Quantitative evaluation of computed and voxelwise computed diffusion-weighted imaging in breast cancer

Cheng, Qingyuan; Ye, Shuxin; Fu, Chuqi; Zhou, Jiejie; He, Xiaxia; Miao, Haiwei; Xu, Nina; Wang, Meihao

doi:10.1259/bjr.20180978

Cited by 7 publications

(5 citation statements)

References 20 publications

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“…Traditional nursing applies the same intervention measures to all patients, fails to consider the different disease states and nursing needs of different patients, and is very limited in terms of its clinical treatment efficacy. Conversely, personalized nursing with a quantitative evaluation of the initial severity of the disease with scientific scales, implements differentiated resource allocations and nursing intensity for patients with different symptoms and severity levels, so as to meet the needs of different patients, and improve nursing efficiency (28)(29)(30)(31).…”

Section: Discussionmentioning

confidence: 99%

Effect of personalized nursing based on quantitative evaluation strategies on remission of first-episode schizophrenia comparing to usual care: a systematic review and meta-analysis

Yan¹,

Yu²,

Zhu³

et al. 2022

Ann Palliat Med

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Background: The drug control of symptoms is for now the main clinical treatment of schizophrenia, but patients' varying condition and poor compliance can also fluctuate the therapeutic effect. Personalized nursing with a quantitative evaluation strategy (PNQES) may help improve the compliance and symptoms, but there are controversies over the outcomes reported in each specific study; the meta-analysis method aims to resolve the controversies over studies, thus, we conducted this study to pooling the results of controlled clinical studies, and to systematically evaluate the effects of this nursing model. Methods: The PubMed, Medline, Embase, China National Knowledge Infrastructure, and Wanfang databases were selected and searched for relevant articles for PNQES comparing to usual care. The inclusion criteria were established according to the Participants, Interventions, Comparisons, Outcomes, and Study (PICOS) framework. The Cochrane risk of bias 2.0 tool was used to evaluate the risk of bias of the included articles. The symptom scores, treatment compliance rate, quality of life, and social function indicators of the patients after nursing were quantitatively analyzed with effect sizes of mean difference (MD) or standard mean difference (SMD).Results: The 11 included articles comprised a total of 1,251 patients with experimental group 625 and control group 626. Of all the 11 articles, only 1 had a "low" risk of bias, while the other articles had "some concern of risk;" none of the articles had a "high" risk of bias. The meta-analysis showed that patients who received PNQES had a significantly lower Positive and Negative Syndrome Scale (PANSS) total score after care than patients who received routine care [MD =−9.95, 95% confidence interval (CI): −14.35, −5.55; P<0.00001]. Further, the treatment compliance rate of patients who received PNQES was significantly higher (odds ratio =4.44, 95% CI: 2.17, 9.09; P<0.0001), as was the quality of life (standard MD =2.40, 95% CI: 1.46, 3.34; P<0.00001). Further, the social function deficit score was significantly lower (MD =−2.25, 95% CI: −3.75, −0.76; P=0.003). Subgroup and regression analyses showed that patient age, initial PANSS score, and the quantitative method of disease severity were not the sources of heterogeneity. Different intervention approaches applied may have been the source of heterogeneity.Discussion: The application of PNQES is helpful for improving patients' symptoms and disease outcomes, treatment compliance, social function, and quality of life. It is suggested to be generalized in clinical application.

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Section: Discussionmentioning

confidence: 99%

Effect of personalized nursing based on quantitative evaluation strategies on remission of first-episode schizophrenia comparing to usual care: a systematic review and meta-analysis

Yan¹,

Yu²,

Zhu³

et al. 2022

Ann Palliat Med

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“…For example, in high-resolution breast DWI, 29 the signal-to-noise ratio generally decreases and thus lower b-values might be optimal for lesion detection. An important approach in such a setting might be to acquire only data up to, for example, 1000 or 1500 s/mm 2 and compute the high b-value images 22,30 . Other factors such as different fat saturation approaches and dependence on scanner technology may also be of importance with respect to the generalizability of this optimal b-value finding 31 …”

Section: Discussionmentioning

confidence: 99%

“…An important approach in such a setting might be to acquire only data up to, for example, 1000 or 1500 s/mm 2 and compute the high b-value images. 22,30 Other factors such as different fat saturation approaches and dependence on scanner technology may also be of importance with respect to the generalizability of this optimal b-value finding. 31 In this study, 1 breast cancer recurrence was overlooked without CE in a woman after breast-conserving therapy.…”

Section: Discussionmentioning

confidence: 99%

Ultra-High b-Value Diffusion-Weighted Imaging-Based Abbreviated Protocols for Breast Cancer Detection

et al. 2021

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Objectives: Contrast-enhanced (CE) magnetic resonance imaging (MRI) is the most effective imaging modality for breast cancer detection. A contrast agent-free examination technique would be desirable for breast MRI screening. The purpose of this study was to evaluate the capability to detect and characterize suspicious breast lesions with an abbreviated, non-contrast-enhanced MRI protocol featuring ultra-high b-value diffusion-weighted imaging (DWI) compared with CE images. Materials and Methods: The institutional review board-approved prospective study included 127 female subjects with different clinical indications for breast MRI. Magnetic resonance imaging examinations included DWI sequences with b-values of 1500 s/mm 2 (b1500) and 2500 s/mm 2 (b2500), native T1-and T2-weighted images, and CE sequences at 1.5 T and 3 T scanners. Two reading rounds were performed, including either the b1500 or the b2500 DWI in consecutive assessment steps: (A) maximum intensity projections (MIPs) of DWI, (B) DWI and apparent diffusion coefficient maps, (C) as (B) but with additional native T1-and T2-weighted images, and (D) as (C) but with additional CE images (full-length protocol). Two readers independently determined the presence of a suspicious lesion. Histological confirmation was obtained for conspicuous lesions, whereas the full MRI data set was obtained for inconspicuous and clearly benign lesions. Statistical analysis included calculation of diagnostic accuracy and interrater agreement via the intraclass correlation coefficient. Results: The cohort comprised 116 cases with BI-RADS 1 findings and 138 cases with BI-RADS ≥2 findings, including 38 histologically confirmed malignancies. For (A), breasts without pathological findings could be recognized with high diagnostic accuracy (negative predictive value, ≥97.0%; sensitivity, ≥92.1% for both readers), but with a limited specificity (≥58.3%; positive predictive value, ≥28.6%). Within the native readings, approach (C) with b2500 performed best (negative predictive value, 99.5%; sensitivity, 97.4%; specificity, 88.4%). The intraclass correlation coefficient was between 0.683 (MIP b1500) and 0.996 (full protocol). Conclusions: A native abbreviated breast MRI protocol with advanced high b-value DWI might allow nearly equivalent diagnostic accuracy as CE breast MRI and seems to be well suited for lesion detection purposes.

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“…Most of the studies have almost exclusively focused on the visibility of breast cancer [20,22,[33][34][35][36]; therefore, there is limited information on the conspicuity of benign breast lesions at high or synthetic b-values. While Chen et al [37] found no significant differences in conspicuity grades using b-values of 600, 800, and 1000 s/mm 2 , our results point to a difference in conspicuity.…”

Section: Discussionmentioning

confidence: 99%

“…Although synthetic b-values over 1000 s/mm 2 have demonstrated an improvement in tumor visualization and image quality [ 19 , 20 , 22 , 34 , 35 , 40 – 43 ], DCE-MRI outperforms DWI for breast cancer visualization and detection with a higher sensitivity across all readers. This is in accordance with the current literature: DCE-MRI outperforms unenhanced MRI with or without supportive sequences for cancer visualization [ 9 , 16 ].…”

Section: Discussionmentioning

confidence: 99%

Diagnostic value of diffusion-weighted imaging with synthetic b-values in breast tumors: comparison with dynamic contrast-enhanced and multiparametric MRI

et al. 2020

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Objectives To assess DWI for tumor visibility and breast cancer detection by the addition of different synthetic b-values. Methods Eighty-four consecutive women who underwent a breast-multiparametric-MRI (mpMRI) with enhancing lesions on DCE-MRI (BI-RADS 2-5) were included in this IRB-approved retrospective study from September 2018 to March 2019. Three readers evaluated DW acquired b-800 and synthetic b-1000, b-1200, b-1500, and b-1800 s/mm 2 images for lesion visibility and preferred b-value based on lesion conspicuity. Image quality (1-3 scores) and breast composition (BI-RADS) were also recorded. Diagnostic parameters for DWI were determined using a 1-5 malignancy score based on qualitative imaging parameters (acquired + preferred synthetic b-values) and ADC values. BI-RADS classification was used for DCE-MRI and quantitative ADC values + BI-RADS were used for mpMRI. Results Sixty-four malignant (average = 23 mm) and 39 benign (average = 8 mm) lesions were found in 80 women. Although b-800 achieved the best image quality score, synthetic b-values 1200-1500 s/mm 2 were preferred for lesion conspicuity, especially in dense breast. b-800 and synthetic b-1000/b-1200 s/mm 2 values allowed the visualization of 84-90% of cancers visible with DCE-MRI performing better than b-1500/b-1800 s/mm 2. DWI was more specific (86.3% vs 65.7%, p < 0.001) but less sensitive (62.8% vs 90%, p < 0.001) and accurate (71% vs 80.7%, p = 0.003) than DCE-MRI for breast cancer detection, where mpMRI was the most accurate modality accounting for less false positive cases. Conclusion The addition of synthetic b-values enhances tumor conspicuity and could potentially improve tumor visualization particularly in dense breast. However, its supportive role for DWI breast cancer detection is still not definite. Key Points • The addition of synthetic b-values (1200-1500 s/mm 2) to acquired DWI afforded a better lesion conspicuity without increasing acquisition time and was particularly useful in dense breasts. • Despite the use of synthetic b-values, DWI was less sensitive and accurate than DCE-MRI for breast cancer detection. • A multiparametric MRI modality still remains the best approach having the highest accuracy for breast cancer detection and thus reducing the number of unnecessary biopsies.

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Quantitative evaluation of computed and voxelwise computed diffusion-weighted imaging in breast cancer

Cited by 7 publications

References 20 publications

Effect of personalized nursing based on quantitative evaluation strategies on remission of first-episode schizophrenia comparing to usual care: a systematic review and meta-analysis

Effect of personalized nursing based on quantitative evaluation strategies on remission of first-episode schizophrenia comparing to usual care: a systematic review and meta-analysis

Ultra-High b-Value Diffusion-Weighted Imaging-Based Abbreviated Protocols for Breast Cancer Detection

Diagnostic value of diffusion-weighted imaging with synthetic b-values in breast tumors: comparison with dynamic contrast-enhanced and multiparametric MRI

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