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Acinic cell carcinoma is a rare malignant tumor that accounts for 2%-3% of salivary gland tumors. Acinic cell carcinoma arising from the breast is extremely rare, with only approximately 70 cases reported to date. Owing to its rarity, previous studies have primarily focused on pathological findings. Herein, we present the clinical and radiological features of acinic cell carcinoma of the breast in a 33-year-old woman.
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We conducted a phase I trial to determine the feasible dose for lapatinib, a dual HER2/EGFR tyrosine kinase inhibitor, with paclitaxel and gemcitabine as a neoadjuvant treatment in HER2 positive patients. In this phase I dose-escalation study, cohorts of 3-6 HER2-positive operable breast cancer patients received lapatinib (1,000 mg/day or 1,250 mg/day PO) with paclitaxel (80 mg/m(2)) and gemcitabine (1,000 or 1,200 mg/m(2)) on days 1 and 8 every 21 days to determine the tolerable dosages. Among 13 patients enrolled, 12 (stage III; n = 11: stage II; n = 1) completed treatment and one withdrew consent. The recommended doses were 1000-mg/day lapatinib, 80-mg/m(2) paclitaxel, and 1,000-mg/m(2) gemcitabine. One patient developed dose-limiting grade 3 hepatotoxicity; 3 experienced dose-limiting grade 4 neutropenia. No notable decline in left ventricle ejection fraction occurred. Eight patients achieved clinical partial response and four achieved clinical complete response (CR). Three patients (25%) achieved both tumor and nodal pathologic CR, 5 (42%) achieved tumor pathologic CR, and 6 (50%) underwent breast-conserving surgery. No relationship between lapatinib dose intensity and tumor response was apparent. Median follow-up was 16.2 (range, 6.5-20.7) months. Lapatinib plus paclitaxel and gemcitabine was tolerable with no overlapping toxicity.
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Protocolos de Quimioterapia Combinada Antineoplásica/administración & dosificación , Protocolos de Quimioterapia Combinada Antineoplásica/efectos adversos , Neoplasias de la Mama/tratamiento farmacológico , Receptor ErbB-2/biosíntesis , Adulto , Anciano , Neoplasias de la Mama/enzimología , Neoplasias de la Mama/genética , Neoplasias de la Mama/cirugía , Estudios de Cohortes , Desoxicitidina/administración & dosificación , Desoxicitidina/efectos adversos , Desoxicitidina/análogos & derivados , Relación Dosis-Respuesta a Droga , Femenino , Estudios de Seguimiento , Humanos , Lapatinib , Dosis Máxima Tolerada , Persona de Mediana Edad , Terapia Neoadyuvante/métodos , Paclitaxel/administración & dosificación , Paclitaxel/efectos adversos , Quinazolinas/administración & dosificación , Quinazolinas/efectos adversos , Receptor ErbB-2/antagonistas & inhibidores , GemcitabinaRESUMEN
Image compression is used in several clinical organizations to help address the overhead associated with medical imaging. These methods reduce file size by using a compact representation of the original image. This study aimed to analyze the impact of image compression on the performance of deep learning-based models in classifying mammograms as "malignant"-cases that lead to a cancer diagnosis and treatment-or "normal" and "benign," non-malignant cases that do not require immediate medical intervention. In this retrospective study, 9111 unique mammograms-5672 normal, 1686 benign, and 1754 malignant cases were collected from the National Cancer Center in the Republic of Korea. Image compression was applied to mammograms with compression ratios (CRs) ranging from 15 to 11 K. Convolutional neural networks (CNNs) with three convolutional layers and three fully-connected layers were trained using these images to classify a mammogram as malignant or not malignant across a range of CRs using five-fold cross-validation. Models trained on images with maximum CRs of 5 K had an average area under the receiver operating characteristic curve (AUROC) of 0.87 and area under the precision-recall curve (AUPRC) of 0.75 across the five folds and compression ratios. For images compressed with CRs of 10 K and 11 K, model performance decreased (average 0.79 in AUROC and 0.49 in AUPRC). Upon generating saliency maps that visualize the areas each model views as significant for prediction, models trained on less compressed (CR < = 5 K) images had maps encapsulating a radiologist's label, while models trained on images with higher amounts of compression had maps that missed the ground truth completely. In addition, base ResNet18 models pre-trained on ImageNet and trained using compressed mammograms did not show performance improvements over our CNN model, with AUROC and AUPRC values ranging from 0.77 to 0.87 and 0.52 to 0.71 respectively when trained and tested on images with maximum CRs of 5 K. This paper finds that while training models on images with increased the robustness of the models when tested on compressed data, moderate image compression did not substantially impact the classification performance of DL-based models.
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Compresión de Datos , Aprendizaje Profundo , Procesamiento de Imagen Asistido por Computador , Mamografía/clasificación , Adulto , Anciano , Anciano de 80 o más Años , Humanos , Persona de Mediana Edad , Modelos Teóricos , Redes Neurales de la Computación , Curva ROCRESUMEN
We investigated magnetic resonance imaging (MRI) criteria identifying residual tumours in patients with triple-negative and human epidermal growth factor receptor type 2-positive (HER2+) breast cancer following neoadjuvant chemotherapy. Retrospectively, 290 patients were included who had undergone neoadjuvant chemotherapy and definitive surgery. Clinicopathological features, as well as lesion size and lesion-to-background parenchymal signal enhancement ratio (SER) in early- and late-phase MRIs, were analysed. Receiver operating characteristic (ROC) analyses evaluated diagnostic performances. Maximal MRI values showing over 90% sensitivity and negative predictive value (NPV) were set as cut-off points. Identified MRI criteria were prospectively applied to 13 patients with hormone receptor-negative (HR-) tumours. The lesion size in HR-HER2-tumours had the highest area under the ROC curve value (0.92), whereas this parameter in HR + HER2 + tumours was generally low (≤ 0.75). For HR-tumours, both sensitivity and NPV exceeded the 90% threshold for early size > 0.2 cm (HR-HER2-) or > 0.1 cm (HR-HER2 +), late size > 0.4 cm, and early SER > 1.3. In the prospective pilot cohort, the criteria size and early SER did not find false negative cases, but one case was false negative with late SER. Distinguishing residual tumours based on MRI is feasible in selected triple-negative and HER2 + breast cancer patients.
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Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Neoplasias de la Mama/tratamiento farmacológico , Carcinoma Ductal de Mama/tratamiento farmacológico , Quimioterapia Adyuvante/métodos , Imagen por Resonancia Magnética/métodos , Terapia Neoadyuvante/métodos , Neoplasia Residual/diagnóstico , Biomarcadores de Tumor/análisis , Neoplasias de la Mama/patología , Carcinoma Ductal de Mama/patología , Femenino , Estudios de Seguimiento , Humanos , Persona de Mediana Edad , Proyectos Piloto , Pronóstico , Estudios Prospectivos , Curva ROC , Estudios RetrospectivosRESUMEN
Adipocytes are active sources of numerous adipokines that work in both a paracrine and endocrine manner. It is not known that the direct contact between tumor and neighboring fat measured by pretreatment breast magnetic resonance imaging (MRI) affects treatment outcomes to neoadjuvant chemotherapy (NAC) in breast cancer patients. A biomarker quantifying the tumor-fat interface volume from pretreatment MRI was proposed and used to predict pathologic complete response (pCR) in breast cancer patients treated with NAC. The tumor-fat interface volume was computed with data-driven clustering using multiphasic MRI. Our approach was developed and validated in two cohorts consisting of 1140 patients. A high tumor-fat interface volume was significantly associated with a non-pCR in both the development and validation cohorts (p = 0.030 and p = 0.037, respectively). Quantitative measurement of the tumor-fat interface volume based on pretreatment MRI may be useful for precision medicine and subsequently influence the treatment strategy of patients.
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PURPOSE: To investigate the diagnostic performance of magnetic resonance imaging (MRI) for predicting pathologic complete response after neoadjuvant chemotherapy (NAC) depending on subtypes of breast cancer using different interpretation thresholds of MRI negativity. PATIENTS AND METHODS: A total of 353 women with breast cancer who had undergone NAC were included. Pathologic examination after complete surgical excision was the reference standard. Tumors were divided into 4 subtypes on the basis of expression of hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2). Tumor enhancement was assessed on early and late phases of MRI. MRI negativity was divided into radiologic complete response (rCR, complete absence of enhancement on both early and late phases) and near-rCR (no discernible early enhancement but observed late enhancement). RESULTS: Ninety (25.5%) of 353 patients experienced pathologic complete response. When analyzing the data of all patients, sensitivity of MRI was higher for rCR versus near-rCR (97.72% vs. 90.49%, P < .0001), whereas specificity was lower for rCR versus near-rCR (44.44% vs. 72.22%, P < .0001). Accuracy was equivalent (84.14% vs. 85.84%). In HR-HER2+ tumors, 100% sensitivity and negative predictive value were achieved by assessing early enhancement only. In HR+HER2- tumors, sensitivity of MRI was higher for rCR versus near-rCR (96.12% vs. 86.82%, P = .0005). CONCLUSION: Diagnostic performance of MRI after NAC differs in accordance with the subtypes and threshold of MRI negativity. MRI assessment with consideration of tumor subtypes is required, along with standardization of MRI interpretation criteria in the NAC setting.
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Protocolos de Quimioterapia Combinada Antineoplásica/uso terapéutico , Biomarcadores de Tumor/metabolismo , Neoplasias de la Mama/patología , Carcinoma Ductal de Mama/patología , Imagen por Resonancia Magnética/métodos , Terapia Neoadyuvante/métodos , Neoplasia Residual/patología , Adolescente , Adulto , Anciano , Neoplasias de la Mama/clasificación , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/metabolismo , Carcinoma Ductal de Mama/clasificación , Carcinoma Ductal de Mama/tratamiento farmacológico , Carcinoma Ductal de Mama/metabolismo , Quimioterapia Adyuvante , Femenino , Estudios de Seguimiento , Humanos , Persona de Mediana Edad , Neoplasia Residual/tratamiento farmacológico , Neoplasia Residual/metabolismo , Pronóstico , Receptor ErbB-2/metabolismo , Receptores de Estrógenos/metabolismo , Receptores de Progesterona/metabolismo , Estudios Retrospectivos , Adulto JovenRESUMEN
PURPOSE: This retrospective study investigated if the initially assigned category 4A or 3 in concordant benign lesions, after ultrasound (US)-guided core needle biopsy, could affect follow-up compliance. METHODS: Eight hundred thirty-eight concordant benign lesions, after core needle biopsy (674, initial category 4A group and 164, category 3 group) and follow-up US, were included in our study. If an immediate surgical excision-a surgical excision before the next follow-up-exists, those cases with pathologic reports were collected. Statistical comparisons for the result of follow-up US compliance, additional biopsy, and malignant rates among 6-month, 12-month, and long-term intervals were performed by using the chi-square test. The log-rank test was used to compare compliance rates in the timing of first follow-up between the two groups, with a significance level of 0.05. RESULTS: The number of immediate surgical excision was higher in the category 4A group (11.1%) than in the category 3 group (6.1%); only one cancer was found in the category 4A group. The patients' compliance rate in a 6-month follow-up showed an increase (p=0.003) in the category 4A group. The additional biopsy rate was higher in the initial category 4A group (10.9%) than in the category 3 group (1.9%) with statistical significance (p=0.001); four cancers were found on additional biopsy in the category 4 group. No cancer was detected in the initial category 3 group, both on immediate surgical excision and follow-up. CONCLUSION: The initial category 4A or 3 of the Breast Imaging Reporting and Data System could be a significant factor that affects immediate surgical excision and follow-up compliance. Cancers were detected only in the initial category 4A group of concordant benign lesions. More attention should be paid to the concordant benign lesions from the initial category 4A group than from the category 3 group.
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[This corrects the article on p. 304 in vol. 20, PMID: 28970857.].
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OBJECTIVE: To evaluate the associations between intravoxel incoherent motion (IVIM)-derived parameters and histopathological features and subtypes of breast cancer. METHODS: Pre-operative MRI from 275 patients with unilateral breast cancer was analyzed. The apparent diffusion coefficient (ADC) and IVIM parameters [tissue diffusion coefficient (Dt), perfusion fraction (fp) and pseudodiffusion coefficient] were obtained from cancer and normal tissue using diffusion-weighted imaging with b-values of 0, 30, 70, 100, 150, 200, 300, 400, 500 and 800 s mm(-2). We then compared the IVIM parameters of tumours with different histopathological features and subtypes. RESULTS: The ADC and Dt were lower and fp was higher in cancers than in normal tissues (p < 0.001). The Dt was lower in high Ki-67 cancer than in low Ki-67 cancer (p = 0.019), whereas ADC showed no significant difference (p = 0.309). Luminal B [human epidermal growth factor receptor 2 (HER2)-negative] cancer showed lower ADC (p = 0.003) and Dt (p = 0.001) than other types. CONCLUSION: We found low tissue diffusivity in high Ki-67 cancer and luminal B (HER2-negative) cancer using IVIM imaging. ADVANCES IN KNOWLEDGE: Low tissue diffusivity is more clearly shown in high Ki-67 tumours and luminal B (HER2-negative) tumours with the IVIM model.