Diagnostic Performance of Apparent Diffusion Coefficient for Prediction of Grading of Pancreatic Neuroendocrine Tumors: A Systematic Review and Meta-analysis

Diagnosing osteomyelitis in diabetic foot by diffusion-weighted imaging and dynamic contrast material-enhanced magnetic resonance imaging: a systematic review and meta-analysis

AIM

To evaluate the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE), for diagnosing osteomyelitis in the diabetic foot.

MATERIALS AND METHODS

A thorough search was carried out to identify suitable studies published up to September 2023. The quality of the studies involved was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The diagnostic sensitivity and specificity of each imaging modality/method for each specific cut point were summarized. The summary receiver operating characteristic (SROC) curve was calculated using bivariate mixed effects models.

RESULTS

Five studies investigating 187 patients and 234 bone lesions with 110 diagnosed osteomyelitis were enrolled. Four studies used DWI (172 lesions), three studies used DCE techniques (140 lesions) and two studies presented results of conventional MRI (66 lesions). The sensitivity ranges using conventional MRI, DWI and DCE were 65%-100%, 65%-100% and 64%-100%, respectively. The specificity ranges were 50%-61%, 56%-95%, and 66%-93%, respectively. The SROC curve of DWI and DCE was 0.89 (95% CI, 0.86-0.92) and 0.90 (95% CI, 0.87-0.92), respectively.

CONCLUSION

Combining DWI and DCE methods, alongside conventional MRI, can improve the reliability and accuracy of diabetic foot osteomyelitis diagnosis. However, the study recognizes result variability due to varying protocols and emphasizes the need for well-designed studies with standardized approaches. To optimize diagnostic performance, the study recommends considering low ADC values, Ktrans or rapid wash-in rate from DCE such as iAUC60, along with using large ROIs that cover the entire lesion while excluding normal bone marrow.

An Illustrated Review of the Recent 2019 World Health Organization Classification of Neuroendocrine Neoplasms: A Radiologic and Pathologic Correlation

ABSTRACT

Recent advances in molecular pathology and an improved understanding of the etiology of neuroendocrine neoplasms (NENs) have given rise to an updated World Health Organization classification. Since gastroenteropancreatic NENs (GEP-NENs) are the most common forms of NENs and their incidence has been increasing constantly, they will be the focus of our attention. Here, we review the findings at the foundation of the new classification system, discuss how it impacts imaging research and radiological practice, and illustrate typical and atypical imaging and pathological findings. Gastroenteropancreatic NENs have a highly variable clinical course, which existing classification schemes based on proliferation rate were unable to fully capture. While well- and poorly differentiated NENs both express neuroendocrine markers, they are fundamentally different diseases, which may show similar proliferation rates. Genetic alterations specific to well-differentiated neuroendocrine tumors graded 1 to 3 and poorly differentiated neuroendocrine cancers of small cell and large-cell subtype have been identified. The new tumor classification places new demands and creates opportunities for radiologists to continue providing the clinically most relevant report and on researchers to design projects, which continue to be clinically applicable.

Advancements in Neuroendocrine Neoplasms: Imaging and Future Frontiers

Neuroendocrine neoplasms (NENs) are a diverse group of tumors with varying clinical behaviors. Their incidence has risen due to increased awareness, improved diagnostics, and aging populations. The 2019 World Health Organization classification emphasizes integrating radiology and histopathology to characterize NENs and create personalized treatment plans. Imaging methods like CT, MRI, and PET/CT are crucial for detection, staging, treatment planning, and monitoring, but each of them poses different interpretative challenges and none are immune to pitfalls. Treatment options include surgery, targeted therapies, and chemotherapy, based on the tumor type, stage, and patient-specific factors. This review aims to provide insights into the latest developments and challenges in NEN imaging, diagnosis, and management.

Quantitative Magnetic Resonance Imaging for the Pancreas: Current Status

ABSTRACT

Magnetic resonance imaging (MRI) is important for evaluating pancreatic disorders, and anatomical landmarks play a major role in the interpretation of results. Quantitative MRI is an effective diagnostic modality for various pathologic conditions, as it allows the investigation of various physical parameters. Recent advancements in quantitative MRI techniques have significantly improved the accuracy of pancreatic MRI. Consequently, this method has become an essential tool for the diagnosis, treatment, and monitoring of pancreatic diseases. This comprehensive review article presents the currently available evidence on the clinical utility of quantitative MRI of the pancreas.

The assessment of pathological response to neoadjuvant chemotherapy in muscle-invasive bladder cancer patients with DCE-MRI and DWI: a systematic review and meta-analysis

OBJECTIVE

The purpose of this meta-analysis was to determine the value of dynamic contrast-enhanced-MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in evaluating the pathological response of muscle invasive bladder cancer (MIBC) to neoadjuvant chemotherapy (NAC), and further indirectly compare the diagnostic performance of DCE-MRI and DWI.

METHODS

Literatures associated to DCE-MRI and DWI in the evaluation of pathological response of MIBC to NAC were searched from PubMed, Cochrane Library, web of science, and EMBASE databases. The quality assessment of diagnostic accuracy studies 2 tool was used to assess the quality of studies. Pooled sensitivity (SE), specificity (SP), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the receiver operating characteristic curves (AUC) with their 95% confidence intervals (CIs) were calculated to evaluate the diagnostic performance of DCE-MRI and DWI in predicting the pathological response to NAC in patients with MIBC.

RESULTS

There were 11 studies involved, 6 of which only underwent DCE- MRI examination, 4 of which only underwent DWI examination, and 1 of which underwent both DCE- MRI and DWI examination. The pooled SE, SP, PLR, NLR, DOR of DCE-MRI were 0.88 (95% CI: 0.78-0.93), 0.88 (95% CI: 0.67-0.96), 7.4 (95% CI: 2.3-24.2), 0.14 (95% CI: 0.07-0.27), and 53 (95% CI: 10-288), respectively. The pooled SE, SP, PLR, NLR, DOR of DWI were 0.83 (95% CI: 0.75-0.88), 0.88 (95% CI: 0.81-0.93), 7.1 (95% CI: 4.3-11.7), 0.20 (95% CI: 0.14-0.28), and 36 (95% CI:18-73), respectively. The AUCs of SROC curve for DCE-MRI and DWI were 0.93 (95% CI: 0.91-0.95) and 0.92 (95% CI: 0.89-0.94), respectively. There were no significant differences between DWI and DCE-MRI for SE, SP, and AUC.

CONCLUSION

This meta-analysis demonstrated high diagnostic performance of both DCE-MRI and DWI in predicting the pathological response to NAC in MIBC. DWI might be a potential substitute for DCE-MRI, with no significant difference in diagnostic performance between the two. However, caution should be taken when applying our results, as our results were based on indirect comparison.

ADVANCES IN KNOWLEDGE

No previous studies have comprehensively analysed the value of DCE-MRI and DWI in evaluating the pathological response to NAC in MIBC. According to the current study, both DCE-MRI and DWI yielded high diagnostic performance, with the AUCs of 0.93 and 0.92, respectively. Indirect comparison no significant difference in the diagnostic performanceof DCE-MRI and DWI.

The Diagnostic and Grading Accuracy of 68Ga-DOTATATE and 18F-FDG PET/MR for Pancreatic Neuroendocrine Neoplasms

Accurate diagnosis and grading are critical for pancreatic neuroendocrine neoplasm (pNEN) management. This study compares the diagnostic and grading value of ⁶⁸Ga-DOTATATE PET/MR and ¹⁸F-FDG PET/MR for pNENs separately as well as in combination. A total of 36 patients with histologically confirmed pNENs, who underwent both ⁶⁸Ga-DOTATATE PET/MR and ¹⁸F-FDG PET/MR within 2 weeks from 2020 to 2021, were retrospectively collected and analyzed. The maximum standardized uptake values of ⁶⁸Ga-DOTATATE (G-SUVmax) and ¹⁸F-FDG (F-SUVmax) on PET and the minimum values of apparent diffusion coefficient (ADCmin) on MR were measured on the lesions with known histological grading (25 by surgery, 11 by biopsy). Receiver-operating characteristic analysis was applied to determine the cutoffs of these parameters or their combinations for differentiation between G1 and G2, as well as between low-grade and high-grade pNENs. The Spearman rank correlation coefficient was used to assess the correlation between the imaging parameters and the maximum tumor diameters. The detection rate of ⁶⁸Ga-DOTATATE PET imaging alone was 95%, 87.5%, and 37.5% for G1, G2, and G3, respectively. Adding ¹⁸F-FDG PET or MR sequences of PET/MR increased the detection rate to 100% in all grades. Among the three parameters, G-SUVmax had the highest diagnostic rate in predicting tumor grade. It presented a sensitivity of 87.5% and a specificity of 80.0% with a cutoff value of 42.75 for differentiating G2 from G1 pNETs and a sensitivity and specificity of 100% and 71.4% with a cutoff value of 32.75 in predicting high-grade pNENs. The ratio of G-SUVmax to F-SUVmax (G-SUVmax/F-SUVmax) showed slight improvement in the diagnostic rate, while the product of G-SUVmax and ADCmin (G-SUVmax*ADCmin) did not improve the diagnostic rate. ⁶⁸Ga-DOTATATE PET/MR alone is sufficient for the diagnosis of pNENs and the prediction of various grades.

Diagnostic Performance of Diffusion MRI for differentiating Benign and Malignant Nonfatty Musculoskeletal Soft Tissue Tumors: A Systematic Review and Meta-analysis

Objective: To evaluate the diagnostic performance of standard diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for differentiating benign and malignant soft tissue tumors (STTs).

Materials and methods: A thorough search was carried out to identify suitable studies published up to September 2020. The quality of the studies involved was evaluated using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled sensitivity (SEN), specificity (SPE), and summary receiver operating characteristic (SROC) curve were calculated using bivariate mixed effects models. A subgroup analysis was also performed to explore the heterogeneity.

Results: Eighteen studies investigating 1319 patients with musculoskeletal STTs (malignant, n=623; benign, n=696) were enrolled. Thirteen standard DWI studies using the apparent diffusion coefficient (ADC) showed that the pooled SEN and SPE of ADC were 0.80 (95% CI: 0.77-0.82) and 0.63 (95% CI: 0.60-0.67), respectively. The area under the curve (AUC) calculated from the SROC curve was 0.806. The subgroup analysis indicated that the percentage of myxoid malignant tumors, magnet strength, study design, and ROI placement were significant factors affecting heterogeneity. Four IVIM studies showed that the AUCs calculated from the SROC curves of the parameters ADC and D were 0.859 and 0.874, respectively. The AUCs for the IVIM parameters pseudo diffusion coefficient (D*) and perfusion fraction (f) calculated from the SROC curve were 0.736 and 0.573, respectively. Two DKI studies showed that the AUCs of the DKI parameter mean kurtosis (MK) were 0.97 and 0.89, respectively.

Conclusion: The DWI-derived ADC value and the IVIM DWI-derived D value might be accurate tools for discriminating musculoskeletal STTs, especially for non-myxoid SSTs, using more than two b values, with maximal b value ranging from 600 to 800 s/mm², additionally, a high-field strength (3.0 T) optimizes the diagnostic performance.

Noise reduction in diffusion weighted MRI of the pancreas using an L1-regularized iterative SENSE reconstruction

OBJECTIVES

To prospectively evaluate an L1 regularized iterative SENSE reconstruction (L1-R SENSE) to eliminate band-like artifacts frequently seen with parallel imaging (SENSE) at high acceleration factors in high resolution diffusion weighted magnetic resonance imaging of the pancreas.

METHODS

Fourteen patients with pancreatic ductal adenocarcinoma (PDAC) underwent respiratory triggered DWI ss-EPI at a resolution of 2.5 × 2.5 × 3 mm3 with uniform undersampling in the phase encoding direction (AP axis) with an acceleration factor of 4. Data were reconstructed using the standard SENSE reconstruction routine of the vendor and an iterative SENSE reconstruction employing L1 regularization after a wavelet sparsifying transformation (L1-R SENSE). Retrospective reconstruction of the data with a lower number of averages was performed using both reconstruction methods. Two radiologists independently assessed noise artifacts, anatomical details and image quality (IQ) subjectively with a 4-point scale. Apparent diffusion coefficient (ADC) and covariance (CV) of ADC estimated from images reconstructed at a different number of averages for PDAC and the normal pancreas were assessed.

RESULTS

L1-R SENSE resulted in higher IQ and less noise artifacts than SENSE. Anatomical details were significantly higher for SENSE in one reader. Mean ADC of PDAC and normal pancreas were significantly higher for L1-R SENSE than SENSE. L1-R SENSE revealed lower CV of ADC for normal pancreas compared to SENSE, whereas no difference was noted for PDAC.

CONCLUSION

Compared with traditional SENSE reconstruction, L1-R SENSE effectively reduces band-like noise and improves the robustness of the ADC estimation from acquisitions using single-shot DW-EPI of the pancreas.

Imaging of Pancreatic Neuroendocrine Neoplasms

Pancreatic neuroendocrine neoplasms (panNENs) represent the second most common pancreatic tumors. They are a heterogeneous group of neoplasms with varying clinical expression and biological behavior, from indolent to aggressive ones. PanNENs can be functioning or non-functioning in accordance with their ability or not to produce metabolically active hormones. They are histopathologically classified according to the 2017 World Health Organization (WHO) classification system. Although the final diagnosis of neuroendocrine tumor relies on histologic examination of biopsy or surgical specimens, both morphologic and functional imaging are crucial for patient care. Morphologic imaging with ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) is used for initial evaluation and staging of disease, as well as surveillance and therapy monitoring. Functional imaging techniques with somatostatin receptor scintigraphy (SRS) and positron emission tomography (PET) are used for functional and metabolic assessment that is helpful for therapy management and post-therapeutic re-staging. This article reviews the morphological and functional imaging modalities now available and the imaging features of panNENs. Finally, future imaging challenges, such as radiomics analysis, are illustrated.

Optimal target b-value on computed diffusion-weighted magnetic resonance imaging for visualization of pancreatic ductal adenocarcinoma and focal autoimmune pancreatitis

PURPOSE

To compare computed diffusion-weighted imaging (cDWI) feasibility with that of directly acquired DWI for visualizing pancreatic ductal adenocarcinoma (PDAC) and focal autoimmune pancreatitis (AIP).

METHODS

From April 2012 to January 2017, 135 patients with PDAC (n = 111) or focal AIP (n = 24) were retrospectively enrolled. They underwent DWI with b-values of 0, 500, and 1000 s/mm². From DWI₀ and DWI₁₀₀₀, we generated cDWIs with targeted b-values of 1500, 2000, and 3000 s/mm². The lesions' signal intensities, image quality, signal intensity ratio (SIR) of lesions and pancreatic parenchyma to spinal cord, and lesion-to-pancreatic parenchyma contrast ratio (CR) were compared among the five DWI protocols (DWI₅₀₀, DWI₁₀₀₀, cDWI₁₅₀₀, cDWI₂₀₀₀, and cDWI₃₀₀₀). SIR was analyzed by receiver operating characteristic (ROC) analyses.

RESULTS

DWI₅₀₀, DWI₁₀₀₀, and cDWI₁₅₀₀ had higher image quality than cDWI₂₀₀₀ and cDWI₃₀₀₀ (P < 0.001). The incidence of clear hyperintense PDAC was highest on cDWI₂₀₀₀, followed by cDWI₁₅₀₀, and cDWI₃₀₀₀ (P < 0.001-0.002), while the incidence of clear hyperintense AIP was higher on DWI₁₀₀₀, cDWI₁₅₀₀, and cDWI₂₀₀₀ than on DWI₅₀₀ and cDWI₃₀₀₀ (P = 0.001-0.022). SIRs decreased whereas CRs increased as the b-value increased, for both PDAC and AIP. The area under the ROC curve (AUC) of SIR_lesion was significantly lower on cDWI₁₅₀₀ than on cDWI₂₀₀₀ and cDWI₃₀₀₀ (P < 0.001).

CONCLUSION

cDWI₁₅₀₀ or cDWI₂₀₀₀ generated from b-values of 0 and 1000 s/mm² were the most effective for visualizing PDAC and focal AIP; however, the SIR_lesion AUC was significantly lower on cDWI₁₅₀₀ than on cDWI₂₀₀₀ and cDWI₃₀₀₀.

Diffusion-Weighted MRI Predicts Lymph Node Metastasis and Tumor Aggressiveness in Resectable Pancreatic Neuroendocrine Tumors

OBJECTIVES

The aim of this study was to identify whether diffusion-weighted magnetic resonance imaging (DW-MRI) can predict the malignant behavior of preoperative well-differentiated pancreatic neuroendocrine tumors (PanNETs).

METHOD

Forty patients with PanNETs who underwent pancreatectomy were enrolled in this study. The apparent diffusion coefficient (ADC) values were measured. Clinicopathological factors were compared in patients with high ADC and low ADC values and in patients with and without lymph node metastasis (LNM).

RESULT

The low ADC group was significantly associated with higher Ki-67 index, higher mitotic count, larger tumor size, higher rate of LNM, and venous invasion. In patients with low ADC values, the incidence of LNMs was 33.3%. In patients with high ADC values, there were no patients with LNM being 0%. A significant negative correlation was found between the mean ADC values and the Ki-67 index and between the mean ADC values and the mitotic count. In multivariate analysis, neural invasion and mean ADC values ≤ 1458 were independent predictors of LNM.

CONCLUSION

ADC values obtained using DW-MRI in the preoperative assessment of patients with PanNETs might be a useful predictor of malignant potential, especially LNM.

Diffusion-Weighted Imaging in Oncology: An Update

To date, diffusion weighted imaging (DWI) is included in routine magnetic resonance imaging (MRI) protocols for several cancers. The real additive role of DWI lies in the "functional" information obtained by probing the free diffusivity of water molecules into intra and inter-cellular spaces that in tumors mainly depend on cellularity. Although DWI has not gained much space in some oncologic scenarios, this non-invasive tool is routinely used in clinical practice and still remains a hot research topic: it has been tested in almost all cancers to differentiate malignant from benign lesions, to distinguish different malignant histotypes or tumor grades, to predict and/or assess treatment responses, and to identify residual or recurrent tumors in follow-up examinations. In this review, we provide an up-to-date overview on the application of DWI in oncology.

Correlation Between Apparent Diffusion Coefficient Value on MRI and Histopathologic WHO Grades of Neuroendocrine Tumors

Background

The correlation of diffusion-weighted MRI and tumor aggressiveness has been established for different tumor types, which leads to the question if it could also apply for neuroendocrine tumors (NET).

Purpose

To investigate the possible correlation between apparent diffusion coefficient (ADC) value on magnetic resonance imaging (MRI) and histopathologic WHO-grades of NET.

Material and Methods

Electronic patient records from patients presented at the multidisciplinary neuro-endocrine tumor board between November 2017 and April 2019 were retrospectively reviewed. Patients with both available MR imaging (primary tumor or metastasis) and known WHO tumor grade were included (n = 47). Average and minimum ADC values (avgADC; minADC) were measured by drawing a freehand ROI excluding only the outermost border of the lesion. The largest axial size (primary tumor) or most clearly delineated lesion (metastasis) was used.

Results

Forty seven patients met the inclusion criteria (mean age 59 ± 12 SD; 24F/23M). Twenty one patients (45%) were diagnosed with WHO G1 tumor, 17 seventeen with G2 (36%) and nine with G3 (19%) tumor. Twenty eight primary tumors and 19 metastases were measured. A significant difference was found between low-grade (G1+G2) and high-grade (G3) tumors (Mann-Whitney; avgADC: p < 0,001; minADC: p = 0,001). There was a moderate negative correlation between WHO-grade and avgADC/minADC (Spearman; avgADC: -0,606; 95% CI [-0,773; -0,384]; minADC: -0,581; 95% CI [-0.759; -0.353]).

Conclusion

Our data show a significant difference in both average and minimum ADC values on MRI between low and high grade NET. A moderate negative correlation was found between histopathologic WHO grade and ADC value.