Preoperative magnetic resonance imaging use and oncologic outcomes in premenopausal breast cancer patients.
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ABSTRACT:
SUBMITTER: Zeng Z
PROVIDER: S-EPMC7532157 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
Preoperative magnetic resonance imaging use and oncologic outcomes in premenopausal breast cancer patients.
Zeng Zexian Z Amin Amanda A Roy Ankita A Pulliam Natalie E NE Karavites Lindsey C LC Espino Sasa S Helenowski Irene I Li Xiaoyu X Luo Yuan Y Khan Seema A SA
NPJ breast cancer 20201002
Breast magnetic resonance imaging (MRI) delineates disease extent sensitively in newly diagnosed breast cancer patients, but improved cancer outcomes are uncertain. Young women, for whom mammography is less sensitive, are expected to benefit from MRI-based resection. We identified 512 women aged ≤50 years, undergoing breast-conserving treatment (BCT: tumor-free resection margins and radiotherapy) during 2006-2013 through Northwestern Medicine database queries; 64.5% received preoperative MRI and ...[more]
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Project description:BackgroundAdvancements in imaging technology have been associated with changes to operative planning in treatment of localized prostate cancer. The impact of these changes on postoperative outcomes is understudied.ObjectiveTo compare oncologic and functional outcomes between men who had computed tomography (CT) and those who had multiparametric magnetic resonance imaging (mpMRI) prior to undergoing radical prostatectomy.Design setting and participantsIn this retrospective cohort study, we identified all men who underwent radical prostatectomy (n = 1259) for localized prostate cancer at our institution between 2009 and 2016. Of these, 917 underwent preoperative CT and 342 mpMRI.Outcome measurements and statistical analysisBiochemical recurrence-free survival, positive margin status, postoperative complications, and 1-yr postprostatectomy functional scores (using the 26-item Expanded Prostate Cancer Index Composite [EPIC-26] questionnaire) were compared between those who underwent preoperative CT and those who underwent mpMRI using propensity score weighted Cox proportional hazard regression, logistic regression, and linear regression models.Results and limitationsBaseline and 1-yr follow-up EPIC-26 data were available for 449 (36%) and 685 (54%) patients, respectively. After propensity score weighting, no differences in EPIC-26 functional domains were observed between the imaging groups at 1-yr follow-up. Positive surgical margin rates (odds ratio 1.03, 95% confidence interval [CI] 0.77-1.38, p = 0.8) and biochemical recurrence-free survival (hazard ratio 1.21, 95% CI 0.84-1.74, p = 0.3) were not significantly different between groups. Early and late postoperative complications occurred in 219 and 113 cases, respectively, and were not different between imaging groups. Our study is limited by a potential selection bias from the lack of functional scores for some patients.ConclusionsIn this single-center study of men with localized prostate cancer undergoing radical prostatectomy, preoperative mpMRI had minimal impact on functional outcomes and oncologic control compared with conventional imaging. These findings challenge the assumptions that preoperative mpMRI improves operative planning and perioperative outcomes.Patient summaryIn this study, we assessed whether the type of prostate imaging performed prior to surgery for localized prostate cancer impacted outcomes. We found that urinary and sexual function, cancer control, and postoperative complications were similar regardless of whether magnetic resonance imaging or computed tomography was utilized prior to surgery.
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Project description:PURPOSE:To examine associations between pre-operative magnetic resonance imaging (MRI) use and clinical outcomes among women undergoing breast-conserving surgery (BCS) with or without radiotherapy for early-stage breast cancer. METHODS:We identified women from the Surveillance, Epidemiology, and End Results-Medicare dataset aged 67-94 diagnosed during 2004-2010 with stage I/II breast cancer who received BCS. We compared subsequent mastectomy and breast cancer mortality with versus without pre-operative MRI, using Cox regression and competing risks models. We further stratified by receipt of radiotherapy for subgroup analyses. RESULTS:Our sample consisted of 24,379 beneficiaries, 4691 (19.2%) of whom received pre-operative MRI. Adjusted rates of subsequent mastectomy and breast cancer mortality were not significantly different with and without MRI: 3.2 versus 4.1 per 1000 person-years [adjusted hazard ratio (AHR) 0.92; 95% confidence interval (CI) 0.70-1.19] and 5.3 versus 8.7 per 1000 person-years (AHR 0.89; 95% CI 0.73-1.08), respectively. In subgroup analyses, women receiving BCS plus radiotherapy had similar rates of subsequent mastectomy (AHR 1.17; 95% CI 0.84-1.61) and breast cancer mortality (AHR 1.00; 95% CI 0.80-1.24) with versus without MRI. However, among women receiving BCS alone, MRI use was associated with lower risks of subsequent mastectomy (AHR 0.60; 95% CI 0.37-0.98) and breast cancer mortality (AHR 0.57; 95% CI 0.36-0.92). CONCLUSIONS:Pre-operative MRI was associated with improved outcomes among older women with breast cancer receiving BCS alone, but not among those receiving BCS plus radiotherapy. Further research is needed to identify appropriate settings for which MRI may be helpful.
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Project description:BackgroundPreoperative magnetic resonance imaging (MRI) use has increased among older women diagnosed with breast cancer. MRI detects additional malignancy, but its impact on locoregional surgery and radiation treatment remains unclear.MethodsWe examined the associations of preoperative MRI with initial locoregional treatment type (mastectomy, breast conserving surgery [BCS] with radiation therapy [RT], and BCS without RT) and BCS reoperation rates for Surveillance, Epidemiology, and End Results Medicare women diagnosed with stages 0 to III breast cancer from 2005 to 2009 (n = 55,997).ResultsWe found no association of initial locoregional treatment of mastectomy (odds ratios [OR], 1.04; 95% confidence intervals, .98 to 1.11) or reoperation after initial BCS (OR, .96; 95% confidence intervals, .89 to 1.03) between women with preoperative MRI (16.2%) compared to women without MRI. However, women with MRI who had initial BCS were more likely to undergo RT (OR, 1.09 [1.02 to 1.16]).ConclusionsPreoperative breast MRI in Medicare-enrolled women with stages 0 to III breast cancer was not associated with increased mastectomy. However, in older women with MRI undergoing BCS, there was a greater use of RT.
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Project description:ObjectiveDue to an insidious proliferative pattern, invasive lobular breast cancer (ILC) often fails to form a defined radiological or palpable lesion and accurate diagnosis remains challenging. This study aimed to determine the value of preoperative magnetic resonance imaging (MRI) for ILC and its impact on surgical outcomes.MethodsConsecutive symptomatic patients diagnosed with ILC in a tertiary centre over a 9-year period were reviewed. The time from diagnosis until surgery, initial type of surgery/index operation (breast-conserving surgery [BCS]/mastectomy) and the rates of reoperation (re-excision/completion mastectomy) were recorded. Patients were grouped into those who received conventional imaging and preoperative MRI (MR+) and those who received conventional imaging alone (MR-).ResultsThere were 218 cases of ILC, and 32.1% (n = 70) had preoperative MRI. Time from diagnosis to surgery was longer in the MR+ than the MR- group (32.5 vs 21.1 days, P < .001) even when adjusting for age and breast density. Initial BCS was performed on 71.4% (n = 50) of MR+ patients and 72.3% (n = 107) of the MR- group. While the rate of completion mastectomy following initial BCS was higher in the MR+ group (30.0%, n = 15 vs 14.0%, n = 15; χ2 = 5.63; P = .018), this association was not maintained in multivariable analysis. No difference was recorded in overall (initial and completion) mastectomy rate between the MR+ and MR- group (50.0%, n = 35 vs 37.8%, n = 56; χ2 = 2.89; P = .089). Margin re-excision following BCS was comparable between groups (8.0%, n =4, vs 9.3%, n = 10; χ2 = 0.076, P = .783) despite the selection bias for borderline conservable cases in the MR+ group. The rate of usage of MRI for ILC cases declined over the study period.ConclusionWhile MRI was associated with minor delays in treatment and did not reduce overall rates of margin re-excision or completion mastectomy, it altered the choice of surgical procedure in almost a quarter of MR+ cases. The benefit of preoperative breast MRI appears to be confined to select (younger, dense breast, borderline conservable) cases in symptomatic ILC.
| S-EPMC7430084 | biostudies-literature
Project description:Functional magnetic resonance imaging (fMRI) is a well-known non-invasive technique for the study of brain function. One of its most common clinical applications is preoperative language mapping, essential for the preservation of function in neurosurgical patients. Typically, fMRI is used to track task-related activity, but poor task performance and movement artifacts can be critical limitations in clinical settings. Recent advances in resting-state protocols open new possibilities for pre-surgical mapping of language potentially overcoming these limitations. To test the feasibility of using resting-state fMRI instead of conventional active task-based protocols, we compared results from fifteen patients with brain lesions while performing a verb-to-noun generation task and while at rest. Task-activity was measured using a general linear model analysis and independent component analysis (ICA). Resting-state networks were extracted using ICA and further classified in two ways: manually by an expert and by using an automated template matching procedure. The results revealed that the automated classification procedure correctly identified language networks as compared to the expert manual classification. We found a good overlay between task-related activity and resting-state language maps, particularly within the language regions of interest. Furthermore, resting-state language maps were as sensitive as task-related maps, and had higher specificity. Our findings suggest that resting-state protocols may be suitable to map language networks in a quick and clinically efficient way.
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Project description:BackgroundAppropriate preoperative identification of iCCA subtype is essential for personalized management, so the aim of this study is to investigate the role of MR imaging features in preoperatively differentiating the iCCA subtype.MethodsNinety-three patients with mass-forming intrahepatic cholangiocarcinoma (iCCA, 63 small duct type and 30 large duct type) were retrospectively enrolled according to the latest 5th WHO classification (mean age, males vs. females: 60.66 ± 10.53 vs. 61.88 ± 12.82, 50 men). Significant imaging features for differentiating large duct iCCA and small duct iCCA were identified using univariate and multivariate logistic regression analyses, and a regression-based predictive model was then generated. Furthermore, diagnostic performance parameters of single significant imaging features and the predictive model were obtained, and corresponding receiver operating characteristic (ROC) curves were subsequently presented.ResultsThe univariate analysis showed that tumor in vein, arterial phase hypoenhancement, intrahepatic duct dilatation, lack of targetoid restriction and lack of targetoid appearance in T2 were predictors of large duct type iCCA. Arterial phase hypoenhancement, intrahepatic duct dilatation and lack of targetoid restriction were independent predictors for large duct type iCCA in multivariate analysis. The regression-based predictive model has achieved the best preoperative prediction performance in iCCA subcategorization so far. The area under the ROC curve of the regression-based predictive model was up to 0.91 (95% CI: 0.85, 0.98), and it was significantly higher than every single significant imaging feature.ConclusionsArterial phase hypoenhancement, intrahepatic duct dilatation and lack of targetoid restriction could be considered reliable MR imaging indicators of large duct type iCCA. MR imaging features can facilitate noninvasive prediction of iCCA subtype with satisfactory predictive performance.
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Project description:PURPOSE:Identifying imaging phenotypes and understanding their relationship with prognostic markers and patient outcomes can allow for a noninvasive assessment of cancer. The purpose of this study was to identify and validate intrinsic imaging phenotypes of breast cancer heterogeneity in preoperative breast dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) scans and evaluate their prognostic performance in predicting 10 years recurrence. EXPERIMENTAL DESIGN:Pretreatment DCE-MRI scans of 95 women with primary invasive breast cancer with at least 10 years of follow-up from a clinical trial at our institution (2002-2006) were retrospectively analyzed. For each woman, a signal enhancement ratio (SER) map was generated for the entire segmented primary lesion volume from which 60 radiomic features of texture and morphology were extracted. Intrinsic phenotypes of tumor heterogeneity were identified via unsupervised hierarchical clustering of the extracted features. An independent sample of 163 women diagnosed with primary invasive breast cancer (2002-2006), publicly available via The Cancer Imaging Archive, was used to validate phenotype reproducibility. RESULTS:Three significant phenotypes of low, medium, and high heterogeneity were identified in the discovery cohort and reproduced in the validation cohort (P < 0.01). Kaplan-Meier curves showed statistically significant differences (P < 0.05) in recurrence-free survival (RFS) across phenotypes. Radiomic phenotypes demonstrated added prognostic value (c = 0.73) predicting RFS. CONCLUSIONS:Intrinsic imaging phenotypes of breast cancer tumor heterogeneity at primary diagnosis can predict 10-year recurrence. The independent and additional prognostic value of imaging heterogeneity phenotypes suggests that radiomic phenotypes can provide a noninvasive characterization of tumor heterogeneity to augment personalized prognosis and treatment.
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Project description:Despite the high sensitivity and widespread use of preoperative magnetic resonance imaging (MRI), the American Cancer Society and the National Comprehensive Cancer Network guidelines do not recommend the routine use of preoperative MRI owing to the conflicting results and lack of clear benefit to the surgical outcome (reoperation and mastectomy) and long-term clinical outcomes (local recurrence and metachronous contralateral breast cancer). Preoperative MRI detects additional cancers that are occult at mammography and ultrasound but increases the rate of mastectomy. Concerns about overdiagnosis and overtreatment of preoperative MRI might be mitigated by adjusting the confounding factors when conducting studies, using the state-of-the-art image-guided biopsy technique, applying the radiologists' cumulative experiences in interpreting MRI findings, and performing multiple lumpectomies in patients with multicentric cancer. Among the various imaging methods, dynamic contrast-enhanced MRI has the highest accuracy in predicting pathologic complete response after neoadjuvant chemotherapy. Prospective trials aimed at applying the MRI information to the de-escalation of surgical or radiation treatments are underway. In this review, current studies on the clinical outcomes of preoperative breast MRI are updated, and circumstances in which MRI may be useful for surgical planning are discussed.
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Project description:PurposeDetection of multifocal, multicentric, and contralateral breast cancers in patients affects surgical management. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can identify additional foci that were initially undetected by conventional imaging. However, its use is limited owing to low specificity and high false-positive rate. Multiparametric MRI (DCE-MRI + diffusion-weighted [DW] MRI) can increase the specificity. We aimed to describe the protocols of our prospective, multicenter, observational cohort studies designed to compare the diagnostic performance of DCE-MRI and multiparametric MRI for the diagnosis of multifocal, multicentric cancer and contralateral breast cancer in patients with newly diagnosed breast cancer.MethodsTwo studies comparing the performance of DCE-MRI and multiparametric MRI for the diagnosis of multifocal, multicentric cancer (NCT04656639) and contralateral breast cancer (NCT05307757) will be conducted. For trial NCT04656639, 580 females with invasive breast cancer candidates for breast conservation surgery whose DCE-MRI showed additional suspicious lesions (breast imaging reporting and data system [BI-RADS] category ≥ 4) on DCE-MRI in the ipsilateral breast will be enrolled. For trial NCT05307757, 1098 females with invasive breast cancer whose DCE-MRI showed contralateral lesions (BI-RADS category ≥ 3 or higher on DCE-MRI) will be enrolled. Participants will undergo 3.0-T DCE-MRI and DW-MRI. The diagnostic performance of DCE-MRI and multiparametric MRI will be compared. The receiver operating characteristic curve, sensitivity, specificity, positive predictive value, and characteristics of the detected cancers will be analyzed. The primary outcome is the difference in the receiver operating characteristic curve between DCE-MRI and multiparametric MRI interpretation. Enrollment completion is expected in 2024, and study results are expected to be presented in 2026.DiscussionThis prospective, multicenter study will compare the performance of DCE-MRI versus multiparametric MRI for the preoperative evaluation of multifocal, multicentric, and contralateral breast cancer and is currently in the patient enrollment phase.Trial registrationClinicalTrials.gov Identifier: NCT04656639, NCT05307757. Registered on April 1 2022.
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Project description:Glioblastoma, the most frequent primary malignant brain neoplasm, is genetically diverse and classified into four transcriptomic subtypes, i. e., classical, mesenchymal, proneural, and neural. Currently, detection of transcriptomic subtype is based on ex vivo analysis of tissue that does not capture the spatial tumor heterogeneity. In view of accumulative evidence of in vivo imaging signatures summarizing molecular features of cancer, this study seeks robust non-invasive radiographic markers of transcriptomic classification of glioblastoma, based solely on routine clinically-acquired imaging sequences. A pre-operative retrospective cohort of 112 pathology-proven de novo glioblastoma patients, having multi-parametric MRI (T1, T1-Gd, T2, T2-FLAIR), collected from the Hospital of the University of Pennsylvania were included. Following tumor segmentation into distinct radiographic sub-regions, diverse imaging features were extracted and support vector machines were employed to multivariately integrate these features and derive an imaging signature of transcriptomic subtype. Extracted features included intensity distributions, volume, morphology, statistics, tumors' anatomical location, and texture descriptors for each tumor sub-region. The derived signature was evaluated against the transcriptomic subtype of surgically-resected tissue specimens, using a 5-fold cross-validation method and a receiver-operating-characteristics analysis. The proposed model was 71% accurate in distinguishing among the four transcriptomic subtypes. The accuracy (sensitivity/specificity) for distinguishing each subtype (classical, mesenchymal, proneural, neural) from the rest was equal to 88.4% (71.4/92.3), 75.9% (83.9/72.8), 82.1% (73.1/84.9), and 75.9% (79.4/74.4), respectively. The findings were also replicated in The Cancer Genomic Atlas glioblastoma dataset. The obtained imaging signature for the classical subtype was dominated by associations with features related to edge sharpness, whereas for the mesenchymal subtype had more pronounced presence of higher T2 and T2-FLAIR signal in edema, and higher volume of enhancing tumor and edema. The proneural and neural subtypes were characterized by the lower T1-Gd signal in enhancing tumor and higher T2-FLAIR signal in edema, respectively. Our results indicate that quantitative multivariate analysis of features extracted from clinically-acquired MRI may provide a radiographic biomarker of the transcriptomic profile of glioblastoma. Importantly our findings can be influential in surgical decision-making, treatment planning, and assessment of inoperable tumors.
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