coefficient (ADC) values could help predict the prognostic factors of rectal cancer. Eighty-seven patients (55 men and 32 women; mean age, 59±11 years) with pathologically confirmed rectal cancer were enrolled. Preoperative quantitative metrics, including T1, T2, proton density (PD), and ADC values, were measured with diffusion-weighted imaging (DWI) acquired by a single-shot echo-planar sequence and synthetic magnetic resonance imaging acquired by a multi-dynamic multi-echo sequence at 3.0 T, in patients with rectal cancer by two radiologists. We evaluated the diagnostic performance of synthetic magnetic resonance imaging using the independent sample t-test or Mann-Whitney U test and receiver operating characteristic (ROC) curve and multivariate logistic regression analyses and compared the area under the ROC curve of quantitative values using the DeLong test. The T2 and PD values showed a significant reduction among patients with poor differentiation and lymph node metastasis in rectal cancer. The area under the ROC curve values of T2 and PD values for predicting magnetic resonance imaging N stage and differentiation were 0.734, 0.682, and 0.673, 0.686, respectively. Moreover, combining T2 and PD values for magnetic resonance imaging N stage slightly improved the area under the ROC curve value of 0.774 (95% CI, 0.673-0.876). In the present study, the ADC and T1 values were not significant in the differentiation or clinical stage of rectal cancer (RC). Quantitative T2 and PD values obtained by synthetic magnetic resonance imaging might be used for evaluating prognostic factors of rectal cancer noninvasively. Furthermore, combining T2 and PD values further improved the diagnostic performance of magnetic resonance imaging N staging in rectal cancer. The ADC and T1 values were not significant in the differentiation or clinical stage of RC.

Diffusion-weighted imaging of breast invasive lobular carcinoma: comparison with invasive carcinoma of no special type using a histogram analysis.

To investigate the imaging findings and visibility of breast invasive lobular carcinoma (ILC) on diffusion-weighted imaging (DWI) and compare quantitative apparent diffusion coefficient (ADC) metrics of ILC and invasive carcinoma of no special type (NST) using a histogram analysis. We performed an observational retrospective study of 629 consecutive women with pathologically proven ILC and invasive ductal carcinoma of NST, who underwent 3-T MRI including DWI, between January 2017 and August 2020. After propensity score matching, 71 women were allocated to each group. On DWI, 9 (12.7%) lesions of ILC and 4 (5.6%) invasive carcinomas of the NST were not visualized. For the tumor visibility on DWI, tumor size, tumor ADC value, and background diffusion grade were significantly associated with the visibility score in both groups (all P<0.05), whereas the mean background ADC value was not significant (P>0.05). The mean ADC (1.226×10-3 vs. 1.052×10-3 mm2/s, P<0.001), median ADC (1.222×10-3 vs. 1.051×10-3 mm2/s, P=0.002), maximum ADC (1.758×10-3 vs. 1.504×10-3 mm2/s, P<0.001), minimum ADC (0.717×10-3 vs. 0.649×10-3 mm2/s, P=0.003), 90th percentile ADC (1.506×10-3 vs. 1.292×10-3 mm2/s, P<0.001) and 10th percentile ADC (0.956×10-3 vs. 0.818×10-3 mm2/s, P=0.008) were higher in ILC than in invasive carcinoma of NST. Additionally, the ADC difference value of the ILC was higher than that of invasive carcinoma of NST (1.04×10-3 vs. 0.855×10-3 mm2/s, P=0.027). On DWI, the visibility of ILC was lower compared to invasive carcinoma of NST. ILC showed higher quantitative ADC values and higher ADC difference values.

Can Pre-treatment Quantitative Multi-parametric MRI Predict the Outcome of Radiotherapy in Patients with Prostate Cancer?

To investigate whether pre-treatment quantitative multiparametric MRI can predict biochemical outcome of prostate cancer (PCa) patients treated with primary radiotherapy (RT). Fifty-one patients with biopsy confirmed PCa underwent prostate multiparametric MRI on 3T MR scanner prior to RT. Thirty-seven men (73%) were treated with external beam RT alone, 12 men (24%) were treated with brachytherapy monotherapy, and two men (4%) were treated with external beam RT with brachytherapy boost. The index lesion was outlined by a radiologist and quantitative apparent diffusion coefficient (ADC), T2 and DCE parameters were measured. Biochemical failure was defined using the Phoenix criteria. After a median follow-up of 65 months, seven patients had biochemical failure. ADC had an area under the receiver operating characteristic curve of 0.71 for predicting RT outcome with significantly lower ADC (0.78 ± 0.17 vs 0.96 ± 0.26 µm2/ms, p=0.04) of the index lesion in men with biochemical failure. Ideal ADC cutoff point (Youdens index) was 0.96 µm2/ms which had a sensitivity of 100% and specificity of 48% for predicting biochemical failure. Kaplan-Meier analysis showed that lower ADC values were associated with significantly lower freedom from biochemical failure (FFBF, p=0.03, no failures out of 20 men if ADC ≥ 0.96 µm2/ms; seven of 31 with failures if ADC < 0.96 µm2/ms). On multivariable analysis, ADC was associated with FFBF (HR 0.96 per increase in ADC of 0.01 um2/ms [95% CI, 0.92-1.00]; p = 0.042) after accounting for National Comprehensive Cancer Network risk category (p=0.064) and receipt of androgen deprivation therapy (p=0.141). Quantitative T2 and DCE parameters were not associated with biochemical outcome. Our results suggest that quantitative ADC values of the index lesion may predict biochemical failure following primary radiotherapy in patients with PCa. Lower ADC values were associated with inferior biochemical control.

The Potential Role of Peritumoral Apparent Diffusion Coefficient Evaluation in Differentiating Glioblastoma and Solitary Metastatic Lesions of the Brain.

Differentiating glioblastoma (GBM) and solitary metastasis is not always possible using conventional magnetic resonance imaging (MRI) techniques. In conventional brain MRI, GBM and brain metastases are lesions with mostly similar imaging findings. In this study, we investigated whether apparent diffusion coefficient (ADC) ratios, ADC gradients, and minimum ADC values in the peritumoral edema tissue can be used to discriminate between these two tumors. This retrospective study was approved by the local institutional review board with a waiver of written informed consent. Prior to surgical and medical treatment, conventional brain MRI and diffusion-weighted MRI (b = 0 and b = 1000) images were taken from 43 patients (12 GBM and 31 solitary metastasis cases). Quantitative ADC measurements were performed on the peritumoral tissue from the nearest segment to the tumor (ADC1), the middle segment (ADC2), and the most distant segment (ADC3). The ratios of these three values were determined proportionally to calculate the peritumoral ADC ratios. In addition, these three values were subtracted from each other to obtain the peritumoral ADC gradients. Lastly, the minimum peritumoral and tumoral ADC values, and the quantitative ADC values from the normal-appearing ipsilateral white matter, contralateral white matter, and ADC values from cerebrospinal fluid (CSF) were recorded. For the differentiation of GBM and solitary metastasis, ADC3 / ADC1 was the most powerful parameter with a sensitivity of 91.7% and specificity of 87.1% at the cut-off value of 1.105 (p < 0.001), followed by ADC3 / ADC2 with a cut-off value of 1.025 (p = 0.001), sensitivity of 91.7%, and specificity of 74.2%. The cut-off, sensitivity and specificity of ADC2 / ADC1 were 1.055 (p = 0.002), 83.3%, and 67.7%, respectively. For ADC3 - ADC1, the cut-off value, sensitivity, and specificity were calculated as 150 (p < 0.001), 91.7%, and 83.9%, respectively. ADC3 - ADC2 had a cutoff value of 55 (p = 0.001), sensitivity of 91.7%, and specificity of 77.4, whereas ADC2 - ADC1 had a cut-off value of 75 (p = 0.003), sensitivity of 91.7%, and specificity of 61.3%. Among the remaining parameters, only the ADC3 value successfully differentiated between GBM and metastasis (GBM 1802.50 ± 189.74 vs. metastasis 1634.52 ± 212.65, p = 0.022). The integration of the evaluation of peritumoral ADC ratio and ADC gradient into conventional MR imaging may provide valuable information for differentiating GBM from solitary metastatic lesions.

Feasibility and possible value of quantitative semi-automated diffusion weighted imaging volumetry of neuroblastic tumors

BackgroundTo assess the feasibility and possible value of semi-automated diffusion weighted imaging (DWI) volumetry of whole neuroblastic tumors with apparent diffusion coefficient (ADC) map evaluation after neoadjuvant chemotherapy.MethodsPediatric patients who underwent surgical resection of neuroblastic tumors at our institution from 2013 to 2019 and who received a preoperative MRI scan with DWI after chemotherapy were included. Tumor volume was assessed with a semi-automated approach in DWI using a dedicated software prototype. Quantitative ADC values were calculated automatically of the total tumor volume after manual exclusion of necrosis. Manual segmentation in T1 weighted and T2 weighted sequences was used as reference standard for tumor volume comparison. The Student’s t test was used for parametric data while the Wilcoxon rank sum test and the Kruskal-Wallis test were applied for non-parametric data.ResultsTwenty seven patients with 28 lesions (neuroblastoma (NB): n = 19, ganglioneuroblastoma (GNB): n = 7, ganglioneuroma (GN): n = 2) could be evaluated. Mean patient age was 4.5 ± 3.2 years. Median volume of standard volumetry (T1w or T2w) was 50.2 ml (interquartile range (IQR): 91.9 ml) vs. 45.1 ml (IQR: 98.4 ml) of DWI (p = 0.145). Mean ADC values (× 10− 6 mm2/s) of the total tumor volume (without necrosis) were 1187 ± 301 in NB vs. 1552 ± 114 in GNB/GN (p = 0.037). The 5th percentile of ADC values of NB (614 ± 275) and GNB/GN (1053 ± 362) provided the most significant difference (p = 0.007) with an area under the curve of 0.848 (p < 0.001).ConclusionsQuantitative semi-automated DWI volumetry is feasible in neuroblastic tumors with integrated analysis of tissue characteristics by providing automatically calculated ADC values of the whole tumor as well as an ADC heatmap. The 5th percentile of the ADC values of the whole tumor volume proved to be the most significant parameter for differentiation of the histopathological subtypes in our patient cohort and further investigation seems to be worthwhile.

Radiation-induced occult insufficiency fracture or bone metastasis after radiotherapy for cervical cancer? The nomogram based on quantitative apparent diffusion coefficients for discrimination

BackgroundRadiation-induced insufficiency fractures (IF) is frequently occult without fracture line, which may be mistaken as metastasis. Quantitative apparent diffusion coefficient (ADC) shows potential value for characterization of benign and malignant bone marrow diseases. The purpose of this study was to develop a nomogram based on multi-parametric ADCs in the differntiation of occult IF from bone metastasis after radiotherapy (RT) for cervical cancer.MethodsThis study included forty-seven patients with cervical cancer that showed emerging new bone lesions in RT field during the follow-up. Multi-parametric quantitative ADC values were measured for each lesion by manually setting region of interests (ROIs) on ADC maps, and the ROIs were copied to adjacent normal muscle and bone marrow. Six parameters were calculated, including ADCmean, ADCmin, ADCmax, ADCstd, ADCmean ratio (lesion/normal bone) and ADCmean ratio (lesion/muscle). For univariate analysis, receiver operating characteristic curve (ROC) analysis was performed to assess the performance. For combined diagnosis, a nomogram model was developed by using a multivariate logistic regression analysis.ResultsA total of 75 bone lesions were identified, including 48 occult IFs and 27 bone metastases. There were significant differences in the six ADC parameters between occult IFs and bone metastases (p < 0.05), the ADC ratio (lesion/ muscle) showed an optimal diagnostic efficacy, with an area under ROC (AUC) of 0.887, the sensitivity of 95.8%, the specificity of 81.5%, respectively. Regarding combined diagnosis, ADCstd and ADCmean ratio (lesion/muscle) were identified as independent factors and were selected to generate a nomogram model. The nomogram model showed a better performance, yielded an AUC of 0.92, the sensitivity of 91.7%, the specificity of 96.3%, positive predictive value (PPV) of 97.8% and negative predictive value (NPV) of 86.7%, respectively.ConclusionsMulti-parametric ADC values demonstrate potential value for differentiating occult IFs from bone metastasis, a nomogram based on the combination of ADCstd and ADCmean ratio (lesion/muscle) may provide an improved classification performance.

Diagnostic contribution of focal cortical dysplasia MRI imaging findings and ADC values

BackgroundFocal cortical dysplasia (FCD) is a condition that often interferes with the cranial mass. Knowledge of focal cortical dysplasia magnetic resonance imaging (MRI) characteristics is of utmost importance for diagnosis. This study aimed to determine the diagnostic contribution of cranial MRI and the apparent diffusion coefficient (ADC) in FCD.ResultsCranial MRI revealed subcortical hyperintensity (SCH) in 52 patients (82.5%), blurring of the gray-white matter (GWM) interface (blurring) in 52 patients (82.5%), cortical thickening (CT) in 48 patients (76%), cortical signal increase (CSI) in 41 patients (65%), and transmantle sign (TMS) in 29 patients (46%). All of the FCDs had a diffusion increase in diffusion-weighted images (DWIs). The mean ADC value at the lesion level was 1.087 × 10−3 mm2/s (0.82/1.316 × 10−3 mm2/s), which was significantly higher than the mean ADC value measured from the contralateral symmetric region (0.758 × 10−3 mm2/s, 0.678/0.872 × 10−3 mm2/s, p = 0.001).ConclusionResults of this study revealed that the most common MRI findings in FCD patients are SCH, blurring, and CT. These findings aid in an easier diagnosis in patients with suspected FCD. All of the lesions studied here in had a diffusion increase in DWI. The quantitative mean ADC values detected in the differential diagnosis of other lesions with a diffusion increase can be used as a reference. Therefore, in addition to the ADC values and electroencephalography (EEG) findings, the conventional MRI findings of FCD, which is resistant to medical treatment, can help to facilitate the diagnosis of FCD, which can be treated with surgery.

Correlation between DCE-MRI quantitative perfusion histogram parameters, apparent diffusion coefficient and Ki-67 in different pathological types of lung cancer

Objective: To explore the efficacy of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) histogram molecular imaging index, apparent diffusion coefficient (ADC) in different types of lung cancer and explore their correlation with Ki-67. Methods: A total of 33 cases of lung cancer patients confirmed by pathology in Shaoxing People's Hospital from March 2017 to March 2018 were collected, 28 males and 5 females aged 50-85 years old, including 15 cases of squamous cell carcinoma, 12 cases of adenocarcinoma, and 6 cases of small cell carcinoma. All patients performed DCE-MRI and DWI imaging within one week before surgery or puncture. ADC values, DCE-MRI quantitative perfusion parameters by histogram metrics analysis (mean value, skewness, kurtosis, uniformity, entropy, energy, quantile) of K(trans), K(ep), V(e), and V(p) were then collected. Ki-67 expression in lung cancer tissue was detected by immunohistochemical method. One-way analysis of variance and least significant difference were used to compare the differences among the parameters of the three groups which were normal distribution and equal variances, while Kruskal-Walls test and Mann-Whitney U test were used to compare the parameters that did not conform to normal distribution or variance. Pearson correlation analysis was used to compare the correlations between quantitative perfusion histogram parameters, ADC values and immunohistochemical scores of Ki-67. Results: The Ki-67 count in small cell lung cancer(458±82, P=0.011) and squamous cell carcinoma(355±277, P=0.034)were significantly higher than that in adenocarcinoma (168±164). The correlation analysis showed that there was a significant negative correlation between ADC values and Ki-67 (P=0.018, r=-0.416). And V(e) (Q5, Q10) was negatively related to Ki-67 (P=0.017, r=-0.420; P=0.040, r=-0.366). In squamous cell carcinoma patients, V(e) (homogeneity) was significantly negatively correlated with the expression of Ki-67 (P=0.033, r=-0.570). K(trans)(homogeneity) and V(e) (homogeneity, Q5, Q10, Q25) were significantly positively correlated with ADC values (P value from 0.001 to 0.035, r value from 0.545 to 0.765). Conclusion: DCE-MRI quantitative perfusion histogram parameters, ADC value can evaluate the lung cancer cell proliferation activity in different pathological types.

Preoperative MR Imaging to Differentiate Chordoid Meningiomas from Other Meningioma Histologic Subtypes.

Chordoid meningiomas are uncommon WHO grade II primary intracranial neoplasms that possess unique chordoid histology and follow an aggressive clinical course. Our aim was to assess the utility of qualitative MR imaging features and quantitative apparent diffusion coefficient values as distinguishing preoperative MR imaging metrics to identify and differentiate chordoid histology from other meningioma histologic subtypes. Twenty-one patients with meningiomas with chordoid histology, which included both chordoid meningiomas (>50% chordoid histology) and meningiomas with focal chordoid histology (<50% chordoid histology) with available preoperative MR imaging examinations, including diffusion-weighted imaging, were identified. Qualitative imaging features and quantitative ADC values were compared between meningiomas with chordoid histology and 42 nonchordoid meningiomas (29 WHO grade I, eleven WHO grade II, and 2 WHO grade III). The median ADC (10-3mm2/s) of meningiomas with chordoid histology was significantly higher than nonchordoid meningiomas (1.16 versus 0.92, P < .001), as was the median normalized ADC (1.60 versus 1.19, P < .001). In subgroup analysis, the median and normalized ADC values of chordoid meningiomas (n = 11) were significantly higher than those in meningiomas with focal chordoid histology (n = 10, P < .001 and P < .001, respectively) or nonchordoid meningiomas (n = 42, P < .001 and <0.001, respectively). Median and normalized ADC values were not significantly different between the meningiomas with focal chordoid histology and nonchordoid meningiomas (P = .816 and .301, respectively). Among the qualitative imaging features, only DWI signal intensity was significantly associated with meningiomas with chordoid histology diagnosis. ADC values are higher in chordoid compared with nonchordoid meningiomas and may be used to discriminate the degree of chordoid histology in meningiomas. While qualitative MR imaging features do not strongly discriminate chordoid from nonchordoid meningiomas, DWI may allow preoperative identification of chordoid meningiomas.

Multiparametric MRI Features and Pathologic Outcome of Wedge-Shaped Lesions in the Peripheral Zone on T2-Weighted Images of the Prostate.

This study investigates the multiparametric MRI (mpMRI) characteristics and pathologic outcome of wedge-shaped lesions observed on T2-weighted images. Seventy-six patients with histologically confirmed prostate cancer underwent preoperative 3-T MRI before undergoing radical prostatectomy. Two radiologists worked in consensus to mark wedge-shaped regions of hypointensity on T2-weighted images and assess their appearance on apparent diffusion coefficient (ADC) maps (to determine the degree of hypointensity) and dynamic contrast-enhanced (DCE) MRI (DCE-MRI) (to assess whether they showed early enhancement). The pathologic outcome of wedge-shaped lesions was assessed by matching MR images with whole-mount histologic specimens retrospectively. The difference in quantitative ADC values between malignant and benign wedge-shaped lesions was assessed using a t test. Thirty-five wedge-shaped regions were identified, 12 (34%) of which were found be malignant. Most malignant wedge-shaped regions were highly hypointense (10/12; 83%) on ADC maps and showed early enhancement on DCE-MRI (7/12; 58%). However, benign wedge-shaped lesions were predominantly mildly hypointense (13/23; 57%) on ADC maps and showed no early enhancement (15/23; 65%). Histologic correlates of the benign wedge-shaped regions showed prostatitis (acute inflammation [7/23; 30%] or chronic inflammation [9/23; 39%]), hemosiderin-laden macrophages (6/23; 26%), prominent blood vessels (7/23; 30%), intraluminal blood (6/23; 26%), and nonspecific atrophy (6/23; 26%). The mean (± SD) quantitative ADC value of malignant wedge-shaped regions (1.13 ± 0.11 μm2/ms) was significantly lower (p = 0.0001) than that of benign wedge-shaped regions (1.52 ± 0.27 μm2/ms). This study shows that a greater percentage of wedge-shaped features are malignant than was previously thought. Of importance, mpMRI (specifically, ADC maps) can distinguish between malignant and benign wedge-shaped features.

Apparent diffusion coefficient as a potential marker for tumour differentiation, staging and long-term clinical outcomes in gallbladder cancer.

To evaluate the correlation between tumour differentiation or stage of gallbladder cancer (GBC) and the apparent diffusion coefficient (ADC), as well as to assess whether ADC value can predict long-term disease-free survival (DFS) after surgery. This retrospective study was approved by the institutional review board and the requirement for informed consent was waived. Between March 2008 and June 2016, 79 patients who underwent magnetic resonance (MR) imaging with diffusion-weighted image and subsequent surgery for GBC were included in this study. Correlations between quantitative ADC values and tumour differentiation or stage based on the American Joint Committee on Cancer (AJCC) were assessed using Spearman's correlation analysis. Prognostic factors for DFS were identified with multivariate Cox regression analysis using imaging and clinical characteristics. All patients were classified as having well- (n = 18), moderately (n = 35) or poorly differentiated GBCs (n = 26). The ADC value of GBCs was significantly correlated with tumour differentiation and AJCC stage (p < 0.001 and p < 0.001, respectively). Sixty-nine patients were followed up for 2.0-92.4 months (median, 23.5 months). On multivariate analysis, the significant prognostic factor for DFS was not tumour differentiation or AJCC stage but a binary tumour ADC value (hazard ratio, 4.29; p = 0.009). DFS rates were significantly different according to the classification of tumour ADC value (cut-off value = 1.04 × 10-3 mm2/s; p = 0.004). The ADC value of GBCs was significantly correlated with tumour differentiation as well as AJCC stage. In addition, it predicted long-term outcomes after surgery in patients with GBC. • ADC values of GBC and tumour differentiation were negatively correlated. • Lower ADC values of GBC were significantly correlated with higher tumour stage. • Tumour ADC value could be useful for risk stratification of GBC patients.

Longitudinal MRI dynamics of recent small subcortical infarcts and possible predictors

We aimed to explore the morphological evolution of recent small subcortical infarcts (RSSIs) over 15 months. Moreover, we hypothesized that quantitative lesion apparent diffusion coefficient (ADC) values and serum neurofilament light (NfL) levels predict subsequent lacunar cavitation. We prospectively studied 78 RSSI patients, who underwent pre-defined follow-up investigations three and 15 months poststroke using 3 T MRI including high-resolution T1 sequences. To identify potential predictors of cavitation, we determined RSSI size and quantitative ADC values, and serum NfL using the SIMOA technique. The majority of RSSIs showed cavitation at three months (n = 61, 78%) with only minimal changes regarding cavitation status thereafter. The maximum axial lacunar diameter decreased from 8 mm at three to 7 mm at 15 months (p < 0.05). RSSIs which cavitated had lower lesional ADC values and were associated with higher baseline NfL levels compared to those without cavitation, but did not differ regarding lesion size. In logistic regression analysis, only baseline NfL levels predicted cavitation (p = 0.017). In this prospective study using predefined high-resolution MRI protocols, the majority of RSSIs evolved into lacunes during the first three months poststroke with not much change thereafter. Serum NfL seems to be a promising biomarker for more advanced subsequent tissue destruction in RSSIs.

Utility of DWI with quantitative ADC values in ovarian tumors: a meta-analysis of diagnostic test performance.

Background Diffusion-weighted imaging (DWI) and quantitative apparent diffusion coefficient (ADC) values are widely used in the differential diagnosis of ovarian tumors. Purpose To assess the diagnostic performance of quantitative ADC values in ovarian tumors. Material and Methods PubMed, Embase, the Cochrane Library, and local databases were searched for studies assessing ovarian tumors using quantitative ADC values. We quantitatively analyzed the diagnostic performances for two clinical problems: benign vs. malignant tumors and borderline vs. malignant tumors. We evaluated diagnostic performances by the pooled sensitivity and specificity values and by summary receiver operating characteristic (SROC) curves. Subgroup analyses were used to analyze study heterogeneity. Results From the 742 studies identified in the search results, 16 studies met our inclusion criteria. A total of ten studies evaluated malignant vs. benign ovarian tumors and six studies assessed malignant vs. borderline ovarian tumors. Regarding the diagnostic accuracy of quantitative ADC values for distinguishing between malignant and benign ovarian tumors, the pooled sensitivity and specificity values were 0.91 and 0.91, respectively. The area under the SROC curve (AUC) was 0.96. For differentiating borderline from malignant tumors, the pooled sensitivity and specificity values were 0.89 and 0.79, and the AUC was 0.91. The methodological quality of the included studies was moderate. Conclusion Quantitative ADC values could serve as useful preoperative markers for predicting the nature of ovarian tumors. Nevertheless, prospective trials focused on standardized imaging parameters are needed to evaluate the clinical value of quantitative ADC values in ovarian tumors.