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Cancer Imaging
Scopus
ISSN 1470-7330 · BMC · 981 artikel di indeks
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Artikel Jurnal
NI-RADS in posttreatment head and neck cancer surveillance: a framework for standardized imaging with clinical impact
Abstract The Neck Imaging Reporting and Data System (NI-RADS), developed through the American College of Radiology (ACR), provides a standardized framework for interpreting and managing posttreatment imaging in head and neck cancer. Building upon the success of NI-RADS PET/CT, the recently released…
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Artikel Jurnal
CT characteristics of solitary pulmonary capillary hemangioma versus lung adenocarcinoma
Abstract Background Solitary pulmonary capillary hemangioma is an underrecognized rare benign disease that can radiologically mimic lung adenocarcinoma. This study aims to demonstrate radiologic features of SPCH and compare characteristics between SPCH and lung adenocarcinoma. Materials and methods…
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Artikel Jurnal
Contrast-enhanced mammography based quantitative and qualitative feature analysis across different breast cancer molecular subtypes
Abstract Objective To investigate the imaging manifestations of different molecular subtypes of breast cancer (BC) by contrast enhanced mammography (CEM). Methods From April 2019 to January 2022, 183 BC patients with suspected malignant mass underwent CEM examination were included. The differences…
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Artikel Jurnal
Prediction of lymph node metastasis and recurrence risk in early-stage oral tongue squamous cell carcinoma with fully automated MRI deep learning
Abstract Background This study aimed to develop and validate a fully automated magnetic resonance imaging (MRI) deep learning (DL) framework for primary tumor detection and prediction of lymph node metastasis (LNM) in early-stage OTSCC. Methods A total of 348 patients from two centers were…
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Artikel Jurnal
Development and validation of MRI-based models to predict lymph node metastasis in bladder cancer: a multi-center study
Abstract Background Accurate preoperative evaluation of lymph node (LN) status is crucial for guiding precise treatment. Although several methods have been developed for preoperative evaluation of LN status, accurate evaluation remains a challenge. Objective To develop and validate MRI-based…
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Artikel Jurnal
Contrast-enhanced ultrasound quantitative parameters for predicting benign and malignant greater omentum lesions: an applied study
Abstract Objective To explore the value of contrast-enhanced ultrasound (CEUS) quantitative parameters in differentiating benign and malignant diseases of the greater omentum and to establish a new CEUS Greater Omentum Imaging Reporting and Data System (CEUS-GOIRADS). Methods We analyzed 15 CEUS…
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Artikel Jurnal
Prediction of pathological complete response to neoadjuvant therapy in breast cancer using deep learning with multi-modal radiological image and biopsy whole slide images: a two-center study
Abstract Background To develop a predictive model utilizing deep learning by mammography (MG), ultrasound (US), magnetic resonance imaging (MRI), and biopsy whole-slide images (WSI) to evaluate pathological complete response (pCR) of primary lesion after neoadjuvant therapy (NAT) in breast cancer…
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Artikel Jurnal
Impact of MMR status on preoperative CT-based lymph node overstaging in right-sided colon cancer: a retrospective analysis
Abstract Background Neoadjuvant treatment for colon cancer has recently gained more and more attention. Given the imprecision of radiologic staging, low-risk patients may be exposed to the toxicities and inconvenience of chemotherapy when surgery alone might have been considered sufficient…
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Artikel Jurnal
A novel interpretable machine learning framework integrating clinicopathological and radiomic features for early recurrence prediction in mass-forming intrahepatic cholangiocarcinoma
Abstract Rationale and objectives Early recurrence after curative resection remains a major determinant of poor prognosis in intrahepatic cholangiocarcinoma (ICC). Existing multimodal prediction models often lack interpretability due to feature interference during fusion. This study aimed to…
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Artikel Jurnal
MRI-based patient selection for active surveillance in prostate cancer using U-Found: a generalized deep learning model
Abstract Background Current MRI prostate cancer risk assessment methods focus mainly on detecting tumor lesions, ignoring the prostate gland macro-environment which may also impact disease progression. A generalized deep-learning model for prostate may help capture these gland-level characteristics…
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Artikel Jurnal
Pretreatment MRI radiomics for predicting pathological Miller-Payne grading in breast cancer following neoadjuvant chemotherapy
Abstract Background Breast cancer’s personalized management requires better risk stratification. Recent studies focus on differentiating the pathological complete response (pCR) from non-pCR, which lacks accuracy in prognostic prediction and therapy guidance for most non-pCR patients. We aimed to…
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Artikel Jurnal
The significance of small lymph nodes on CT for advanced poorly cohesive gastric carcinoma
Abstract Objective This study aims to assess the size of metastatic lymph nodes (LNs) in advanced poorly cohesive gastric carcinoma (PC-GC) on pre-operative CT and to evaluate potential differences based on histological types. Methods We included advanced gastric cancer patients who underwent…
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Artikel Jurnal
Prognostic features of biochemical recurrence of prostate cancer following radical prostatectomy based on diffusion kurtosis imaging
Abstract Objectives To evaluate characteristics of diffusion kurtosis imaging (DKI), baseline prostate-specific antigen (PSA) and postoperative histopathological findings associated with biochemical recurrence (BCR) of prostate cancer (PCa) after radical prostatectomy (RP). Materials & Methods…
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Artikel Jurnal
Human–AI interaction in a cancer-enriched double-reading breast screening cohort: diagnostic accuracy and second-reader behavior
Abstract Rationale and objectives To evaluate the impact of deploying AI as the first reader (R1) in a double-reading breast-screening workflow and to characterize second-reader (R2) behavior—including the effect of disclosing whether R1 was AI or human. Materials and methods This retrospective…
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Artikel Jurnal
Dual-layer spectral detector computed tomography multiparameter machine learning model for prediction of lymph node metastases in esophageal squamous cell carcinoma
Abstract Objective Accurate assessment of lymph node metastasis (LNM) is essential for the staging, treatment, and prognosis of esophageal squamous cell carcinoma (ESCC). This study investigates the potential of dual-layer spectral detector computed tomography (SDCT) quantitative parameters in…
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Artikel Jurnal
When PSMA is not enough: the diagnostic blind spots of PSMA PET/CT and the added value of [¹⁸F]FDG in high-risk prostate cancer: dual-tracer cohort study
Abstract Purpose PSMA PET/CT has transformed prostate cancer management, yet its diagnostic utility is not absolute. It fails to detect PSMA-suppressed disease variants, including treatment-induced neuroendocrine prostate cancer (t-NEPC) and dedifferentiated tumors, and is inherently blind to…
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Artikel Jurnal
Dynamic nomogram for predicting axillary lymph node metastasis in breast cancer based on MRI analysis and the platelet-to-lymphocyte ratio (PLR)
Abstract Background This study aimed to develop a dynamic nomogram in which clinical indicators are integrated with magnetic resonance imaging (MRI) radiomics to predict axillary lymph node metastasis (ALNM) in patients with breast cancer. Methods Our retrospective study included 221 pathologically…
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Artikel Jurnal
Survival prediction of 18F-FDG PET/CT in pediatric patients with recurrent neuroblastoma
Abstract Purpose Our study aims to investigate the predictive potential of FDG PET/CT in pediatric patients with NB at the time of recurrence. Methods Pediatric patients with suspected recurrence of NB underwent FDG PET/CT were included in this retrospective study. The clinicopathological data, PET…
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Artikel Jurnal
Evaluation of audiovisual and auditory interventions on exam anxiety during whole-body magnetic resonance imaging in cancer patients: a quasi-experimental study
Abstract Background WB-MRI is a radiation-free imaging technique widely used in oncology. Despite clinical advantages, WB-MRI can cause significant patient anxiety and claustrophobia, affecting scan completion and patient adherence. Non-invasive interventions to reduce MRI-related distress are…