Which type of breast cancers is undetectable on ring-type dedicated breast PET?

Sasada, Shinsuke; Masumoto, Norio; Goda, Noriko; Kajitani, Keiko; Emi, Akiko; Kadoya, Takayuki; Okada, Morihito

doi:10.1016/j.clinimag.2018.05.010

Cited by 16 publications

(9 citation statements)

References 12 publications

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“…The RAS/ERK signaling pathway plays an important role in the occurrence and development of breast cancer and other epithelial tumors. Studies have shown that SHP2 participates in the RAS/ERK signaling pathway and plays an important regulatory role [ 15 ]. In the study of lung cancer and cartilage tumors, it was found that through the stimulation of EGF, IL-6, and other growth factors or cytokines, the phosphatase domain of SHP2 can activate the RAS signaling pathway and phosphorylate SHP2 after autophosphorylation [ 16 ].…”

Section: Related Workmentioning

confidence: 99%

Analysis of the Mechanism of Breast Metastasis Based on Image Recognition and Ultrasound Diagnosis

Huang

Zheng

Lai

2021

Journal of Healthcare Engineering

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Breast cancer is one of the cancers with the highest incidence among women. In the late stage, cancer cells may metastasize to a distance, causing multiple organ diseases, threatening the lives of patients. The detection of lymph node metastasis based on pathological images is a key indicator for the diagnosis and staging of breast cancer, and correct staging decisions are the prerequisite and basis for targeted treatment. At present, the detection of lymph node metastasis mainly relies on manual screening by pathologists, which is time-consuming and labor-intensive, and the diagnosis results are variable and subjective. The automatic staging method based on the panoramic image calculation of the sentinel lymph node of the breast proposed in this paper can provide a set of standardized, high-accuracy, and repeatable objective diagnosis results. However, it is very difficult to automatically detect and locate cancer metastasis areas in highly complex panoramic images of lymph nodes. This paper proposes a novel deep network training strategy based on the sliding window to train an automatic localization model of cancer metastasis area. The training strategy first trains the initial convolutional network in a small amount of data, extracts false-positive and false-negative image blocks, and uses manual screening combined with automatic network screening to reclassify the false-positive blocks to improve the class of negative categories. Using mammography, ultrasound, MRI, and 18F-FDG PET-CT examinations, the detection rate and diagnostic accuracy of primary cancers in the breast of patients with axillary lymph node metastasis as the first diagnosis were obtained. The detection rate and diagnostic accuracy of breast MRI for primary cancers in the breast are much higher than those of X-ray, ultrasound, and 18F-FDG PET-CT (all P values <0.001). Mammography, ultrasound, and PET-CT examinations showed no difference in the detection rate and diagnostic accuracy of primary cancers in the breast of patients with axillary lymph node metastasis as the first diagnosis. Breast MRI should be used as a routine examination for patients with axillary lymph node metastasis as the first diagnosis. The primary breast cancer in the first diagnosed patients with axillary lymph node metastasis is often presented as localized asymmetric compactness or calcification on X-ray; it often appears as small focal mass lesions and ductal lesions without three-dimensional space-occupying effect on ultrasound.

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Section: Related Workmentioning

confidence: 99%

Analysis of the Mechanism of Breast Metastasis Based on Image Recognition and Ultrasound Diagnosis

Huang

Zheng

Lai

2021

Journal of Healthcare Engineering

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“…However, the impacts of SUV and PUV are not equal. The reported correlation coefficients for SUV max of whole-body PET were 0.84-0.94 for the SUV max of ring-type dbPET and 0.78 for PUV max (12,(14)(15)(16).…”

Section: Discussionmentioning

confidence: 98%

Classification of Abnormal Findings on Ring-type Dedicated Breast PET for the Detection of Breast Cancer

et al. 2020

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Aim: To investigate the usefulness of classification of ring-type dedicated breast positron-emission tomography (dbPET) findings in detection of breast cancer. Patients and Methods: A total of 709 patients with breast cancer underwent dbPET before treatment. Each finding was morphologically categorized as a focus (uptake size ≤5 mm), mass (>5 mm), or non-mass (multiple uptakes not belonging to a three-dimensional mass or without distinct mass features). Non-mass uptakes were additionally classified as linear, focal, segmental, regional, or diffuse distributions. Lesion-to-background ratios were calculated. Results: Among 910 abnormal findings, 700 (76.9%) were malignant and 210 (23.1%) were benign. Morphologically, 198 (21.8%) lesions were foci, 431 (47.4%) were masses, and 281 (30.9%) were non-masses. In multivariate analysis, mass, focal and segmental distributions of nonmass lesions and high lesion-to-background ratio were significantly related to breast cancer (all p<0.001). Conclusion: Classification of abnormal findings on dbPET using morphology and lesion-to-background ratio were useful to detect breast cancer.Breast cancer is the most common cancer among adult women worldwide, comprising 30% of all cancer in women (1). Breast cancer screening reduces breast cancer mortality and early-stage detection leads to a favorable prognosis (2). Positron-emission tomography (PET)/computed tomography (CT) using 18 F-fluorodeoxyglucose (FDG) is a molecular approach used for cancer imaging and performed for cancer screening, staging and monitoring of treatment response, as well as predicting prognosis in breast cancer medicine. However, due to the limited spatial resolution of whole-body PET/CT, it is hard to detect small breast cancers. Dedicated breast PET (dbPET) was developed for high-resolution molecular breast imaging to detect sub-centimeter breast cancers. dbPET has two scanner types: opposite and ring (3). Both types improve the sensitivity for breast cancer detection compared to that of whole-body PET (4, 5). In addition, ring-type dbPET can be used to calculate the standardized uptake value (SUV) by obtaining three-dimensional images as well as attenuation and scatter correction, unlike oppositetype dbPET (6).In mammography, ultrasonography (US), and magnetic resonance imaging (MRI), category classifications of abnormal findings, such as the Breast Imaging Reporting and Data System (BI-RADS) (7), have been developed to standardize and optimize the management of breast lesions. Categorization according to BI-RADS enables radiologists to estimate the probability of breast cancer in breast abnormalities. However, no diagnostic classifications yet exist for dbPET as a new breast imaging tool. Currently, dbPET is performed for breast cancer screening, preoperative assessment, and evaluation of therapeutic effect in breast cancer medicine simultaneously with whole-body PET (4, 8). Especially in cancer screening, category classification of dbPET is required. Because dbPET is a functional imaging modality rather t...

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“…Kumar et al [ 20 ] showed a sensitivity of 23% for primary breast cancers sized ≤ 10 mm using WBPET. The sensitivity of dbPET for DCIS was reported to be 41–90%, higher than that with WBPET [ 9 , 13 , 21 ]. In this study, the dbPET detection rate for DCIS was 81.8%, which was comparable to that of previous reports.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, the areas near the chest wall tend to become blind areas. The limitation of FOV is attributed to the thickness of the breast and the location of the tumour on the patient’s side [ 21 , 32 ]. In this study, five tumours were undetected by dbPET, despite detected by WBPET/MRI.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic performance of dedicated breast positron emission tomography

et al. 2022

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Background Dedicated breast positron emission tomography (dbPET) has been developed for detecting smaller breast cancer. We investigated the diagnostic performance of dbPET in patients with known breast cancer. Methods Eighty-two preoperative patients with breast cancer were included in the study (84 tumours: 11 ductal carcinomas in situ [DCIS], 73 invasive cancers). They underwent mammography (MMG), ultrasonography (US), and contrast-enhanced breast magnetic resonance imaging (MRI) before whole-body PET/MRI (WBPET/MRI) and dbPET. We evaluated the sensitivity of all modalities, and the association between the maximum standard uptake value (SUVmax) level and histopathological features. Results The sensitivities of MMG, US, MRI, WBPET/MRI and dbPET for all tumours were 81.2% (65/80), 98.8% (83/84), 98.6% (73/74), 86.9% (73/84), and 89.2% (75/84), respectively. For 11 DCIS and 22 small invasive cancers (≤ 2 cm), the sensitivity of dbPET (84.9%) tended to be higher than that of WBPET/MRI (69.7%) (p = 0.095). Seven tumours were detected by dbPET only, but not by WBPET/MRI. Five tumours were detected by only WBPET/MRI because of the blind area of dbPET detector, requiring a wider field of view. After making the mat of dbPET detector thinner, all 22 scanned tumours were depicted. The higher SUVmax of dbPET was significantly related to the negative oestrogen receptor status, higher nuclear grade, and higher Ki67 (p < 0.001). Conclusions The sensitivity of dbPET for early breast cancer was higher than that of WBPET/MRI. High SUVmax was related to aggressive features of tumours. Moreover, dbPET can be used for the diagnosis and oncological evaluation of breast cancer.

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Which type of breast cancers is undetectable on ring-type dedicated breast PET?

Cited by 16 publications

References 12 publications

Analysis of the Mechanism of Breast Metastasis Based on Image Recognition and Ultrasound Diagnosis

Analysis of the Mechanism of Breast Metastasis Based on Image Recognition and Ultrasound Diagnosis

Classification of Abnormal Findings on Ring-type Dedicated Breast PET for the Detection of Breast Cancer

Diagnostic performance of dedicated breast positron emission tomography

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