Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance

[Purpose]Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson’s disease (PD) by showing reduced signals in the substantia nigra (SN) and locus coeruleus (LC), but requires a long scan time. The aim of this study was to assess the image quality and diagnostic performance of NM-MRI with a shortened scan time using a denoising approach with deep learning-based reconstruction (dDLR).[Materials and methods]We enrolled 22 healthy volunteers, 22 non-PD patients and 22 patients with PD who underwentNM-MRI, and performed manual ROI-based analysis. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in ten healthy volunteers were compared among images with a number of excitations (NEX) of 1 (NEX1), NEX1 images with dDLR (NEX1+dDLR) and 5-NEX images (NEX5). Acquisition times for NEX1 and NEX5 were 3 min 12 s and 15 min 58 s, respectively. Diagnostic performances using the contrast ratio (CR) of the SN (CR_SN) and LC (CR_LC) and those by visual assessment for diferentiating PD from non-PD were also compared between NEX1 and NEX1+dDLR.[Results]Image quality analyses revealed that SNRs and CNRs of the SN and LC in NEX1+dDLR were signifcantly higherthan in NEX1, and comparable to those in NEX5. In diagnostic performance analysis, areas under the receiver operating characteristic curve (AUC) using CR_SN and CR_LC of NEX1+dDLR were 0.87 and 0.75, respectively, which had no signifcant diference with those of NEX1. Visual assessment showed improvement of diagnostic performance by applying dDLR.[Conclusion]Image quality for NEX1+dDLR was comparable to that of NEX5. dDLR has the potential to reduce scan time of NM-MRI without degrading image quality. Both 1-NEX NM-MRI with and without dDLR showed high AUCs for diagnosing PD by CR. The results of visual assessment suggest advantages of dDLR. Further tuning of dDLR would be expected to provide clinical merits in diagnosing PD

Subcategory classifications of Breast Imaging and Data System (BI-RADS) category 4 lesions on MRI

[Purpose]Category 4 in BI-RADS for magnetic resonance imaging (MRI) has a wide range of probabilities of malignancy, extending from > 2 to  0%,  ≤ 2%), 4 (> 2%,   2%,  ≤ 10%), 4B (> 10%,  ≤ 50%) and 4C (> 50%,  < 95%) at the time of diagnosis. Radiological and pathological reports were retrospectively analyzed, and the PPVs were calculated. [Results] We included 149 malignant and 285 benign lesions. The PPVs of subcategories 4A, 4B and 4C were 1.8%, 11.8% and 67.5%, respectively. The PPVs were higher for lesions coexisting with category 5 or 6 lesions compared with those for isolated lesions. [Conclusion] Category 4 lesions can be classified into three subcategories depending on the likelihood of malignancy. Lesions coexisting with category 5 or 6 lesions are more likely to be malignant

Evaluation of Malignant Breast Lesions Using High-resolution Readout-segmented Diffusion-weighted Echo-planar Imaging: Comparison with Pathology

PURPOSE: We aimed to investigate the performance of high resolution-diffusion-weighted imaging (HR-DWI) using readout-segmented echo-planar imaging in visualizing malignant breast lesions and evaluating their extent, using pathology as a reference. METHODS: This retrospective study included patients who underwent HR-DWI with surgically confirmed malignant breast lesions. Two radiologists blinded to the final diagnosis evaluated HR-DWI independently and identified the lesions, measuring their maximum diameters. Another radiologist confirmed if those lesions were identical to the pathology. The maximum diameters of the lesions between HR-DWI and pathology were compared, and their correlations were calculated using Spearman's correlation coefficient. Apparent diffusion coefficient (ADC) values of the lesions were measured. RESULTS: Ninety-five mass/64 non-mass lesions were pathologically confirmed in 104 females. Both radiologists detected the same 93 mass lesions (97.9%). Spearman's correlation coefficient for mass lesions were 0.89 and 0.90 (P < 0.0001 and 0001) for the two radiologists, respectively. The size differences within 10 mm were 90.3% (84/93) and 94.6% (88/93) respectively. One radiologist detected 35 non-mass lesions (54.7%) and another radiologist detected 32 non-mass lesions (50.0%), of which 28 lesions were confirmed as identical. Spearman's correlation coefficient for non-mass lesions were 0.59 and 0.22 (P = 0.0002 and 0.22), respectively. The mean ADC value of mass lesions and non-mass lesions were 0.80 and 0.89 × 10-3 mm2/s, respectively. CONCLUSION: Using HR-DWI, malignant mass lesions were depicted with excellent agreement with the pathological evaluation. Approximately half of the non-mass lesions could not be identified, suggesting a current limitation of HR-DWI

Application of a Flexible PET Scanner Combined with 3 T MRI Using Non-local Means Reconstruction: Qualitative and Quantitative Comparison with Whole-Body PET/CT

[Purpose] Flexible positron emission tomography (fxPET) employing a non-local means reconstruction algorithm was designed to fit existing magnetic resonance imaging (MRI) systems. We aimed to compare the qualitative and quantitative performance of fxPET among fxPET with MR-based attenuation correction (MRAC), fxPET with CT-based attenuation correction (CTAC) using CT as a part of WB PET/CT, and whole-body (WB) PET/CT. [Procedures] Sixteen patients with suspected head and neck cancer underwent 2-deoxy-2-[18F]fluoro-D-glucose WB PET/CT scans, followed by fxPET and 3 T MRI scans. Phantom data were compared among the three datasets. For registration accuracy, we measured the distance between the center of the tumor determined by fxPET and that in MRI. We compared image quality, detection rates, and quantitative values including maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and tumor-to-muscle ratio (TMR) among the three datasets. [Results] The phantom data in fxPET, except the percent contrast recoveries of 17-mm and 22-mm hot spheres, were inferior to those in WB PET/CT. The mean registration accuracy was 4.4 mm between fxPET using MRAC and MRI. The image quality was comparable between two fxPET datasets, but significantly inferior to WB PET/CT (p < 0.0001). In contrast, detection rates were comparable among the three datasets. SUVmax was significantly higher, and MTV and TLG were significantly lower in the two fxPET datasets compared with the WB PET/CT dataset (p < 0.005). There were no significant differences in SUVmax, MTV, and TLG between the two fxPET datasets or in TMR among the three datasets. All quantitative values had significantly positive correlations. [Conclusions] Compared with WB PET/CT, the phantom data and image quality were inferior in fxPET. However, the results of the detection rates and quantitative values suggested the clinical feasibility of fxPET

The predictive value of preoperative (18)F-fluorodeoxyglucose PET for postoperative recurrence in patients with localized primary gastrointestinal stromal tumour.

To assess the potential value of preoperative (18)F-FDG PET to predict postoperative recurrence of solitary localized primary gastrointestinal stromal tumour (GIST) after radical resection

Visual Evaluation of Ultrafast MRI in the Assessment of Residual Breast Cancer after Neoadjuvant Systemic Therapy : A Preliminary Study Association with Subtype

The purpose of this study was to investigate the diagnostic performance of ultrafast DCE (UF-DCE) MRI after the completion of neoadjuvant systemic therapy (NST) in breast cancer. In this study, MR examinations of 55 post-NST breast cancers were retrospectively analyzed. Residual tumor sizes were measured in the 20th phase of UF-DCE MRI, early and delayed phases of conventional DCE MRI, and high spatial-resolution CE MRI (UF, early, delayed, and HR, respectively). The diagnostic performance for the detection of residual invasive cancer was calculated by ROC analysis. The size difference between MRI and pathological findings was analyzed using the Wilcoxon signed-rank test with the Bonferroni correction. The overall AUC was highest for UF (0.86 and 0.88 for readers 1 and 2, respectively). The difference in imaging and pathological sizes for UF (5.7 ± 8.2 mm) was significantly smaller than those for early, delayed, and HR (p < 0.01). For luminal subtype breast cancer, the size difference was significantly smaller for UF and early than for delayed (p < 0.01). UF-DCE MRI demonstrated higher AUC and specificity for the more accurate detection of residual cancer and the visualization of tumor extent than conventional DCE MRI

Thin-slice reverse encoding distortion correction DWI facilitates visualization of non-functioning pituitary neuroendocrine tumor (PitNET)/pituitary adenoma and surrounding normal structures

Abstract Background To evaluate the clinical usefulness of thin-slice echo-planar imaging (EPI)-based diffusion-weighted imaging (DWI) with an on-console distortion correction technique, termed reverse encoding distortion correction DWI (RDC-DWI), in patients with non-functioning pituitary neuroendocrine tumor (PitNET)/pituitary adenoma. Methods Patients with non-functioning PitNET/pituitary adenoma who underwent 3-T RDC-DWI between December 2021 and September 2022 were retrospectively enrolled. Image quality was compared among RDC-DWI, DWI with correction for distortion induced by B 0 inhomogeneity alone (B0-corrected-DWI), and original EPI-based DWI with anterior-posterior phase-encoding direction (AP-DWI). Susceptibility artifact, anatomical visualization of cranial nerves, overall tumor visualization, and visualization of cavernous sinus invasion were assessed qualitatively. Quantitative assessment of geometric distortion was performed by evaluation of anterior and posterior displacement between each DWI and the corresponding three-dimensional T2-weighted imaging. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient values were measured. Results Sixty-four patients (age 70.8 ± 9.9 years [mean ± standard deviation]; 33 females) with non-functioning PitNET/pituitary adenoma were evaluated. In terms of susceptibility artifacts in the frontal and temporal lobes, visualization of left trigeminal nerve, overall tumor visualization, and anterior displacement, RDC-DWI performed the best and B0-corrected-DWI performed better than AP-DWI. The right oculomotor and right trigeminal nerves were better visualized by RDC-DWI than by B0-corrected-DWI and AP-DWI. Visualization of cavernous sinus invasion and posterior displacement were better by RDC-DWI and B0-corrected-DWI than by AP-DWI. SNR and CNR were the highest for RDC-DWI. Conclusions RDC-DWI achieved excellent image quality regarding susceptibility artifact, geometric distortion, and tumor visualization in patients with non-functioning PitNET/pituitary adenoma. Relevance statement RDC-DWI facilitates excellent visualization of the pituitary region and surrounding normal structures, and its on-console distortion correction technique is convenient. RDC-DWI can clearly depict cavernous sinus invasion of PitNET/pituitary adenoma even without contrast medium. Key points • RDC-DWI is an EPI-based DWI technique with a novel on-console distortion correction technique. • RDC-DWI corrects distortion due to B 0 field inhomogeneity and eddy current. • We evaluated the usefulness of thin-slice RDC-DWI in non-functioning PitNET/pituitary adenoma. • RDC-DWI exhibited excellent visualization in the pituitary region and surrounding structures. • In addition, the on-console distortion correction of RDC-DWI is clinically convenient. Graphical Abstrac

Personalized Pathway-Activated Systems lmaging in Oncology(PET Radiotracers for Tumor Imaging)

intro PET Radiotracers for Tumor Imaging(Ming-Rong Zhang