Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCmean

The Role of Predictive and Prognostic MRI-Based Biomarkers in the Era of Total Neoadjuvant Treatment in Rectal Cancer

The role of magnetic resonance imaging (MRI) in rectal cancer management has significantly increased over the last decade, in line with more personalized treatment approaches. Total neoadjuvant treatment (TNT) plays a pivotal role in the shift from traditional surgical approach to non-surgical approaches such as 'watch-and-wait'. MRI plays a central role in this evolving landscape, providing essential morphological and functional data that support clinical decision-making. Key MRI-based biomarkers, including circumferential resection margin (CRM), extramural venous invasion (EMVI), tumour deposits, diffusion-weighted imaging (DWI), and MRI tumour regression grade (mrTRG), have proven valuable for staging, response assessment, and patient prognosis. Functional imaging techniques, such as dynamic contrast-enhanced MRI (DCE-MRI), alongside emerging biomarkers derived from radiomics and artificial intelligence (AI) have the potential to transform rectal cancer management offering data that enhance T and N staging, histopathological characterization, prediction of treatment response, recurrence detection, and identification of genomic features. This review outlines validated morphological and functional MRI-derived biomarkers with both prognostic and predictive significance, while also exploring the potential of radiomics and artificial intelligence in rectal cancer management. Furthermore, we discuss the role of rectal MRI in the 'watch-and-wait' approach, highlighting important practical aspects in selecting patients for non-surgical management.

Advances and residual knowledge gaps in the neck management of head and neck squamous cell carcinoma patients with advanced nodal disease undergoing definitive (chemo)radiotherapy for their primary

PURPOSE

Substantial changes have been made in the neck management of patients with head and neck squamous cell carcinomas (HNSCC) in the past century. These have been fostered by changes in cancer epidemiology and technological progress in imaging, surgery, or radiotherapy, as well as disruptive concepts in oncology. We aimed to review changes in nodal management, with a focus on HNSCC patients with nodal involvement (cN+) undergoing (chemo)radiotherapy.

METHODS

A narrative review was conducted to review current advances and address knowledge gaps in the multidisciplinary management of the cN+ neck in the context of (chemo)radiotherapy.

RESULTS

Metastatic neck nodes are associated with poorer prognosis and poorer response to radiotherapy, and have therefore been systematically treated by surgery. Radical neck dissection (ND) has gradually evolved toward more personalized and less morbid approaches, i.e., from functional to selective ND. Omission of ND has been made feasible by use of positron-emission tomography/computed tomography to monitor the radiation response in cN+ patients. Human papillomavirus-driven oropharyngeal cancers and their cystic nodes have shown dramatically better prognosis than tobacco-related cancers, justifying a specific prognostic classification (AJCC) creation. Finally, considering the role of lymph nodes in anti-tumor immunity, de-escalation of ND and prophylactic nodal irradiation in combination are intense areas of investigation. However, the management of bulky cN3 disease remains an issue, as aggressive multidisciplinary strategies or innovative combined treatments have not yet significantly improved their prognosis.

CONCLUSION

Personalized neck management is an increasingly important aspect of the overall therapeutic strategies in cN+ HNSCC.

Predicting the prognosis of hepatic arterial infusion chemotherapy in hepatocellular carcinoma

Hepatic artery infusion chemotherapy (HAIC) has good clinical efficacy in the treatment of advanced hepatocellular carcinoma (HCC); however, its efficacy varies. This review summarized the ability of various markers to predict the efficacy of HAIC and provided a reference for clinical applications. As of October 25, 2023, 51 articles have been retrieved based on keyword predictions and HAIC. Sixteen eligible articles were selected for inclusion in this study. Comprehensive literature analysis found that methods used to predict the efficacy of HAIC include serological testing, gene testing, and imaging testing. The above indicators and their combined forms showed excellent predictive effects in retrospective studies. This review summarized the strategies currently used to predict the efficacy of HAIC in middle and advanced HCC, analyzed each marker's ability to predict HAIC efficacy, and provided a reference for the clinical application of the prediction system.

Predicting the prognosis of hepatic arterial infusion chemotherapy in hepatocellular carcinoma

Hepatic artery infusion chemotherapy (HAIC) has good clinical efficacy in the treatment of advanced hepatocellular carcinoma (HCC); however, its efficacy varies. This review summarized the ability of various markers to predict the efficacy of HAIC and provided a reference for clinical applications. As of October 25, 2023, 51 articles have been retrieved based on keyword predictions and HAIC. Sixteen eligible articles were selected for inclusion in this study. Comprehensive literature analysis found that methods used to predict the efficacy of HAIC include serological testing, gene testing, and imaging testing. The above indicators and their combined forms showed excellent predictive effects in retrospective studies. This review summarized the strategies currently used to predict the efficacy of HAIC in middle and advanced HCC, analyzed each marker's ability to predict HAIC efficacy, and provided a reference for the clinical application of the prediction system.

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

BACKGROUND

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.

PURPOSE

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.

MATERIAL AND METHODS

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.

RESULTS

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.

CONCLUSION

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.

Apparent diffusion coefficient for differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck: a systematic review and meta-analysis

BACKGROUND

Radiological differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck is often difficult due to their similarities.

PURPOSE

To evaluate the diagnostic benefit of apparent diffusion coefficient (ADC) calculated from diffusion-weighted imaging (DWI) in differentiating the two.

MATERIAL AND METHODS

A systematic review was performed by searching the MEDLINE, Scopus, and Embase databases in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement. Forest plots and the pooled mean difference of ADC values were calculated to describe the relationship between extra-nodal lymphoma and squamous cell carcinoma in the head and neck. Heterogeneity among studies was evaluated using the Cochrane Q test and I2 statistic.

RESULTS

The review identified eight studies with 440 patients (441 lesions) eligible for meta-analysis. Among all studies, the mean ADC values of squamous cell carcinoma was 0.88 × 10-3mm2/s and that of lymphoma was 0.64 × 10-3mm2/s. In the meta-analysis, the ADC value of lymphoma was significantly lower than that of squamous cell carcinoma (pooled mean difference = 0.235, 95% confidence interval [CI] = 0.168-0.302, P <0.0001). The Cochrane Q test (chi-square = 55.7, P <0.0001) and I2 statistic (I2 = 87.4%, 95% CI = 77.4-93.0%) revealed significant heterogeneity.

CONCLUSION

This study highlights the value of quantitative assessment of ADC for objective and reliable differentiation between extra-nodal lymphoma and squamous cell carcinoma in the head and neck. Conclusions should be interpreted with caution due to heterogeneity in the study data.

Diagnostic value of radiomics in predicting Ki-67 and cytokeratin 19 expression in hepatocellular carcinoma: a systematic review and meta-analysis

Background

Radiomics have been increasingly used in the clinical management of hepatocellular carcinoma (HCC), such as markers prediction. Ki-67 and cytokeratin 19 (CK-19) are important prognostic markers of HCC. Radiomics has been introduced by many researchers in the prediction of these markers expression, but its diagnostic value remains controversial. Therefore, this review aims to assess the diagnostic value of radiomics in predicting Ki-67 and CK-19 expression in HCC.

Methods

Original studies were systematically searched in PubMed, EMBASE, Cochrane Library, and Web of Science from inception to May 2023. All included studies were evaluated by the radiomics quality score. The C-index was used as the effect size of the performance of radiomics in predicting Ki-67and CK-19 expression, and the positive cutoff values of Ki-67 label index (LI) were determined by subgroup analysis and meta-regression.

Results

We identified 34 eligible studies for Ki-67 (18 studies) and CK-19 (16 studies). The most common radiomics source was magnetic resonance imaging (MRI; 25/34). The pooled C-index of MRI-based models in predicting Ki-67 was 0.89 (95% CI:0.86-0.92) in the training set, and 0.87 (95% CI: 0.82-0.92) in the validation set. The pooled C-index of MRI-based models in predicting CK-19 was 0.86 (95% CI:0.81-0.90) in the training set, and 0.79 (95% CI: 0.73-0.84) in the validation set. Subgroup analysis suggested Ki-67 LI cutoff was a significant source of heterogeneity (I 2 = 0.0% P>0.05), and meta-regression showed that the C-index increased as Ki-67 LI increased.

Conclusion

Radiomics shows promising diagnostic value in predicting positive Ki-67 or CK-19 expression. But lacks standardized guidelines, which makes the model and variables selection dependent on researcher experience, leading to study heterogeneity. Therefore, standardized guidelines are warranted for future research.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023427953.

Quantitative evaluation of diffusion-weighted MRI for differentiating benign and malignant thyroid nodules larger than 4 cm

PURPOSE

Our study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis.

METHODS

Eighty-two thyroid nodules were investigated retrospectively and divided them into benign (n = 62) and malignant groups (n = 20). We calculated quantitative features DWI and apparent diffusion coefficient (ADC) signal intensity standard deviation (DWISD and ADCSD), DWI and ADC signal intensity ratio (DWISIR and ADCSIR), mean ADC and minimum ADC value (ADCmean and ADCmin) and ADC value standard deviation (ADCVSD). Univariate and multivariate logistic regression were conducted to identify independent predictors, and develop a prediction model. We performed receiver operating characteristic (ROC) analysis to determine the optimal threshold of risk factors, and constructed combined threshold models. Our study calculated diagnostic performance including area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and unnecessary biopsy rate of all models were calculated and compared them with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) result.

RESULTS

Two independent predictors of malignant nodules were identified by multivariate analysis: DWISIR (P = 0.007) and ADCmin (P < 0.001). The AUCs for multivariate prediction model, combined DWISIR and ADCmin thresholds model, combined DWISIR and ADCSIR thresholds model and ACR-TIRADS were 0.946 (0.896-0.996), 0.875 (0.759-0.991), 0.777 (0.648-0.907) and 0.722 (0.588-0.857). The combined DWISIR and ADCmin threshold model had the lowest unnecessary biopsy rate of 0%, compared with 56.3% for ACR-TIRADS.

CONCLUSION

Quantitative DWI demonstrated favorable malignant thyroid nodule diagnostic efficacy. The combined DWISIR and ADCmin thresholds model significantly reduced the unnecessary biopsy rate.

ADC histogram parameters differentiating atypical from transitional meningiomas: correlation with Ki-67 proliferation index

BACKGROUND

Preoperative differentiation of atypical meningioma (AtM) from transitional meningioma (TrM) is critical to clinical treatment.

PURPOSE

To investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating AtM from TrM and its correlation with the Ki-67 proliferation index (PI).

METHODS

Clinical, imaging, and pathological data of 78 AtM and 80 TrM were retrospectively collected. Regions of interest (ROIs) were delineated on axial ADC images using MaZda software and histogram parameters (mean, variance, skewness, kurtosis, 1st percentile [ADCp1], 10th percentile [ADCp10], 50th percentile [ADCp50], 90th percentile [ADCp90], and 99th percentile [ADCp99]) were generated. The Mann-Whitney U test was used to compare the differences in histogram parameters between the two groups; receiver operating characteristic (ROC) curves were used to assess diagnostic efficacy in differentiating AtM from TrM preoperatively. The correlation between histogram parameters and Ki-67 PI was analyzed.

RESULTS

All histogram parameters of AtM were lower than those of TrM, and the variance, skewness, kurtosis, ADCp90, and ADCp99 were significantly different (P < 0.05). Combined ADC histogram parameters (variance, skewness, kurtosis, ADCp90, and ADCp99) achieved the best diagnostic performance for distinguishing AtM from TrM. Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.800%, 76.25%, 67.95%, 70.15%, 70.93%, and 73.61%, respectively. All histogram parameters were negatively correlated with Ki-67 PI (r = -0.012 to -0.293).

CONCLUSION

ADC histogram analysis is a potential tool for non-invasive differentiation of AtM from TrM preoperatively, and ADC histogram parameters were negatively correlated with the Ki-67 PI.

The Prediction of Biological Features Using Magnetic Resonance Imaging in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis

Magnetic resonance imaging (MRI) is an indispensable, routine technique that provides morphological and functional imaging sequences. MRI can potentially capture tumor biology and allow for longitudinal evaluation of head and neck squamous cell carcinoma (HNSCC). This systematic review and meta-analysis evaluates the ability of MRI to predict tumor biology in primary HNSCC. Studies were screened, selected, and assessed for quality using appropriate tools according to the PRISMA criteria. Fifty-eight articles were analyzed, examining the relationship between (functional) MRI parameters and biological features and genetics. Most studies focused on HPV status associations, revealing that HPV-positive tumors consistently exhibited lower ADCmean (SMD: 0.82; p < 0.001) and ADCminimum (SMD: 0.56; p < 0.001) values. On average, lower ADCmean values are associated with high Ki-67 levels, linking this diffusion restriction to high cellularity. Several perfusion parameters of the vascular compartment were significantly associated with HIF-1α. Analysis of other biological factors (VEGF, EGFR, tumor cell count, p53, and MVD) yielded inconclusive results. Larger datasets with homogenous acquisition are required to develop and test radiomic-based prediction models capable of capturing different aspects of the underlying tumor biology. Overall, our study shows that rapid and non-invasive characterization of tumor biology via MRI is feasible and could enhance clinical outcome predictions and personalized patient management for HNSCC.

Differential diagnosis of atypical and anaplastic meningiomas based on conventional MRI features and ADC histogram parameters using a logistic regression model nomogram

The purpose of the study was to determine the value of a logistic regression model nomogram based on conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) histogram parameters in differentiating atypical meningioma (AtM) from anaplastic meningioma (AnM). Clinical and imaging data of 34 AtM and 21 AnM diagnosed by histopathology were retrospectively analyzed. The whole tumor delineation along the tumor edge on ADC images and ADC histogram parameters were automatically generated and comparisons between the two groups using the independent samples t test or Mann-Whitney U test. Univariate and multivariate logistic regression analyses were used to construct the nomogram of the AtM and AnM prediction model, and the model's predictive efficacy was evaluated using calibration and decision curves. Significant differences in the mean, enhancement, perc.01%, and edema were noted between the AtM and AnM groups (P < 0.05). Age, sex, location, necrosis, shape, max-D, variance, skewness, kurtosis, perc.10%, perc.50%, perc.90%, and perc.99% exhibited no significant differences (P > 0.05). The mean and enhancement were independent risk factors for distinguishing AtM from AnM. The area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the nomogram were 0.871 (0.753-0.946), 80.0%, 81.0%, 79.4%, 70.8%, and 87.1%, respectively. The calibration curve demonstrated that the model's probability to predict AtM and AnM was in favorable agreement with the actual probability, and the decision curve revealed that the prediction model possessed satisfactory clinical availability. A logistic regression model nomogram based on conventional MRI features and ADC histogram parameters is potentially useful as an auxiliary tool for the preoperative differential diagnosis of AtM and AnM.

A very rare cause of leukoencephalopathy: Lymphomatosis cerebri

Leukoencephalopathy is a common finding on Magnetic Resonance Imaging (MRI), particularly in the elderly. A differential diagnosis may represent a very bet for clinicians when clear elements for diagnosis are lacking. Diffuse infiltrative "non mass like" leukoencephalopathy on MRI may represent the presentation of a very rare aggressive condition known as lymphomatosis cerebri (LC). The lack of orienting data, such as contrast enhancement on MRI or specific findings on examination of Cerebrospinal Fluid (CSF) or blood tests, may even far more complicate such a difficult diagnosis and orientate toward a less aggressive but time-losing mimic. A 69-old man initially presented to the Emergency Department (ED) complaining the recent appearance of unsteady walking, limitation of down and upgaze palsy, and hypophonia. Brain MRI revealed the presence of multiple, confluent hyperintense lesions on T2/Flair Attenuated Imaging Recovery (FLAIR) sequences involving either the withe matter of the semi-oval centres, juxtacortical structures, basal ganglia, or bilateral dentate nuclei. DWI sequences showed a wide restriction signal in the same brain regions but without any sign of contrast enhancement. Initial 18F-labeled fluoro-2-deoxyglucose positron emission tomography (FDG PET) and CSF studies were not relevant. Brain MRI revealed a high choline-signal, abnormal Choline/ N-Acetyl-Aspartate (NAA), and Choline/Creatine (Cr) ratios, as well as reduced NAA levels. Finally, a brain biopsy revealed the presence of diffuse large B-cell lymphomatosis cerebri. The diagnosis of lymphomatosis cerebri remains elusive. The valorisation of brain imaging may induce clinicians to suspect such a difficult diagnosis and go through the diagnostic algorithm.

Prediction of prognostic factors in breast cancer: A noninvasive method utilizing histogram parameters derived from Adc maps

Objective

The aim of this study is to investigate the relationship between histogram parameters and prognostic factors of breast cancer and to reveal the diagnostic performance of histogram parameters in predicting prognostic factors status.

Materials and methods

Ninety-two patients with a confirmed histopathological diagnosis of breast cancer were included in the study. Magnetic resonance imaging (MRI) was performed using a 1.5T scanner and two different b values were used for diffusion-weighted imaging (DWI) (b values: 0 s/mm², b: 800 s/mm²). For 3D histogram analysis, regions of interest (ROI) were drawn each slice of the lesion on apparent diffusion coefficient (ADC) maps. The following data were derived from the histogram analysis data: percentiles, skewness, kurtosis, and entropy. The relationship between prognostic factors and histogram analysis data was investigated using the Kolmogorov-Smirnov test, Shapiro-Wilk test, skewness-kurtosis test, independent t-test, Mann-Whitney U test, and Kruskal-Wallis test. Receiver operator characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the histogram parameters.

Results

ADC_max, kurtosis, and entropy parameters were statistically significantly correlated with tumor diameter (p = 0.002, p = 0.008, and p = 0.001, respectively). There was a significant difference in ADC_90% and ADC_max values, depending on estrogen receptor (ER) and progesterone receptor (PR) status. These values were lower in ER- and PR-positive than ER- and PR-negative patients (p = 0.02 and p = 0.001 vs. p = 0.018, p = 0.008). All ADC percentage values were lower in patients with a positive Ki-67 proliferation index as compared with those with a negative Ki-67 proliferation index (all p = 0.001). The entropy value was high in high-grade lesions and lesions with axillary involvement (p = 0.039 and p = 0.048, respectively). The highest area under the curve (AUC) for ER and PR status was calculated for the ADC_90% value with ROC curve analysis. The highest AUC for Ki-67 proliferation index was found for the ADC_50%.

Conclusion

Histogram analysis parameters derived from of ADC maps of whole lesions can reflect histopathological features of the tumors. Based on our study, it was concluded that histogram analysis parameters were related to the prognostic factors of the tumor.

Review of meningioma diagnosis and management

Meningiomas are the most common intracranial tumors in adult patients. Although the majority of meningiomas are diagnosed as benign, approximately 20% of cases are high-grade tumors that require significant clinical treatment. The gold standard for grading central nervous system tumors comes from the World Health Organization Classification of Tumors of the central nervous system. Treatment options also depend on the location, imaging, and histopathological features of the tumor. This review will cover diagnostic strategies for meningiomas, including 2021 updates to the World Health Organization's grading of meningiomas. Meningioma treatment plans are variable and highly dependent on tumor grading. This review will also update the reader on developments in the treatment of meningiomas, including surgery, radiation therapy and monoclonal antibody treatment.

Apparent Diffusion Coefficient in the Differentiation of Common Pediatric Brain Tumors in the Posterior Fossa: Different Region-of-Interest Selection Methods for Time Efficiency, Measurement Reproducibility, and Diagnostic Utility

OBJECTIVES

This study aimed to explore the diagnostic ability of apparent diffusion coefficient (ADC) values obtained from different region of interest (ROI) measurements in tumor parenchyma for differentiating posterior fossa tumors (PFTs) and the correlations between ADC values and Ki-67.

METHODS

Seventy-three pediatric patients with PFTs who underwent conventional diffusion-weighted imaging were recruited in this study. Five different ROIs were manually drawn by 2 radiologists (ROI-polygon, ROI-3 sections, ROI-3-5 ovals, ROI-more ovals, and ROI-whole). The interreader/intrareader repeatability, time required, diagnostic ability, and Ki-67 correlation analysis of the ADC values based on these ROI strategies were calculated.

RESULTS

Both interreader and intrareader reliabilities were excellent for ADC values among the different ROI strategies (intraclass correlation coefficient, 0.899-0.992). There were statistically significant differences in time consumption among the 5 ROI selection methods ( P < 0.001). The time required for the ROI-3-5 ovals was the shortest (32.23 ± 5.14 seconds), whereas the time required for the ROI-whole was the longest (204.52 ± 92.34 seconds). The diagnostic efficiency of the ADC values showed no significant differences among the different ROI measurements ( P > 0.05). The ADC value was negatively correlated with Ki-67 ( r = -0.745 to -0.798, all P < 0.0001).

CONCLUSIONS

The ROI-3-5 ovals method has the best interobserver repeatability, the shortest amount of time spent, and the best diagnostic ability. Thus, it is considered an effective measurement to produce ADC values in the evaluation of pediatric PFTs.

Evaluation of pretreatment ADC values as predictors of treatment response to neoadjuvant chemotherapy in patients with breast cancer - a multicenter study

BACKGROUND

Magnetic resonance imaging (MRI) can be used to diagnose breast cancer. Diffusion weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can reflect tumor microstructure in a non-invasive manner. The correct prediction of response of neoadjuvant chemotherapy (NAC) is crucial for clinical routine. Our aim was to compare ADC values between patients with pathological complete response (pCR) and non-responders based upon a multi-center design to improve the correct patient selection, which patient would more benefit from NAC and which patient would not.

METHODS

For this study, data from 4 centers (from Japan, Brazil, Spain and United Kingdom) were retrospectively acquired. The time period was overall 2003-2019. The patient sample comprises 250 patients (all female; median age, 50.5). In every case, pretreatment breast MRI with DWI was performed. pCR was assessed by experienced pathologists in every center using the surgical specimen in the clinical routine work up. pCR was defined as no residual invasive disease in either breast or axillary lymph nodes after NAC. ADC values between the group with pCR and those with no pCR were compared using the Mann-Whitney U test (two-group comparisons). Univariable and multivariabe logistic regression analysis was performed to predict pCR status.

RESULTS

Overall, 83 patients (33.2%) achieved pCR. The ADC values of the patient group with pCR were lower compared with patients without pCR (0.98 ± 0.23 × 10^- 3 mm²/s versus 1.07 ± 0.24 × 10^- 3 mm²/s, p = 0.02). The ADC value achieved an odds ratio of 4.65 (95% CI 1.40-15.49) in univariable analysis and of 3.0 (95% CI 0.85-10.63) in multivariable analysis (overall sample) to be associated with pCR status. The odds ratios differed in the subgroup analyses in accordance with the molecular subtype.

CONCLUSIONS

The pretreatment ADC-value is associated with pathological complete response after NAC in breast cancer patients. This could aid in clinical routine to reduce treatment toxicity for patients, who would not benefit from NAC. However, this must be tested in further studies, as the overlap of the ADC values in both groups is too high for clinical prediction.

Ankylosing spondylitis disease activity and serum vitamin D levels: A systematic review and meta-analysis

BACKGROUND

To prove that serum vitamin D (VD) levels are strongly associated with ankylosing spondylitis (AS) disease activity, the association between serum VD levels and key monitoring indicators of AS disease activity has been analyzed, such as the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP).

METHODS

Studies published in PubMed, Cochrane Library, EMBASE, and China National Knowledge Infrastructure by August 30, 2022 were searched, and 6 studies finally met the selection criteria. Serum 25-hydroxyvitamin D (25(OH)D), ESR, CRP levels, and correlation coefficients between serum VD and BASDAI, ESR, CRP in AS, and control in these studies were extracted for the meta-analysis.

RESULTS

When compared to controls, patients with AS had considerably lower blood 25(OH)D levels (MD = -7.53 ng/mL, 95% CI, -9.78 to -5.28, P < .001) and significantly higher ESR and CRP levels (ESR: MD = 11.75 mm/h, 95% CI, 4.20 to 19.31, P = .002; CRP: MD = 15.36 mg/L, 95% CI, 4.95 to 25.77, P = .004). Additionally, a negative correlation was discovered between serum VD levels and BASDAI, ESR, and CRP (Fisher' Z = -0.34, -0.38, -0.35, respectively).

CONCLUSION

The findings of our meta-analysis demonstrated a negative correlation between serum VD levels and the main monitoring indices of disease activity in patients with AS and verified that the differences in the continent and ethnicity may be one of the major contributors to this finding.

NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients

NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses. The project’s goal is to develop an open imaging biobank for the collection and preservation of a large amount of standardised imaging multimodal datasets, including computed tomography, magnetic resonance imaging, and positron emission tomography data, together with the corresponding patient-related and omics-related relevant information extracted from regional healthcare services using an adapted privacy-preserving model. The project is based on an open-source imaging biobank and an open-science oriented virtual research environment (VRE). Available integrative omics and multi-imaging data of three use cases (prostate cancer, rectal cancer, and gastric cancer) will be collected. All data confined in NAVIGATOR (i.e., standard and novel imaging biomarkers, non-imaging data, health agency data) will be used to create a digital patient model, to support the reliable prediction of the disease phenotype and risk stratification. The VRE that relies on a well-established infrastructure, called D4Science.org, will further provide a multiset infrastructure for processing the integrative omics data, extracting specific radiomic signatures, and for identification and testing of novel imaging biomarkers through big data analytics and artificial intelligence.

Recommendations for the diagnosis and radiological follow-up of pituitary neuroendocrine tumours

Pituitary neuroendocrine tumours (PitNETs) constitute a heterogeneous group of tumours with a gradually increasing incidence, partly accounted for by more sensitive imaging techniques and more extensive experience in neuroradiology in this regard. Although most PitNETs are indolent, some exhibit aggressive behaviour, and recurrence may be seen after surgical removal. The changes introduced in the WHO classification in 2017 and terminological debates in relation to neuroendocrine tumours warrant an update of the guidelines for the diagnosis, preoperative and postoperative management, and follow-up of response to treatment of PitNETs. This multidisciplinary document, an initiative of the Neuroendocrinology area of the Sociedad Española de Endocrinología y Nutrición [Spanish Society of Endocrinology and Nutrition] (SEEN), focuses on neuroimaging studies for the diagnosis, prognosis and follow-up of PitNETs. The basic requirements and elements that should be covered by magnetic resonance imaging are described, and a minimum radiology report to aid clinicians in treatment decision-making is proposed. This work supplements the consensus between the Neuroendocrinology area of the SEEN and the Sociedad Española de Anatomía Patológica [Spanish Society of Pathology] (SEAP) for the pathological study of PitNETs.

Local ablation of hepatocellular carcinoma by interstitial brachytherapy: prediction of outcome by diffusion-weighted imaging

BACKGROUND

Interstitial brachytherapy (iBT) has become a viable treatment option in the therapy of early and intermediate stage hepatocellular carcinoma (HCC). Prognostic imaging tools to predict patient outcome are missing.

PURPOSE

To assess the predictive value of baseline diffusion-weighted imaging in HCC before iBT with regard to local tumor control and overall survival (OS).

MATERIAL AND METHODS

We retrospectively identified 107 patients who underwent iBT for HCC from 2011 to 2018 from our database. Apparent diffusion coefficient (ADC) values for each treated lesion were analyzed in region of interest measurements. Additionally, explorative combined ratios adjusting total measured lesion area and mean measured lesion area per patient by ADC values were calculated. Measurements underwent a univariate and multivariate Cox regression analysis. The log rank test was then used to verify prognostic cutoff levels for median survival time.

RESULTS

A total of 189 lesions in 81 patients were measured. Median survival of patients was 46.0 months. Neither ADC parameter was indicative of local tumor control. Lesion size >5 cm was associated with lower local tumor control (hazard ratio [HR]=4.292, 95% confidence interval [CI]=1.285-14.331; P = 0.018). Average measured lesion area divided by ADC_min (ADC_{area mean, min}) was identified to independently predict OS (HR=1.994, 95% CI=1.172-3.392; P = 0.011). A cutoff based on the variable's median (0.29 × 10-4 AU) identified patients with poor outcome (OS 36 vs. 61 months) for lower ADC_{area mean, min} values as verified by the log-rank test (P = 0.040).

CONCLUSION

Pre-treatment ADC_{area mean, min} may serve as an independent predictor of OS in patients with HCC undergoing iBT.

Quantitative Values from Synthetic MRI Correlate with Breast Cancer Subtypes

The purpose of this study is to correlate quantitative T1, T2, and proton density (PD) values with breast cancer subtypes. Twenty-eight breast cancer patients underwent MRI of the breast including synthetic MRI. T1, T2, and PD values were correlated with Ki-67 and were compared between ER-positive and ER-negative cancers, and between Luminal A and Luminal B cancers. The effectiveness of T1, T2, and PD in differentiating the ER-negative from the ER-positive group and Luminal A from Luminal B cancers was evaluated using receiver operating characteristic analysis. Mean T2 relaxation of ER-negative cancers was significantly higher than that of ER-positive cancers (p < 0.05). The T1, T2, and PD values exhibited a strong positive correlation with Ki-67 (Pearson’s r = 0.75, 0.69, and 0.60 respectively; p < 0.001). Among ER-positive cancers, T1, T2, and PD values of Luminal A cancers were significantly lower than those of Luminal B cancers (p < 0.05). The area under the curve (AUC) of T2 for discriminating ER-negative from ER-positive cancers was 0.87 (95% CI: 0.69−0.97). The AUC of T1 for discriminating Luminal A from Luminal B cancers was 0.83 (95% CI: 0.61−0.95). In conclusion, quantitative values derived from synthetic MRI show potential for subtyping of invasive breast cancers.

Diffusion Breast MRI: Current Standard and Emerging Techniques

The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.

The association between common serum adipokines levels and postmenopausal osteoporosis: A meta‐analysis

The clinical relevance of blood levels of adipokines in individuals with postmenopausal osteoporosis (PMOP) has not been previously clarified. We performed this meta‐analysis to clarify the association between three common adipokines levels and the occurrence of PMOP. PubMed, Embase, Cochrane library, and China National Knowledgement Infrastructure (CNKI) were searched for collecting articles published before 31 October 2021, without language and status restrictions. Fourteen studies met the selection criteria. Meta‐analysis revealed that blood leptin level was remarkably lower (mean difference [MD], −1.94; 95% confidence interval [CI], −3.83 to −0.06; I² = 96%) and adiponectin level was remarkably higher (MD, 3.48; 95% CI, 2.36 to 4.60; I² = 90%) in individuals with PMOP than healthy individuals with normal bone mineral density (BMD). However, the statistical difference in leptin level was changed after eliminating the confounding influence of leptin sources and assay approaches. Furthermore, a positive association (r = 0.28) between leptin level and body mass index (BMI) as well as a negative association (r = −0.33) between adiponectin level and BMD was found. Moreover, adiponectin had the highest probability of predicting PMOP (84%). Current evidence suggests that leptin positively affects BMI and adiponectin negatively affects BMD, and adiponectin is the most relevant adipokine negatively associated with PMOP.

Investigation of breast cancer microstructure and microvasculature from time-dependent DWI and CEST in correlation with histological biomarkers

We investigated the associations of time-dependent DWI, non-Gaussian DWI, and CEST parameters with histological biomarkers in a breast cancer xenograft model. 22 xenograft mice (7 MCF-7 and 15 MDA-MB-231) were scanned at 4 diffusion times [T_d = 2.5/5 ms with 11 b-values (0–600 s/mm²) and T_d = 9/27.6 ms with 17 b-values (0–3000 s/mm²), respectively]. The apparent diffusion coefficient (ADC) was estimated using 2 b-values in different combinations (ADC^0–600 using b = 0 and 600 s/mm² and shifted ADC [sADC^200–1500] using b = 200 and 1500 s/mm²) at each of those diffusion times. Then the change (Δ) in ADC/sADC between diffusion times was evaluated. Non-Gaussian diffusion and intravoxel incoherent motion (IVIM) parameters (ADC₀, the virtual ADC at b = 0; K, Kurtosis from non-Gaussian diffusion; f, the IVIM perfusion fraction) were estimated. CEST images were acquired and the amide proton transfer signal intensity (APT SI) were measured. The ΔsADC_9–27.6 (between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{9\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC9ms200-1500 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC27.6ms200-1500 and ΔADC_2.5_sADC_27.6 (between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{ADC}}_{{2.5\, {\text{ms}}}}^{0{-}600}$$\end{document}ADC2.5ms0-600 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$\end{document}sADC27.6ms200-1500) was significantly larger for MCF-7 groups, and ΔADC_2.5_sADC_27.6 was positively correlated with Ki67_max and APT SI. ADC₀ decreased significantly in MDA-MB-231 group and K increased significantly with T_d in MCF-7 group. APT SI and cellular area had a moderately strong positive correlation in MDA-MB-231 and MCF-7 tumors combined, and there was a positive correlation in MDA-MB-231 tumors. There was a significant negative correlation between APT SI and the Ki-67-positive ratio in MDA-MB-231 tumors and when combined with MCF-7 tumors. The associations of ΔADC_2.5_sADC_27.6 and API SI with Ki-67 parameters indicate that the T_d-dependent DW and CEST parameters are useful to predict the histological markers of breast cancers.

DWI of the Breast - Possibilities and Limitations

BACKGROUND

 The MRI of the breast is of great importance in the diagnosis of disorders of the breast. This can be stated for the primary diagnosis as well as the follow up. Of special interest is diffusion weighted imaging (DWI), which has an increasingly important role. The present review provides results regarding the diagnostic and prognostic relevance of DWI for disorders of the breast.

METHODS

 Under consideration of the recently published literature, the clinical value of DWI of the breast is discussed. Several diagnostic applications are shown, especially for the primary diagnosis of unclear tumors of the breast, the prediction of the axillary lymph node status and the possibility of a native screening. Moreover, correlations between DWI and histopathology features and treatment prediction with DWI are provided.

RESULTS

 Many studies have shown the diagnostic value of DWI for the primary diagnosis of intramammary lesions. Benign lesions of the breast have significantly higher apparent diffusion coefficients (ADC values) compared to malignant tumors. This can be clinically used to reduce unnecessary biopsies in clinical routine. However, there are inconclusive results for the prediction of the histological subtype of the breast cancer. DWI can aid in the prediction of treatment to neoadjuvant chemotherapy.

CONCLUSION

 DWI is a very promising imaging modality, which should be included in the standard protocol of the MRI of the breast. DWI can provide clinically value in the diagnosis as well as for prognosis in breast cancer.

KEY POINTS

  · DWI can aid in the discrimination between benign and malignant tumors of the breast and therefore avoiding unnecessary biopsies.. · The ADC value cannot discriminate between immunhistochemical subtypes of the breast cancer. · The ADC value of breast cancer increases under neoadjuvant chemotherapy and can by this aid in treatment prediction.. · There is definite need of standardisation for clinical translation.

CITATION FORMAT

· Meyer HJ, Martin M, Denecke T. DWI of the Breast - Possibilities and Limitations. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1775-8572.

Breast Cancer Subtypes and Quantitative Magnetic Resonance Imaging: A Systemic Review

Magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast cancer detection. This systematic review investigated the role of quantitative MRI features in classifying molecular subtypes of breast cancer. We performed a literature search of articles published on the application of quantitative MRI features in invasive breast cancer molecular subtype classification in PubMed from 1 January 2002 to 30 September 2021. Of the 1275 studies identified, 106 studies with a total of 12,989 patients fulfilled the inclusion criteria. Bias was assessed based using the Quality Assessment of Diagnostic Studies. All studies were case-controlled and research-based. Most studies assessed quantitative MRI features using dynamic contrast-enhanced (DCE) kinetic features and apparent diffusion coefficient (ADC) values. We present a summary of the quantitative MRI features and their correlations with breast cancer subtypes. In DCE studies, conflicting results have been reported; therefore, we performed a meta-analysis. Significant differences in the time intensity curve patterns were observed between receptor statuses. In 10 studies, including a total of 1276 lesions, the pooled difference in proportions of type Ⅲ curves (wash-out) between oestrogen receptor-positive and -negative cancers was not significant (95% confidence interval (CI): [−0.10, 0.03]). In nine studies, including a total of 1070 lesions, the pooled difference in proportions of type 3 curves between human epidermal growth factor receptor 2-positive and -negative cancers was significant (95% CI: [0.01, 0.14]). In six studies including a total of 622 lesions, the pooled difference in proportions of type 3 curves between the high and low Ki-67 groups was significant (95% CI: [0.17, 0.44]). However, the type 3 curve itself is a nonspecific finding in breast cancer. Many studies have examined the relationship between mean ADC and breast cancer subtypes; however, the ADC values overlapped significantly between subtypes. The heterogeneity of ADC using kurtosis or difference, diffusion tensor imaging parameters, and relaxation time was reported recently with promising results; however, current evidence is limited, and further studies are required to explore these potential applications.

Whole-lesion histogram analysis of apparent diffusion coefficient for the assessment of non-mass enhancement lesions on breast MRI

Objectives

To investigate the application of apparent diffusion coefficient (ADC) histogram analysis in differentiating between benign and malignant breast lesions detected as non-mass enhancement on MRI.

Materials and Methods

A retrospective study was conducted for 25 malignant and 26 benign breast lesions showing non-mass enhancement on breast MRI. An experienced radiologist without prior knowledge of the pathological results drew a region of interest (ROI) outlining the periphery of each lesion on the ADC map. A histogram was then made for each lesion. Following a univariate analysis of 18 summary statistics values, we conducted statistical discrimination after hierarchical clustering using Ward’s method. A comparison between the malignant and the benign groups was made using multiple logistic regression analysis and the Mann-Whitney U test. A P -value of less than 0.05 was considered statistically significant.

Results

Univariate analysis for the 18 summary statistics values showed the malignant group had greater entropy (P < 0.001) and lower uniformity (P < 0.001). While there was no significant difference in mean and skewness values, the malignant group tended to show a lower mean (P = 0.090) and a higher skewness (P = 0.065). Hierarchical clustering of the 18 summary statistics values identified four values (10th percentile, entropy, skewness, and uniformity) of which the 10th percentile values were significantly lower for the malignant group (P = 0.035).

Conclusions

Whole-lesion ADC histogram analysis may be useful for differentiating malignant from benign lesions which show non-mass enhancement on breast MRI.

The Utility of ADC First-Order Histogram Features for the Prediction of Metachronous Metastases in Rectal Cancer: A Preliminary Study

Simple Summary

Metachronous metastases are the main factors affecting survival in rectal cancer, and 15–25% of patients will develop them at a 5-year follow-up. Early identification of patients with higher risk of developing distant metachronous metastases would help to improve therapeutic protocols and could allow for a more accurate, personalized management. Apparent diffusion coefficient (ADC) represents an MRI quantitative biomarker, which can assess the diffusion characteristics of tissues, depending on the microscopic mobility of water, showing information related to tissue cellularity. First-order histogram-based features statistics describe the frequency distribution of intensity values within a region of interest, revealing microstructural alterations. In our study, we demonstrated that whole-tumor ADC first-order features may provide useful information for the assessment of rectal cancer prognosis, regarding the occurrence of metachronous metastases.

Abstract

This study aims the ability of first-order histogram-based features, derived from ADC maps, to predict the occurrence of metachronous metastases (MM) in rectal cancer. A total of 52 patients with pathologically confirmed rectal adenocarcinoma were retrospectively enrolled and divided into two groups: patients who developed metachronous metastases (n = 15) and patients without metachronous metastases (n = 37). We extracted 17 first-order (FO) histogram-based features from the pretreatment ADC maps. Student’s t-test and Mann–Whitney U test were used for the association between each FO feature and presence of MM. Statistically significant features were combined into a model, using the binary regression logistic method. The receiver operating curve analysis was used to determine the diagnostic performance of the individual parameters and combined model. There were significant differences in ADC 90th percentile, interquartile range, entropy, uniformity, variance, mean absolute deviation, and robust mean absolute deviation in patients with MM, as compared to those without MM (p values between 0.002–0.01). The best diagnostic was achieved by the 90th percentile and uniformity, yielding an AUC of 0.74 [95% CI: 0.60–0.8]). The combined model reached an AUC of 0.8 [95% CI: 0.66–0.90]. Our observations point out that ADC first-order features may be useful for predicting metachronous metastases in rectal cancer.

The utility of diffusion-weighted imaging and ADC values in the characterization of mumps orchitis and seminoma

BACKGROUND

Diffusion-weighted imaging (DWI) can quantitatively reflect the diffusion characteristics of tissues, providing a theoretical basis for qualitative diagnosis and quantitative analysis of a disease.

PURPOSE

To characterize testicular lesions that present as a hypointense signal on magnetic resonance imaging (MRI) T2-weighted images using DWI.

MATERIAL AND METHODS

Study participants were divided into three groups. Group A were healthy controls (n = 35), group B included patients with mumps orchitis (n = 20), and group C included patients with seminoma (n = 15). DWI sequences used b-values of 0, 1000, and 2000 s/mm². Apparent diffusion coefficient (ADC) values between 1000 and 2000 s/mm² were calculated by MRI postprocessing software. The Kruskal-Wallis test and receiver operating characteristic analysis were performed to evaluate how well ADC values distinguished between mumps orchitis and seminoma.

RESULTS

Normal testicular tissue showed a hyperintense signal on DWI and hypointensity on the ADC map: mean ADC value was 0.77 (0.69-0.85) ± 0.08 ×10^-3 mm²/s. Mumps orchitis and seminoma showed slight hyperintensity on DWI: mean ADC values were 0.85 (0.71-0.99) ± 0.15 ×10^-3 mm²/s and 0.43 (0.39-0.47) ± 0.04 × 10^-3 mm²/s, respectively. There were statistically significant differences in mean ADC values between normal testicular tissue and seminoma and between mumps orchitis and seminoma. The cutoff ADC value for differentiating seminoma from mumps orchitis was 0.54 × 10^-3 mm²/s. The sensitivity, specificity, and Youden Index for diagnosing seminoma were 99%, 31%, and 30%, respectively.

CONCLUSION

High b-value DWI has potential utility for differentiating mumps orchitis from seminoma in the clinical setting.

Different facets of intracranial central nervous system lymphoma and its imaging mimics

Lymphomas of the central nervous system (CNS) are broadly classified into primary CNS lymphoma (PCNSL) and secondary CNS lymphoma (SCNSL). PCNSL refers to lymphoma restricted to the brain, leptomeninges, spinal cord, or eyes without evidence of it outside the CNS at primary diagnosis, while SCNSL refers to secondary CNS involvement by systemic lymphoma. The brain is the most common site of involvement and intracranial CNS lymphoma has a highly variable imaging appearance and varies according to the patient’s clinical profile and immunity. This pictorial essay aims to illustrate the different facets of intracranial CNS lymphomas on neuroimaging. This enables radiologists to be familiarized with their key diagnostic features and differentiate from their differential diagnoses, leading to early diagnosis, and treatment.

Characterization of high-grade pineal region lesions: the usefulness of apparent diffusion coefficient volumetric values

BACKGROUND

High-grade pineal region tumors are rare and heterogeneous types of primary central nervous system neoplasms; radiological differential diagnosis is challenging but it is important because it has a therapeutic relevance.

PURPOSE

To discriminate among high-grade pineal region tumors by combining apparent diffusion coefficient (ADC) volumetric values and qualitative features in order to predict their histology.

MATERIAL AND METHODS

Twenty-two patients with high-grade pineal region tumors were assessed by qualitative and quantitative analysis. Margins, T2-weighted signal intensity, contrast enhancement, hemorrhage, calcifications, different volumetric ADC fractions (ADC_mean, ADC_max, ADC_min) were evaluated and were compared to the histopathologic findings (cell count and proliferation index).

RESULTS

Our qualitative imaging data showed that only margins were different among different tumors and each tumor type showed peculiar age onset. ADC_mean was found the best quantitative value to discriminate high-grade tumors of the pineal region. ADC_mean correlated with proliferation index but not with cell count. ADC_mean values were lower in tumors with higher proliferation rate and a significant difference in ADC_mean values were found between germinomas and pineoblastomas, between germinomas and papillary tumors and between papillary tumors and pineoblastomas. Moreover, the cut-off value of 0.865 × 10^-3 mm²/s for ADC_mean (ADC mean threshold value) could differentiate germinoma from pineoblastomas with the best combination of sensitivity and specificity.

CONCLUSION

The ADC_mean value measured on the whole tumor, reflecting tumor proliferative activity, may be a practical and non-invasive marker for predicting tumor histology in high-grade pineal region lesions and might be useful in preoperative assessment.

Diffusion-Weighted Imaging of Different Breast Cancer Molecular Subtypes: A Systematic Review and Meta-Analysis

Background

Magnetic resonance imaging can be used to diagnose breast cancer (BC). Diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure.

Objectives

This analysis aimed to compare ADC values between molecular subtypes of BC based on a large sample of patients.

Method

The MEDLINE library and Scopus database were screened for the associations between ADC and molecular subtypes of BC up to April 2020. The primary end point of the systematic review was the ADC value in different BC subtypes. Overall, 28 studies were included.

Results

The included studies comprised a total of 2,990 tumors. Luminal A type was diagnosed in 865 cases (28.9%), luminal B in 899 (30.1%), human epidermal growth factor receptor (Her2)-enriched in 597 (20.0%), and triple-negative in 629 (21.0%). The mean ADC values of the subtypes were as follows: luminal A: 0.99 × 10-3 mm2/s (95% CI 0.94-1.04), luminal B: 0.97 × 10-3 mm2/s (95% CI 0.89-1.05), Her2-enriched: 1.02 × 10-3 mm2/s (95% CI 0.95-1.08), and triple-negative: 0.99 × 10-3 mm2/s (95% CI 0.91-1.07).

Conclusions

ADC values cannot be used to discriminate between molecular subtypes of BC.

Discrimination between malignant and benign thyroid tumors by diffusion-weighted imaging - A systematic review and meta analysis

PURPOSE

Magnetic resonance imaging is used to stage thyroid tumors. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Our aim was to compare ADC values of malignant and benign thyroid lesions based on a large sample.

METHODS

MEDLINE library, EMBASE and SCOPUS databases were screened for the associations between ADC values and thyroid lesions up to August 2021. The primary endpoint of the systematic review were ADC values of benign and malignant thyroid lesions. In total, 29 studies were suitable for the analysis and were included into the present study.

RESULTS

The included studies comprised a total of 2137 lesions, 1118 (52.3%) benign and 1019 (47.7%) malignant lesions. The pooled mean ADC value of the benign thyroid lesions was 1.88 × 10^-3 mm²/s [95% CI 1.77-2.0] and the pooled mean ADC value of malignant thyroid lesions was 1.15 × 10^-3 mm²/s [95% CI 1.04-1.25].

CONCLUSIONS

ADC can well discriminate benign and malignant thyroid tumors. Therefore, DWI should be implemented into the presurgical diagnostic work-up in clinical routine.

68Ga-DOTATATE PET/CT and MRI with Diffusion-Weighted Imaging (DWI) in Short- and Long-Term Assessment of Tumor Response of Neuroendocrine Liver Metastases (NELM) Following Transarterial Radioembolization (TARE)

Simple Summary

TARE with ⁹⁰Yttrium has become a valuable treatment option for patients with unresectable NELMs. However, early evaluation of therapy response remains challenging as size-based response assessments (such as RECIST) are known to be limited, especially in slow-growing tumors. Alternatives such as quantitative evaluation of SUV of ⁶⁸Ga-DOTATATE PET/CT and ADC of DWI-MRI have not been compared so far. We found that early percentage changes in SUV tumor-to-organ ratios on first follow-up after TARE could predict longer HPFS in patients with NELM and were superior to ΔSUVmax/SUVmean alone or to ΔADC.

Abstract

The aim of this study was to evaluate the role of SUV and ADC in assessing early response in patients with NELM following TARE. Thirty-two patients with pre- and postinterventional MRI with DWI and ⁶⁸Ga-DOTATATE PET/CT were included. ADC and SUV of three target lesions and of tumor-free spleen and liver tissue were determined on baseline and first follow-up imaging, and tumor to spleen (T/S) and tumor to liver (T/L) ratios were calculated. Response was assessed by RECIST 1.1 and mRECIST on first follow-up, and long-term response was defined as hepatic progression-free survival (HPFS) over 6, 12, and <24 months. In responders, intralesional ADC values increased and SUV decreased significantly regardless of standard of reference for response assessment (mRECIST/RECIST/HPFS > 6/12/24 m). Using ROC analysis, ΔSUV T/S ratio (max/max) and ΔSUV T/L ratio (max/mean) were found to be the best and most robust metrics to correlate with longer HPFS and were superior to ΔADC. ΔT/S ratio (max/max) < 23% was identified as an optimal cut-off to discriminate patients with longer HPFS (30.2 m vs. 13.4 m; p = 0.0002). In conclusion, early percentage changes in SUV tumor-to-organ ratios on first follow-up seem to represent a prognostic marker for longer HPFS and may help in assessing therapeutic strategies.

An analysis of Ki-67 expression in stage 1 invasive ductal breast carcinoma using apparent diffusion coefficient histograms

Background

To investigate the value of apparent diffusion coefficient (ADC) histograms in differentiating Ki-67 expression in T1 stage invasive ductal breast carcinoma (IDC).

Methods

The records of 111 patients with pathologically confirmed T1 stage IDC who underwent magnetic resonance imaging prior to surgery were retrospectively reviewed. The expression of Ki-67 in tumor tissue samples from the patients was assessed using immunohistochemical (IHC) staining, with a cut-off value of 25% for high Ki-67 labeling index (LI). ADC images of the maximum lay of tumors were selected, and the region of interest (ROI) of each lay was delineated using the MaZda software and analyzed by histogram. The correlations between the histogram characteristic parameters and the Ki-67 LI were investigated. Additionally, the histogram characteristic parameters of the high Ki-67 group (n=54) and the low Ki-67 group (n=57) were statistically analyzed to determine the characteristic parameters with significant difference. Receiver operator characteristic (ROC) analyses were further performed for the significant parameters.

Results

The mean value, and the 1st, 10th, 50th, 90th, and 99th percentiles were found to be negatively correlated with the expression of Ki-67 (all P values <0.001), with a correlation coefficient of -0.624, -0.749, -0.717, -0.621, -0.500, and -0.410, respectively. In the high Ki-67 group, the mean value, and the 1st, 10th, 50th, 90th, and 99th percentiles extracted by the histogram were significantly lower (all P values <0.05) than that of the low Ki-67 group, with areas under the ROC curves ranging from 0.717-0.856. However, the variance, skewness, and kurtosis did not differ between the two groups (all P values >0.05).

Conclusions

Histogram-derived parameters for ADC images can serve as a reliable tool in the prediction of Ki-67 proliferation status in patients with T1 stage IDC. Among the significant ADC histogram values, the 1st and 10th percentiles showed the best predictive values.

Diffusion-Weighted Imaging Reflects Tumor Grading and Microvascular Invasion in Hepatocellular Carcinoma

BACKGROUND

To date, there are inconsistent data about relationships between diffusion-weighted imaging (DWI) and tumor grading/microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Our purpose was to systematize the reported results regarding the role of DWI in prediction of tumor grading/MVI in HCC.

METHOD

MEDLINE library, Scopus, and Embase data bases were screened up to December 2019. Overall, 29 studies with 2,715 tumors were included into the analysis. There were 20 studies regarding DWI and tumor grading, 8 studies about DWI and MVI, and 1 study investigated DWI, tumor grading, and MVI in HCC.

RESULTS

In 21 studies (1,799 tumors), mean apparent diffusion coefficient (ADC) values (ADC_mean) were used for distinguishing HCCs. ADC_mean of G1-3 lesions overlapped significantly. In 4 studies (461 lesions), minimum ADC (ADC_min) was used. ADC_min values in G1/2 lesions were over 0.80 × 10^-3 mm²/s and in G3 tumors below 0.80 × 10^-3 mm²/s. In 4 studies (241 tumors), true diffusion (D) was reported. A significant overlapping of D values between G1, G2, and G3 groups was found. ADC_mean and MVI were analyzed in 9 studies (1,059 HCCs). ADC_mean values of MIV+/MVI- lesions overlapped significantly. ADC_min was used in 4 studies (672 lesions). ADC_min values of MVI+ tumors were in the area under 1.00 × 10^-3 mm²/s. In 3 studies (227 tumors), D was used. Also, D values of MVI+ lesions were predominantly in the area under 1.00 × 10^-3 mm²/s.

CONCLUSION

ADC_min reflects tumor grading, and ADC_min and D predict MVI in HCC. Therefore, these DWI parameters should be estimated for every HCC lesion for pretreatment tumor stratification. ADC_mean cannot predict tumor grading/MVI in HCC.

Relationships between apparent diffusion coefficient (ADC) histogram analysis parameters and PD-L 1-expression in head and neck squamous cell carcinomas: a preliminary study

BACKGROUND

Immunotherapy has become a cornerstone of the modern cancer treatment. It might be crucial to predict its expression non-invasively by imaging. The present study used diffusion-weighted imaging (DWI) quantified by whole lesion apparent diffusion coefficient (ADC) values to elucidate possible associations with programmed cell death ligand 1(PD-L1) expression in head and neck squamous cell cancer (HNSCC).

PATIENTS AND METHODS

Overall, 29 patients with primary HNSCC of different localizations were involved in the study. DWI was obtained by using a sequence with b _- values of 0 and 800 s/mm² on a 3 T MRI. ADC values were evaluated with a whole lesion measurement and a histogram approach. PD-L1 expression was estimated on bioptic samples before any form of treatment using 3 scores, tumor positive score (TPS), immune cell score (ICS), and combined positive score (CPS).

RESULTS

An inverse correlation between skewness derived from ADC values and ICS was identified (r = -0.38, p = 0.04). ADC_max tended to correlate with ICS (r = -0.35, p = 0.06). Other ADC parameters did not show any association with the calculated scores.

CONCLUSIONS

There is a weak association between skewness derived from ADC values and PD-L1 expression in HNSCC, which might not be strong enough to predict PD-L1 expression in clinical routine. Presumably, ADC values are more influenced by complex histopathology compartments, comprising cellular and extracellular aspects of tumors than only of a single subset of tumor associated cells.

Whole-Lesion Histogram Analysis of the Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker for Assessing the Level of Tumor-Infiltrating Lymphocytes: Value in Molecular Subtypes of Breast Cancer

Purpose

To assess whether apparent diffusion coefficient (ADC) metrics can be used to assess tumor-infiltrating lymphocyte (TIL) levels in breast cancer, particularly in the molecular subtypes of breast cancer.

Methods

In total, 114 patients with breast cancer met the inclusion criteria (mean age: 52 years; range: 29–85 years) and underwent multi-parametric breast magnetic resonance imaging (MRI). The patients were imaged by diffusion-weighted (DW)-MRI (1.5 T) using a single-shot spin-echo echo-planar imaging sequence. Two readers independently drew a region of interest (ROI) on the ADC maps of the whole tumor. The mean ADC and histogram parameters (10^th, 25^th, 50^th, 75^th, and 90^th percentiles of ADC, skewness, entropy, and kurtosis) were used as features to analyze associations with the TIL levels in breast cancer. Additionally, the correlation between the ADC values and Ki-67 expression were analyzed. Continuous variables were compared with Student’s t-test or Mann-Whitney U test if the variables were not normally distributed. Categorical variables were compared using Pearson’s chi-square test or Fisher’s exact test. Associations between TIL levels and imaging features were evaluated by the Mann-Whitney U and Kruskal-Wallis tests.

Results

A statistically significant difference existed in the 10^th and 25^th percentile ADC values between the low and high TIL groups in breast cancer (P=0.012 and 0.027). For the luminal subtype of breast cancer, the 10^th percentile ADC value was significantly lower in the low TIL group (P=0.041); for the non-luminal subtype of breast cancer, the kurtosis was significantly lower in the low TIL group (P=0.023). The Ki-67 index showed statistical significance for evaluating the TIL levels in breast cancer (P=0.007). Additionally, the skewness was significantly higher for samples with high Ki-67 levels in breast cancer (P=0.029).

Conclusions

Our findings suggest that whole-lesion ADC histogram parameters can be used as surrogate biomarkers to evaluate TIL levels in molecular subtypes of breast cancer.

Prediction of Response in Head and Neck Tumor: Focus on Main Hot Topics in Research

Radiation therapy is a cornerstone in the treatment of head and neck cancer patients; actually, their management is based on clinical and radiological staging with all patients at the same stage treated in the same way. Recently the increasing knowledge in molecular characterization of head and neck cancer opens the way for a more tailored treatment. Patient outcomes could be improved by a personalized radiotherapy beyond technological and anatomical precision. Several tumor markers are under evaluation to understand their possible prognostic or predictive value. In this paper we discuss those markers specific for evaluate response to radiation therapy in head and neck cancer for a shift toward a biological personalization of radiotherapy.

Apparent diffusion coefficient cannot discriminate metastatic and non-metastatic lymph nodes in rectal cancer: a meta-analysis

BACKGROUND

Our aim was to provide data regarding use of diffusion-weighted imaging (DWI) for distinguishing metastatic and non-metastatic lymph nodes (LN) in rectal cancer.

METHODS

MEDLINE library, EMBASE, and SCOPUS database were screened for associations between DWI and metastatic and non-metastatic LN in rectal cancer up to February 2021. Overall, 9 studies were included into the analysis. Number, mean value, and standard deviation of DWI parameters including apparent diffusion coefficient (ADC) values of metastatic and non-metastatic LN were extracted from the literature. The methodological quality of the studies was investigated according to the QUADAS-2 assessment. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian, and Laird random-effects models with inverse-variance weights were used to account the heterogeneity between the studies. Mean DWI values including 95% confidence intervals were calculated for metastatic and non-metastatic LN.

RESULTS

ADC values were reported for 1376 LN, 623 (45.3%) metastatic LN, and 754 (54.7%) non-metastatic LN. The calculated mean ADC value (× 10^-3 mm²/s) of metastatic LN was 1.05, 95%CI (0.94, 1.15). The calculated mean ADC value of the non-metastatic LN was 1.17, 95%CI (1.01, 1.33). The calculated sensitivity and specificity were 0.81, 95%CI (0.74, 0.89) and 0.67, 95%CI (0.54, 0.79).

CONCLUSION

No reliable ADC threshold can be recommended for distinguishing of metastatic and non-metastatic LN in rectal cancer.

The Association Between Serum/Plasma Leptin Levels and Obstructive Sleep Apnea Syndrome: A Meta-Analysis and Meta-Regression

BACKGROUND

Obstructive sleep apnea syndrome (OSAS) is associated with various adipokines. Leptin, a common adipokine, has attracted considerable attention of many researchers in recent years. So far, there has been little agreement on whether blood leptin levels differ in patients with OSAS. Thus, this meta-analysis examined the relationship between serum/plasma leptin levels and the occurrence of OSAS.

METHOD

WanFang, Embase, CNKI, Medline, SinoMed, Web of Science, and PubMed were searched for articles before March 30, 2021, with no language limitations. STATA version 11.0 and R software version 3.6.1 were used to analyze the obtained data. The weighted mean difference and correlation coefficients were used as the main effect sizes with a random-effects model and a fixed-effects model, respectively. Trial sequential analysis was conducted using dedicated software.

RESULT

Screening of 34 publications identified 45 studies that met the inclusion criteria of this meta-analysis and meta-regression. Our results suggested that plasma/serum leptin levels were remarkably higher in individuals with OSAS than in healthy individuals. Subgroup analyses were performed based on OSAS severity, ethnicity, age, body mass index, assay type, and sample source. The serum and plasma leptin levels were increased in nearly all OSAS subgroups compared to those in the corresponding control groups. Meta-regression analysis indicated that age, BMI, severity, assay approaches, study design, PSG type and ethnicity did not have independent effect on leptin levels. Furthermore, a positive relationship between the serum/plasma leptin level and apnea-hypopnea index (AHI) was found in the meta-analysis. The results of the trial sequential analysis suggested that the enrolled studies surpassed the required information size, confirming that our study findings were reliable.

CONCLUSION

Our study results demonstrate that OSAS patients have higher leptin levels in serum/plasma compared to controls, and the serum/plasma leptin level is positively correlated with AHI, especially in adults.

Long-term apparent diffusion coefficient value changes in patients undergoing radiosurgical treatment of meningiomas

PURPOSE

A noninvasive method to predict the progress or treatment response of meningiomas is desirable to improve the tumor management. Studies showed that apparent diffusion coefficient (ADC) pretreatment values can predict treatment response in brain tumors. The aim of this study was to analyze changes of intratumoral ADC values in patients with meningiomas undergoing conservative or radiosurgery.

METHOD

MR images of 51 patients with diagnose of meningiomas were retrospectively reviewed. Twenty-five patients undergoing conservative or radiosurgery treatment, respectively, were included in the study. The follow-up data ranged between 1 and 10 years. Based on ROI analysis, the mean ADC values, ADC_10%min, and ADC_90%max were evaluated at different time points during follow-up.

RESULTS

Baseline ADC values in between both groups were similar. The ADC_mean values, ADC_10%min, and ADC_90%max within the different groups did not show any significant changes during the follow-up times in the untreated (ADC_mean over 10 years period: 0.87 ± 0.05 × 10^-3 mm²/s) and radiosurgically treated (ADC_mean over 4 years period: 1.02 ± 0.12 × 10^-3 mm²/s) group. However, statistically significant difference was observed when comparing the ADC_mean and ADC_90%max values of untreated with radiosurgically treated (p < 0.0001) meningiomas. Also, ADC_10%min revealed statistically significant difference between the untreated and the radiosurgery group (p < 0.05).

CONCLUSIONS

ADC values in conservatively managed meningiomas remain stable during the follow-up. However, meningiomas undergoing radiosurgery reveal significant change of the mean ADC values over time, suggesting that ADC may reflect a change in the biological behavior of the tumor. These observations might suggest the value of ADC changes as an indicator of treatment response.

Associations between IVIM histogram parameters and histopathology in rectal cancer

PURPOSE

Histogram analysis can better reflect tumor heterogeneity than conventional imaging analysis. The present study analyzed possible correlations between histogram analysis parameters derived from Intravoxel-incoherent imaging (IVIM) and histopathological features in rectal cancer (RC).

METHODS

Seventeen patients with histopathologically proven rectal adenocarcinomas were retrospectively acquired. In all cases, pelvic MRI was performed. Diffusion weighted imaging was obtained using a multi-slice single-shot echo-planar imaging sequence with b values of 0, 50, 200, 500 and 1000 s/mm². Simplified IVIM analysis was performed using the IntelliSpace portal, version 10 and the following images were generated: f (perfusion fraction) map, D (true diffusion coefficient) map, and ADC map utilizing all b-values. Histogram based analysis of signal intensities was performed for every IVIM map using an in-house matlab tool. Histopathology was investigated using Ki 67 specimens with calculation of Ki 67-index and cellularity. CD31 stained specimens were used for calculation of microvessel density (MVD).

RESULTS

There were statistically significant correlations between Ki 67 index and mode derived from ADC as well as entropy from f, r=-0.50, p=.04 and r=-0.55, p=.02, respectively. MVD correlated well with parameters derived from f.

CONCLUSION

IVIM histogram analysis parameters can reflect histopathology in RC. ADC and D values are associated with proliferation potential. Perfusion fraction f is associated with MVD.

Diffusion-weighted MR imaging histogram analysis in HIV positive and negative patients with primary central nervous system lymphoma as a predictor of outcome and tumor proliferation

INTRODUCTION

Ki-67 expression, a marker of tumor proliferation, is considered a prognostic factor in primary CNS lymphoma (PCNSL). Apparent diffusion coefficient (ADC) parameters have also been proposed as imaging biomarkers for tumor progression and proliferative activity in various malignancies. The aim of this study is to investigate the correlation between ADC parameters, Ki-67 expression, overall survival (OS) and progression free survival (PFS) in PCNSL.

MATERIALS AND METHODS

Patients diagnosed with PCNSL at MD Anderson Cancer Center between Mar 2000 and Jul 2016 and at Ben Taub Hospital between Jan 2012 and Dec 2016 were retrospectively studied. Co-registered ADC maps and post-contrast images underwent whole tumor segmentation. Normalized ADC parameters (nADC) were calculated as the ratio to normal white matter. Percentiles of nADC were calculated and were correlated with Ki-67 using Pearson's correlation coefficient and clinical outcomes (OS and PFS) using Cox proportional hazards models.

RESULTS

Selection criteria yielded 90 patients, 23 patients living with HIV (PLWH) and 67 immunocompetent patients. Above median values for nADC_mean, nADC₁₅, nADC₇₅ and nADC₉₅ were associated with improved OS in all patients (p < 0.05). Above median values for nADC_min, nADC_mean, nADC₁, nADC₅ and kurtosis were associated with improved PFS in all patients (p < 0.05). In patients with available Ki-67 expression data (n = 22), nADC_mean, nADC₁₅ and nADC₇₅ inversely correlated with Ki-67 expression (p < 0.05). For PLWH, there was no correlation between ADC parameters and Ki-67 expression or clinical outcomes.

CONCLUSIONS

ADC histogram analysis can predict tumor proliferation and survival in immunocompetent patients with PCNSL, but with limited utility in PLWH.

Impact of atorvastatin loaded exosome as an anti-glioblastoma carrier to induce apoptosis of U87 cancer cells in 3D culture model

Exosomes (EXOs) are naturally occurring nanosized lipid bilayers that can be efficiently used as a drug delivery system to carry small pharmaceutical, biological molecules and pass major biological barriers such as the blood-brain barrier. It was hypothesized that EXOs derived from human endometrial stem cells (hEnSCs-EXOs) can be utilized as a drug carrier to enhance tumor-targeting drugs, especially for those have low solubility and limited oral bioactivity. In this study, atorvastatin (Ato) loaded EXOs (AtoEXOs) was prepared and characterized for its physical and biological activities in tumor growth suppression of 3 D glioblastoma model. The AtoEXOs were obtained in different methods to maximize drug encapsulation efficacy. The characterization of AtoEXOs was performed for its size, stability, drug release, and in vitro anti-tumor efficacy evaluated comprising inhibition of proliferation, apoptosis induction of tumor cells. Expression of apoptotic genes by Real time PCR, Annexin V/PI, tunnel assay was studied after 72 h exposing U87 cells where encapsulated in matrigel in different concentrations of AtoEXOs (5, 10 μM). The results showed that the prepared AtoEXOs possessed diameter ranging from 30-150 nm, satisfying stability and sustainable Ato release rate. The AtoEXOs was up taken by U87 and generated significant apoptotic effects while this inhibited tumor growth of U87 cells. Altogether, produced AtoEXOs formulation due to its therapeutic efficacy has the potential to be an adaptable approach to treat glioblastoma brain tumors.

ADC values of benign and high grade meningiomas and associations with tumor cellularity and proliferation - A systematic review and meta-analysis

INTRODUCTION

The aim of the present systematic review and meta-analysis was to compare the reported ADC values in different meningiomas and to analyze associations between ADC and cell count and proliferation activity in this tumor entity.

METHOD

MEDLINE library and SCOPUS database were screened for papers investigating ADC values of meningiomas up November 2019. The first primary endpoint of the systematic review was the reported ADC mean value of the meningioma groups. The second primary endpoint was the correlation coefficient between ADC values and proliferation index Ki 67 and cellularity.

RESULTS

For the discrimination analysis between benign and high grade meningioma 17 studies were suitable. There were 766 grade I tumors and 289 high grade meningiomas. The calculated mean ADC value of the benign grade I tumors was 0.93 × 10^-3mm²/s [95%-Confidence interval 0.84;1.03] and the mean value of the high-grade tumors was 0.77 × 10^-3mm²/s [95%-Confidence interval 0.73-0.80]. The pooled correlation coefficient between ADC and the proliferation index Ki 67 was r = -0.36 [95% CI -0.43; -0.28]. The pooled correlation coefficient between ADC and cellularity was r = -0.43 [95% CI -0.61; - 0.26].

CONCLUSION

No validated ADC threshold can be recommended for distinguishing benign from high grade meningiomas. Only a moderate inverse correlation was identified between ADC values and tumor microstructure in meningiomas and, therefore, ADC might not accurately enough to predict proliferation potential and cellularity in this entity.

Imaging and diagnostic advances for intracranial meningiomas

The archetypal imaging characteristics of meningiomas are among the most stereotypic of all central nervous system (CNS) tumors. In the era of plain film and ventriculography, imaging was only performed if a mass was suspected, and their results were more suggestive than definitive. Following more than a century of technological development, we can now rely on imaging to non-invasively diagnose meningioma with great confidence and precisely delineate the locations of these tumors relative to their surrounding structures to inform treatment planning. Asymptomatic meningiomas may be identified and their growth monitored over time; moreover, imaging routinely serves as an essential tool to survey tumor burden at various stages during the course of treatment, thereby providing guidance on their effectiveness or the need for further intervention. Modern radiological techniques are expanding the power of imaging from tumor detection and monitoring to include extraction of biologic information from advanced analysis of radiological parameters. These contemporary approaches have led to promising attempts to predict tumor grade and, in turn, contribute prognostic data. In this supplement article, we review important current and future aspects of imaging in the diagnosis and management of meningioma, including conventional and advanced imaging techniques using CT, MRI, and nuclear medicine.