Impact Of Magnetic Resonance Imaging Research Articles

Abstract PO3-27-03: PROMISE Study: Pre-Operatory MRI is not Effective. A Systematic review of impact of magnetic resonance imaging on surgery-decision and clinical outcomes in women with breast cancer

Abstract Background: The use of magnetic resonance imaging (MRI) in patients with breast cancer before surgery has been a subject of ongoing debate and discussion. The role of MRI as a preoperative tool to guide surgical decision-making remains controversial. Some studies suggest that MRI may improve the detection of additional tumors or assess the extent of disease, while others discuss that it may lead to increased false-positive findings and unnecessary interventions. The potential benefits and potential harms of incorporating MRI into the preoperative assessment of breast cancer patients continue to be topics of research and clinical interest. Clarifying the impact of preoperative MRI on surgical outcomes is crucial to inform evidence-based practices and optimize patient care. Until present, there is no pooled analyses from randomized clinical trials perspective of the clinical impact regarding the routine use of MRI. Objectives: This study aims to conduct metanalysis of randomized controlled trials (RCT) to investigate the association between preoperative MRI and surgical outcomes in women with newly diagnosed invasive breast cancer, providing evidence-based recommendations for clinical practice. Methods: A comprehensive search of electronic databases including PubMed, Medline, Embase, Ovid, Cochrane Library, and Web of Science was conducted by three independent researchers from inception to May 2023. The inclusion and exclusion criteria were based on Cochrane's principles. Relevant data from eligible studies were extracted. A systematic evaluation and meta-analysis were performed using the fixed-effects model to estimate the pooled risk ratio (RR) and 95% CI. Results: Out of 21 studies found, 6 were RCTs and 15 observational comparative studies. The results showed that in RCT preoperative MRI significantly reduce the rate of immediate breast conservative surgery (RR=0.94, 95%CI 0.91~0.96, I2=0%) and increase the mastectomy rate (RR=1.88, 95%CI 1.48~2.38, I2=86%). There wasn’t any change in reoperations rates (RR=0,87, 95%CI 0.71~1.07, I2=72%). Only 1 trial reported data on survival, showing no difference between groups. Conclusion: From RCT standpoint, the evidence suggests that preoperative MRI for newly diagnosed invasive breast cancer may not be beneficial to the patients by increasing rate of mastectomy with no survival benefit and that should be considered when offering as a routine practice to patients with breast cancer before surgery. Forest plot of mastectomy as an outcome Forest plot of re-operation as an outcome Citation Format: Andre Mattar, Andressa Amorim, Evandro Mateus, Fabio Bagnoli, Felipe Zerwes, Francisco Pimentel Cavalcante, Guilherme Novita, Lincon Mori, Marcelo Madeira, Marina Diogenes, Marcelo Antonini, Lucas Okumura. PROMISE Study: Pre-Operatory MRI is not Effective. A Systematic review of impact of magnetic resonance imaging on surgery-decision and clinical outcomes in women with breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-27-03.

Traumatic thoracic spine fracture: can we predict when MRI would modify the fracture classification or decision-making compared to CT alone?

To determine the impact of magnetic resonance imaging (MRI) on fracture classification for thoracic spine fractures (TSFs) compared to computed tomography (CT) alone. This study was a retrospective review of 63 consecutive patients with TSFs who underwent CT and MRI within ten days of injury. Three reviewers classified all fractures according to the AOSpine Classification and the ThoracolumbarAOSpineInjury severity score (TLAOSIS). Posterior ligamentous complex (PLC) injury on MRI was defined by "black stripe discontinuity" and on CT by the presence of vertebral body translation, facet joint malalignment, horizontal laminar or spinous process fracture, and interspinous widening. The proportion of patients with AO type A/B/C and with TLAOSIS ≤ 5 and ≥ 6 was compared between CT and MRI. Classification and regression trees were used to create a series of predictive models for the probability of PLC injury in AO type A fractures. AO classification using CT was as follows: type A in 35 patients (55%), type B in 18 patients (29%), and type C in 10 patients (16%). Thirty-threepatients (52%) had a TLAOSIS ≤5, while the remaining 30 (48%) had TLAOSI ≥6. The addition of MRI after CT upgraded type A to type Bfractures in 10 patients (16%) and changed TL AOSIS from ≤5 to ≥6 in8 cases (12.8%). Type A fractures with load sharing score (LSC) ≥6 had a 60% chance of upgrading to type B, while LSC <6 had a 12.5% chance of upgrading to type B. CT yielded (89%) accuracyin diagnosing PLC injury in TSFs. The addition of MRI after CTsubstantially changed the AO classification or TLAOISS, compared to CT alone, thus suggesting an added value of MRI for PLC assessment for TSFs classification.

Magnetic Resonance Imaging (MRI) Insights into Brain Morphology and Connectivity Disruptions in Schizophrenia

This review explores the transformative impact of Magnetic Resonance Imaging (MRI) on understanding schizophrenia. Structural MRI has unveiled significant alterations in brain regions like the hippocampus and prefrontal cortex, offering detailed insights into anatomical irregularities. Functional MRI studies have shed light on disruptions within the default mode network, providing valuable insights into cognitive deficits associated with the disorder. Additionally, Diffusion Tensor Imaging has highlighted white matter abnormalities, underscoring compromised interregional communication within the brain. Despite persistent challenges such as population heterogeneity and variations in imaging protocols, MRI techniques have significantly advanced our understanding of schizophrenia's neurobiological aspects.

How frequently MRI modifies thoracolumbar fractures' classification or decision-making? A systematic review and meta-analysis.

To provide the first meta-analysis of the impact of magnetic resonance imaging (MRI) on thoracolumbar fractures (TLFs) classification and decision-making. A systematic review was conducted following PRISMA guidelines. We searched PubMed, Scopus, Cochrane, and Web of Science from inception to June 30, 2023 for studies evaluating the change in TLFs classification and treatment decisions after MRI. The studies extracted key findings, objectives, and patient population. A meta-analysis was performed for the pooled frequency of change in AO fracture classification or treatment decisions from surgical to conservative or vice versa after MRI. This meta-analysis included four studies comprising 554 patients. The pooled frequency of change in TLFs classification was 17% (95% CI 9-31%), and treatment decision was 22% (95% CI 11-40%). An upgrade from type A to type B was reported in 15.7% (95% CI 7.2-30.6%), and downgrading type B to type A in 1.2% (95% CI 0.17-8.3%). A change from conservative to surgery recommendation of 17% (95% CI 5.0-43%) was higher than a change from surgery to conservative 2% (95% CI 1-34%). MRI can significantly change the thoracolumbar classification and decision-making, primarily due to upgrading type A to type B fractures and changing from conservative to surgery, respectively. These findings suggest that MRI could change decision-making sufficiently to justify its use for TLFs. Type A subtypes, indeterminate PLC status, and spine regions might help to predict a change in TLFs' classification. However, more studies are needed to confirm the association of these variables with changes in treatment decisions to set the indications of MRI in neurologically intact patients with TLFs. An interactive version of our analysis can be accessed from here: https://databoard.shinyapps.io/mri_spine/ .

MRI-guided Real-time Online Gated Stereotactic Body Radiation Therapy for Liver Tumors.

Liver tumors are commonly encountered in oncology. The study aimed to assess the impact of magnetic resonance imaging (MRI)-guided stereotactic body radiation therapy (SBRT) (MRgSBRT) on disease-related outcomes and the toxicity profile. Patients who received MRgSBRT from 2019 to 2021 for primary and metastatic liver tumors were included in this analysis. The protocol for treatment simulation included Gadoxetate disodium injection followed by a single-dimensional post-exhale MRI (0.35-T MRI linear accelerator) and computed tomography simulation. The patient demographics and treatment-related outcomes were assessed. The time-to-event curves were analyzed for freedom from local progression (FFLP) and overall survival (OS). A total of 35 patients were eligible for analysis with a median age of 70 years (range 25 to 95). The median follow-up was 19.4 months (range 1 to 37mo). The one-year OS was 77.7%, with an estimated 3 years of 47.9%. Patients with the locally controlled disease had a better median OS of 27.8 months (95% CI [23.8-31.6]) compared with 13.5 months (95% CI [5.6-21.3], P =0.007) in patients with local disease progression. The 1-year FFLP was 95.6%, and 3-year estimated FFLP was 87.1%. Patients who received a radiation dose of biologically equivalent dose≥100 Gy had FFLP of 30.9 months (95% CI [28.7-33.1]) compared with 13.3 months (95% CI [5.3-21.3], P =0.004) in patients who received <100 Gy biologically equivalent dose. MRI-guided SBRT provides optimal local control, associated with improved OS in a heavily morbid, pretreated older cohort of patients with reasonable safety profiles.

Environmental Sustainability and MRI: Challenges, Opportunities, and a Call for Action.

The environmental impact of magnetic resonance imaging (MRI) has recently come into focus. This includes its enormous demand for electricity compared to other imaging modalities and contamination of water bodies with anthropogenic gadolinium related to contrast administration. Given the pressing threat of climate change, addressing these challenges to improve the environmental sustainability of MRI is imperative. The purpose of this review is to discuss the challenges, opportunities, and the need for action to reduce the environmental impact of MRI and prepare for the effects of climate change. The approaches outlined are categorized as strategies to reduce greenhouse gas (GHG) emissions from MRI during production and use phases, approaches to reduce the environmental impact of MRI including the preservation of finite resources, and development of adaption plans to prepare for the impact of climate change. Co-benefits of these strategies are emphasized including lower GHG emission and reduced cost along with improved heath and patient satisfaction. Although MRI is energy-intensive, there are many steps that can be taken now to improve the environmental sustainability of MRI and prepare for the effects of climate change. On-going research, technical development, and collaboration with industry partners are needed to achieve further reductions in MRI-related GHG emissions and to decrease the reliance on finite resources. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.

Impact of Magnetic Resonance Imaging on Healthcare in Low- and Middle-Income Countries.

Magnetic resonance imaging (MRI) played a significant role in the digital health platforms that influenced and supported modern medicine. However, there is a shortage of MRI in low- and middle-income countries (LMICs). The International Society of Radiology offers a detailed plan for LMICs to advance imaging quality in the global health agenda. The overarching objective of this scoping review was to determine the impact of MRI in healthcare in LMICs. This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify available evidence. We systematically searched four academic databases for peer-reviewed literature published between 2018 and 2021, namely, Medline, PubMed, Web of Science, and Scopus, as well as Google Scholar as a source for gray literature. The search identified 54 articles. We identified a range of reasons for introducing MRI in LMICs. Nonetheless, some challenges to accepting MRI as a method of healthcare have been reported, including technological, regulatory, and economical challenges.To implement the proposed plan, the involvement of professional and international organizations is considered crucial. The establishment of an International Commission on Medical Imaging under the umbrella of international organizations is suggested and collaboration with other diagnostic disciplines is encouraged to raise awareness of the importance of upscale diagnostics at large and to foster its integration into the care pathway globally.

Impact of magnetic resonance imaging on prosthodontic materials.

Impact of magnetic resonance imaging on prosthodontic materials.

Applications of Magneto Electrochemistry and Magnetohydrodynamics in Microfluidics

Magnetic fields affect electrolytes in diverse ways. This paper focuses on the interactions among electric, magnetic, and flow fields and the applications of the resulting phenomena in microfluidics. When an electrical current is transmitted in an electrolyte in the presence of an external magnetic field, a Lorentz body force results, which may induce pressure gradients and fluid motion—magnetohydrodynamics (MHD). The resulting advection is used to pump fluids, induce/suppress flow instabilities, and control mass transfer in diverse electrochemical processes. When an electrolyte flows in the presence of a magnetic field, electromotive force (emf) is induced in the electrolyte and can be used for flow metering, hydrogen production, and energy conversion. This review describes the governing equations for modeling MHD flows in electrolytes and MHD phenomena and applications relevant to microfluidic systems, such as the use of MHD to pump and stir fluids, propel swimmers, and control fluid flow in fluidic networks without any mechanical components. The paper also briefly assesses the impact of magnetic resonance imaging (MRI) on blood flow. MHD in electrolytes is a highly interdisciplinary, combining electrokinetics, fluid mechanics, electrochemistry, and Maxwell equations.

119P Impact of magnetic resonance imaging in the surgical treatment of early breast cancer in two private cancer care centers in Lima, Peru

The impact of preoperative magnetic resonance imaging (MRI) in newly diagnosed breast cancer patients is matter of debate. Our study's major goal was to investigate the influence of MRI on the primary surgical treatment of early breast cancer: type of surgery, time to surgery, rate of reoperations.

The Impact of Magnetic Resonance Imaging on the Diagnosis of High-Energy Ipsilateral Femoral Neck and Shaft Fractures

To evaluate the most common femoral shaft fracture morphology associated with an ipsilateral femoral neck fracture in high-energy blunt trauma using magnetic resonance imaging (MRI). Retrospective review. Level 1 trauma center. 219 consecutive patients sustaining 228 femoral shaft fractures from high-energy blunt trauma. Fracture patterns were analyzed using the OTA/AO classification system. In addition, location of the fracture was measured as the distance from the distal aspect of the lesser trochanter to the center of the femoral shaft fracture. An OTA/AO 31 type fracture was seen in 16.5% (20/121) of patients presenting with OTA/AO 32-A type fractures, 12% (6/50) of patients with OTA/AO 32-B type fractures, and 26.3% (15/57) of patients with OTA/AO 32-C type fractures. The fractures that occurred in the middle or distal third of the femur shaft constituted 95.1% (39/41). In this cohort, patients with middle and distal third OTA/AO 32-C type fractures had the highest association with an ipsilateral OTA/AO 31 type fracture. OTA/AO 32-A2 and 32-A3 type fractures had the highest association with femoral neck fractures seen only on MRI. The data presented suggest continued usage of the rapid sequence pelvic MRI for all patients with high-energy femoral shaft fractures in whom a femoral neck fracture was not seen on an x-ray or a computed tomography scan. Diagnostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

The impact of magnetic resonance imaging in the assessment of iron overload in heart and liver in transfusion-dependent thalassemic children: Minia experience

BackgroundThalassemia is the most prevalent single-gene disorder. Myocardial and hepatic iron depositions lead to complications and eventually death. We aimed to assess the diagnostic efficacy of magnetic resonance imaging T2* (MRI T2*) in quantifying iron overload in liver and heart in transfusion-dependent B-thalassemia major (TDT) children.MethodsProspective clinical study was carried on sixty children diagnosed with TDT. All of them underwent laboratory investigations, including CBC, serum iron, and ferritin levels. MRI T2* of the heart and liver was carried out to measure the iron overload and estimate the left ventricular ejection fraction (LVEF).ResultsThirty-eight males and 22 females with TDT with a mean age of 13.23 years were included. Twenty cases (33.3%) had severe liver iron overload, while 36 (60%) had normal cardiac iron. There was a moderate significant negative association between hepatic and cardiac iron deposition (P = 0.03). All cases with severe cardiac iron overload had impaired LVEF below 56%. A non-significant positive association was noticed between cardiac iron deposition and LVEF in T2* (P = 0.08). A moderate negative significant association was detected between hepatic iron deposition and serum ferritin, while a fair negative significant association was found between serum ferritin and cardiac iron deposition with P values of 0.04 and 0.02, respectively.ConclusionMRI T2* is the gold standard for monitoring and follow-up of iron overload in the heart and liver. It should be routinely performed in all TDT children as liver iron, and serum ferritin do not reflect cardiac iron overload.

Magnetic Resonance Image Feature Analysis under Deep Learning in Diagnosis of Neurological Rehabilitation in Patients with Cerebrovascular Diseases.

To explore the impact of magnetic resonance imaging (MRI) image features based on deep learning algorithms on the neurological rehabilitation of patients with cerebrovascular diseases, eighty patients with acute cerebrovascular disease were selected as the research objects. According to whether the patients were with vascular cognitive impairment (VCI), they were divided into VCI group (34 cases) and non-VCI group (46 cases). In addition, based on the convolutional neural network (CNN), a new multimodal CNN image segmentation algorithm was proposed. The algorithm was applied to the segmentation of MRI images of patients with vascular cognitive impairment (VCI) and compared with the segmentation results of CNN and fully CNN (FCN). As a result, the segmentation results of the three different algorithms showed that the Dice coefficient, accuracy, and recall of the multimodal CNN algorithm were 0.78 ± 0.24, 0.81 ± 0.28, and 0.88 ± 0.32, respectively, which were significantly increased compared to those of other two algorithms (P < 0.05). The neurological evaluation results showed that the MMSE and MoCA scores of VCI patients were 15.4 and 14.6 ± 5.31, respectively, which were significantly lower than those of the non-VCI group (P < 0.05). The TMT-a and TMT-b scores of VCI patients were 221.7 and 385.9, respectively, which were significantly higher than those of the non-VCI group (P < 0.05). The FA and MD values of nerve function-related fibers shown in the MRI images of the VCI group were significantly different from those of the non-VCI group (P < 0.05). Therefore, the neurological recovery process of VCI patients was affected by multiple neurocognitive-related fiber structures. To sum up, the multimodal CNN algorithm can sensitively and accurately reflect the degree of neurological impairment in patients with cerebrovascular disease and can be applied to disease diagnosis and neurological evaluation of VCI patients.

Traumatic low lumbar fractures: How often MRI changes the fracture classification or clinical decision-making compared to CT alone?

To determine the impact of magnetic resonance imaging (MRI) on fracture classification for low lumbar fractures (LLFs) compared to CT alone. This study was a retrospective review of 41 consecutive patients with LLFs who underwent CT and MRI within 10 days of injury. Three reviewers classified all fractures according to AOSpine Classification and the Thoracolumbar Injury Classification (TLISS). Posterior ligamentous complex (PLC) injury in MRI was defined by black stripe discontinuity and in CT by the presence of: vertebral body translation, facet joint malalignment, horizontal laminar or spinous process fracture, and interspinous widening. The proportion of patients with AO type A/B/C and with TLISS < 5 and≥5 was compared between CT and MRI. We examined the overall accuracy and individual CT findings for PLC injury. AO classification using CT was: AO type A in 26 patients (61%), type B in 7 patients (17%), and type C in 8 patients (22%). Seventeen patients (41%) had a TLISS≥5 while 24 (59%) had TLISS < 5. The addition of MRI after CT changed the AO classification in only 2 patients (4.9%, 95% CI (0.6-16.5%) due to upgrade of type A to type B or vice versa, but did not change TLISS from < 5 to≥5 [p< 0.0001; 95% CI (0.59, 0.77)]. CT was highly accurate (95%) for diagnosis of PLC injury in LLFs. Addition of MRI after CT did not change the AO classification or TLISS, compared to CT alone, thus suggesting limited additional value of MRI for PLC assessment or fracture classification.

Diagnosis and Treatment Effect of Convolutional Neural Network-Based Magnetic Resonance Image Features on Severe Stroke and Mental State.

The purpose of this paper is to explore the impact of magnetic resonance imaging (MRI) image features based on convolutional neural network (CNN) algorithm and conditional random field on the diagnosis and mental state of patients with severe stroke. 208 patients with severe stroke who all received MRI examination were recruited as the research objects. According to cerebral small vascular disease (CSVD) score, the patients were divided into CSVD 0∼4 groups. The patients who completed the three-month follow-up were classified into cognitive impairment group (124 cases) and the noncognitive impairment group (84 cases) according to the cut-off point of the Montreal cognitive assessment (MOCA) scale score of 26. A novel image segmentation algorithm was proposed based on U-shaped fully CNN (U-Net) and conditional random field, which was compared with the fully CNN (FCN) algorithm and U-Net algorithm, and was applied to the MRI segmentation training of patients with severe stroke. It was found that the average symmetric surface distance (ASSD) (3.13 ± 1.35), Hoffman distance (HD) (28.71 ± 9.05), Dice coefficient (0.78 ± 1.35), accuracy (0.74 ± 0.11), and sensitivity (0.85 ± 0.13) of the proposed algorithm were superior to those of FCN algorithm and U-Net algorithm. There were significant differences in the MOCA scores among the five groups of patients from CSVD 0 to CSVD 4 in the three time periods (0, 1, and 3 months) (P < 0.05). Differences in cerebral microhemorrhage (CMB), perivascular space (PVS), and number of cavities, Fazekas, and total CSVD scores between the two groups were significant (P < 0.05). Multivariate regression found that the number of PVS, white matter hyperintensity (WMH) Fazekas, and total CSVD score were independent factors of cognitive impairment. In short, MRI images based on deep learning image segmentation algorithm had good application value for clinical diagnosis and treatment of stroke and can effectively improve the detection effect of brain domain characteristics and psychological state of patients after stroke.

Impact of magnetic resonance imaging on functional integrity of non-conditional cardiovascular implantable electronic devices.

Cardiovascular implantable electronic devices (CIEDs) have historically restricted the use of magnetic resonance imaging (MRI) due to the potential clinical and configurational risks associated with electromagnetic interference. In this study, the authors investigated the impact of MRI on the functional integrity of non-conditional CIEDs and their clinical correlates. In this prospective, observational single-center study, we enrolled patients undergoing MRI over a 5-year period. Prior to assessing the impact of MRI on CIEDs, we performed interrogations in sequential duplication to assess the intrinsic variability of devices. Subsequently, we performed interrogations immediately after MRI, and monitored changes in device parameters and clinical events. We completed 492 MRI studies, 58% in patients with permanent pacemakers (PPMs) and 42% with implantable cardioverter defibrillators (ICDs). Subsequent MRI exposures occurred in 15% encounters. Accounting for intrinsic variability in CIED leads, there were no significant changes in RA, RV, or LV parameters after MRI, regardless of the region imaged (thoracic vs. non-thoracic), type of CIED (PPMs vs. ICDs) and among those with serial MRIs. When ranked for % change pre- to post-MRI, the majority of RA, RV, and LV metrics for thresholds, sensing, and impedance conformed to ≤20% change from baseline. No significant clinical adverse cardiac events or effect on device microcircuitry occurred during the study. Incorporating a novel reproducibility tactic, there were neither clinically meaningful device parameter changes nor adverse clinical events during or following MRIs, suggesting the effects of MRI on non-conditional CIED integrity are far less than previously perceived.

Evaluation of the Impact of Magnetic Resonance Imaging with Susceptibility-weighted Imaging for Screening and Surveillance of Radiation-induced Cavernomas in Long-term Survivors of Malignancy

AimsRadiation-induced cavernomas (RIC) are common late toxicities in long-term survivors of malignancy following cerebral irradiation. However, the natural history of RIC is poorly described. We report the first series of long-term surveillance of RIC using modern magnetic resonance imaging (MRI) including highly sensitive susceptibility-weighted imaging (SWI). The aims of this research were to better characterise the natural history of RIC and investigate the utility of MRI-SWI for screening and surveillance. Materials and methodsEligibility required long-term survivors of malignancy with previous exposure to cerebral irradiation and RIC identified on MRI-SWI surveillance. The number and size of RIC were reported on Baseline MRI-SWI and last Follow-up MRI-SWI. ResultsIn total, 113 long-term survivors with RIC underwent MRI-SWI surveillance; 109 (96%) were asymptomatic at the time of RIC diagnosis. The median age at cerebral irradiation was 9.3 years; the median radiotherapy dose was 50.4 Gy. The median time from cerebral irradiation to Baseline MRI-SWI was 17.9 years. On Baseline MRI-SWI, RIC multiplicity was present in 89% of patients; 34% had >10 RIC; 65% had RIC ≥4 mm. The median follow-up from Baseline MRI-SWI was 7.3 years. On Follow-up MRI-SWI, 96% of patients had multiple RIC; 62% had >10 RIC; 72% had RIC ≥4 mm. Of the 109 asymptomatic patients at RIC diagnosis, 96% remained free from RIC-related symptoms at 10 years. Only two required neurosurgical intervention for RIC; there was no RIC-related mortality. ConclusionsRIC are commonly multiple, asymptomatic and typically increase in size and number over time. Our findings suggest that MRI-SWI for screening of RIC is unlikely to influence longer term intervention in asymptomatic cancer survivors. In the absence of neurological symptoms, assessment or monitoring of RIC are insufficient indications for MRI-SWI surveillance for long-term survivors of malignancy with past exposure to cerebral irradiation.

Editorial Comment.

No AccessJournal of UrologyAdult Urology1 May 2021Editorial CommentThis article comments on the following:Heterogeneity in Genomic Risk Assessment from Tissue Based Prognostic Signatures Used in the Biopsy Setting and the Impact of Magnetic Resonance Imaging Targeted Biopsy Vikram M. Narayan Vikram M. NarayanVikram M. Narayan Urologic Oncology, Emory University School of Medicine, Atlanta, Georgia More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001559.01AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "Editorial Comment." The Journal of Urology, 205(5), p. 1351 Reference 1. : Genomic predictors of outcome in prostate cancer. Eur Urol 2015; 68: 1033. Google Scholar © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetailsRelated articlesJournal of UrologyDec 24, 2020, 12:00:00 AMHeterogeneity in Genomic Risk Assessment from Tissue Based Prognostic Signatures Used in the Biopsy Setting and the Impact of Magnetic Resonance Imaging Targeted Biopsy Volume 205Issue 5May 2021Page: 1351-1351 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Vikram M. Narayan Urologic Oncology, Emory University School of Medicine, Atlanta, Georgia More articles by this author Expand All Advertisement PDF DownloadLoading ...

Volumetric and dosimetric impact of MRI in delineation of gross tumor volume of non-spinal vertebral metastases treated with stereotactic ablative radiation therapy

PurposeTo investigate the Gross Tumor Volumes (GTV) and its dosimetric impact of magnetic resonance imaging (MRI) assisted contouring for non-spinal metastasis treated with stereotactic ablative body radiotherapy (SABR). Material and methodsFive observer contours on CT (GTVCT) and CT+MR (GTVCT+MR) were evaluated against expert team contours (GTVEC) for 14 selected cases. Dice Similarity Index (DSC) and Geographical Miss Index (GMI) quantify observer variation. We also analyze the maximum dose (Dmax) and dose received by 0.35cc (D0.35cc) of the spinal cord (SC) for GTVCT and GTVCT+MR, where optimization parameters and priorities were unchanged. Percent rank function is also evaluated for SC doses. ResultsThe mean DSC and GMI scores for the CT-only dataset are 0.6974 and 0.2851 and for CT+MR dataset is 0.7764 and 0.1907 respectively. Statistically, significant results were found for mean GTV volumes between GTVEC versus GTVCT and GTVCT versus GTVCT+MR (P<0.001). Dosimetric analysis of Dmax and D0.35cc exceeded 84.2% and 88.5% of times its respective threshold doses for CT-only dataset, whereas for the CT+MR dataset, it exceeded only by 18% and 15.7% times. ‘Percent rank’ function analysis for SC doses also indicates the same. ConclusionThis study supports MRI fusion for GTV and OAR delineation for non-spinal metastasis. Our study showed that the dosimetric analysis is vital for observer variation studies and the addition of the MR data set is significant to improve the confidence of Stereotactic treatments.

Apparent diffusion coefficient magnetic resonance imaging (ADC-MRI) in the axillary breast cancer lymph node metastasis detection: a narrative review.

The presence of axillary lymph nodes metastases in breast cancer is the most significant prognostic factor, with a great impact on morbidity, disease-related survival and management of oncological therapies; for this reason, adequate imaging evaluation is strictly necessary. Physical examination is not enough sensitive to assess breast cancer nodal status; axillary ultrasonography (US) is commonly used to detect suspected or occult nodal metastasis, providing exclusively morphological evaluation, with low sensitivity and positive predictive value. Currently, sentinel lymph node biopsy (SLNB) and/or axillary dissection are the milestone for the diagnostic assessment of axillary lymph node metastases, although its related morbidity. The impact of magnetic resonance imaging (MRI) in the detection of nodal metastases has been widely investigated, as it continues to represent the most promising imaging modality in the breast cancer management. In particular, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values represent additional reliable non-contrast sequences, able to improve the diagnostic accuracy of breast cancer MRI evaluation. Several studies largely demonstrated the usefulness of implementing DWI/ADC MRI in the characterization of breast lesions. Herein, in the light of our clinical experience, we perform a review of the literature regarding the diagnostic performance and accuracy of ADC value as potential pre-operative tool to define metastatic involvement of nodal structures in breast cancer patients. For the purpose of this review, PubMed, Web of Science, and SCOPUS electronic databases were searched with different combinations of "axillary lymph node", "breast cancer", "MRI/ADC", "breast MRI" keywords. All original articles, reviews and metanalyses were included.