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1.
Cureus ; 16(6): e61521, 2024 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-38957233

RESUMEN

Reports of mammary Paget's disease (MPD) as a manifestation of breast cancer recurrence are rare. MPD presents a particular challenge when emerging more than two decades after a breast cancer treated with evidence-based therapy. There is a broad spectrum of non-malignant causes for dermatitis of the nipple during the initial presentation that may delay cancer work-up. This case highlights the MPD work-up and management in the context of a personal history of breast cancer. This unique clinical presentation emphasizes the importance of vigilant cancer surveillance for timely intervention, especially for a presumed cured cancer.

2.
J Neurooncol ; 168(2): 307-316, 2024 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-38689115

RESUMEN

OBJECTIVE: Radiation necrosis (RN) can be difficult to radiographically discern from tumor progression after stereotactic radiosurgery (SRS). The objective of this study was to investigate the utility of radiomics and machine learning (ML) to differentiate RN from recurrence in patients with brain metastases treated with SRS. METHODS: Patients with brain metastases treated with SRS who developed either RN or tumor reccurence were retrospectively identified. Image preprocessing and radiomic feature extraction were performed using ANTsPy and PyRadiomics, yielding 105 features from MRI T1-weighted post-contrast (T1c), T2, and fluid-attenuated inversion recovery (FLAIR) images. Univariate analysis assessed significance of individual features. Multivariable analysis employed various classifiers on features identified as most discriminative through feature selection. ML models were evaluated through cross-validation, selecting the best model based on area under the receiver operating characteristic (ROC) curve (AUC). Specificity, sensitivity, and F1 score were computed. RESULTS: Sixty-six lesions from 55 patients were identified. On univariate analysis, 27 features from the T1c sequence were statistically significant, while no features were significant from the T2 or FLAIR sequences. For clinical variables, only immunotherapy use after SRS was significant. Multivariable analysis of features from the T1c sequence yielded an AUC of 76.2% (standard deviation [SD] ± 12.7%), with specificity and sensitivity of 75.5% (± 13.4%) and 62.3% (± 19.6%) in differentiating radionecrosis from recurrence. CONCLUSIONS: Radiomics with ML may assist the diagnostic ability of distinguishing RN from tumor recurrence after SRS. Further work is needed to validate this in a larger multi-institutional cohort and prospectively evaluate it's utility in patient care.


Asunto(s)
Neoplasias Encefálicas , Aprendizaje Automático , Imagen por Resonancia Magnética , Necrosis , Recurrencia Local de Neoplasia , Traumatismos por Radiación , Humanos , Neoplasias Encefálicas/secundario , Neoplasias Encefálicas/radioterapia , Neoplasias Encefálicas/diagnóstico por imagen , Femenino , Masculino , Traumatismos por Radiación/diagnóstico por imagen , Traumatismos por Radiación/etiología , Traumatismos por Radiación/patología , Persona de Mediana Edad , Necrosis/diagnóstico por imagen , Recurrencia Local de Neoplasia/diagnóstico por imagen , Recurrencia Local de Neoplasia/patología , Estudios Retrospectivos , Imagen por Resonancia Magnética/métodos , Anciano , Radiocirugia , Adulto , Diagnóstico Diferencial , Anciano de 80 o más Años , Radiómica
3.
Am Soc Clin Oncol Educ Book ; 44: e430152, 2024 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-38190577

RESUMEN

Oligometastatic state is believed to potentially represent a transitional stage between early, locoregional state disease and widely metastatic disease. Historically, locoregional approaches, particularly in advanced colorectal cancers, have demonstrated efficacy in select patients with limited burden of metastatic disease. Recent strides in systemic therapies, including biomarker-based treatments and immunotherapy, alongside innovations in surgical techniques and novel locoregional approaches such as stereotactic radiotherapy and ablation, have ushered in a new era of therapeutic possibilities across all oligometastatic GI cancers. Despite these advancements, there remains a significant gap in high-quality prospective evidence guiding patient selection and treatment decisions across various disease types. Ongoing clinical trials are anticipated to provide crucial insights into oligometastatic states, fostering the refinement of disease-specific oligometastatic state definitions and treatment algorithms. This article reviews existing data on the management of oligometastatic GI cancer, summarizes current state of knowledge for each disease state, and provides updates on ongoing studies in this space.


Asunto(s)
Neoplasias Colorrectales , Neoplasias Gastrointestinales , Neoplasias Primarias Secundarias , Humanos , Estudios Prospectivos , Neoplasias Gastrointestinales/diagnóstico , Neoplasias Gastrointestinales/terapia , Inmunoterapia , Algoritmos
4.
Cancers (Basel) ; 15(18)2023 Sep 19.
Artículo en Inglés | MEDLINE | ID: mdl-37760604

RESUMEN

Recent clinical research describes a subset of glioblastoma patients that exhibit REP prior to the start of radiation therapy. Current literature has thus far described this population using clinicopathologic features. To our knowledge, this study is the first to investigate the potential of conventional radiomics, sophisticated multi-resolution fractal texture features, and different molecular features (MGMT, IDH mutations) as a diagnostic and prognostic tool for prediction of REP from non-REP cases using computational and statistical modeling methods. The radiation-planning T1 post-contrast (T1C) MRI sequences of 70 patients are analyzed. An ensemble method with 5-fold cross-validation over 1000 iterations offers an AUC of 0.793 ± 0.082 for REP versus non-REP classification. In addition, copula-based modeling under dependent censoring (where a subset of the patients may not be followed up with until death) identifies significant features (p-value < 0.05) for survival probability and prognostic grouping of patient cases. The prediction of survival for the patients' cohort produces a precision of 0.881 ± 0.056. The prognostic index (PI) calculated using the fused features shows that 84.62% of REP cases fall under the bad prognostic group, suggesting the potential of fused features for predicting a higher percentage of REP cases. The experimental results further show that multi-resolution fractal texture features perform better than conventional radiomics features for prediction of REP and survival outcomes.

5.
Cureus ; 14(5): e24913, 2022 May.
Artículo en Inglés | MEDLINE | ID: mdl-35698712

RESUMEN

Paraneoplastic syndromes (PNS) are rare and can be challenging to diagnose and treat. The uniqueness of PNS lies in the complexity of presentation, the importance of early diagnosis, and the role of multidisciplinary care in managing those patients to mitigate long-term neurologic complications. We describe a patient with metastatic renal cell carcinoma who presented with a complex constellation of neurological symptoms (progressive global ataxia and sensory changes) that did not resolve following nephrectomy. While complete resolution of symptoms was not achieved, he did have stabilization of his neurologic decline with the initiation of cancer-directed therapies.

6.
Breast Cancer Res ; 21(1): 80, 2019 07 17.
Artículo en Inglés | MEDLINE | ID: mdl-31315645

RESUMEN

BACKGROUND: A large collaborative analysis of data from 47 epidemiological studies concluded that longer duration of breastfeeding reduces the risk of developing breast cancer. Despite the strong epidemiological evidence, the molecular mechanisms linking prolonged breastfeeding to decreased risk of breast cancer remain poorly understood. METHODS: We modeled two types of breastfeeding behaviors in wild type FVB/N mice: (1) normal or gradual involution of breast tissue following prolonged breastfeeding and (2) forced or abrupt involution following short-term breastfeeding. To accomplish this, pups were gradually weaned between 28 and 31 days (gradual involution) or abruptly at 7 days postpartum (abrupt involution). Mammary glands were examined for histological changes, proliferation, and inflammatory markers by immunohistochemistry. Fluorescence-activated cell sorting was used to quantify mammary epithelial subpopulations. Gene set enrichment analysis was used to analyze gene expression data from mouse mammary luminal progenitor cells. Similar analysis was done using gene expression data generated from human breast samples obtained from parous women enrolled on a tissue collection study, OSU-2011C0094, and were undergoing reduction mammoplasty without history of breast cancer. RESULTS: Mammary glands from mice that underwent abrupt involution exhibited denser stroma, altered collagen composition, higher inflammation and proliferation, increased estrogen receptor α and progesterone receptor expression compared to those that underwent gradual involution. Importantly, when aged to 4 months postpartum, mice that were in the abrupt involution cohort developed ductal hyperplasia and squamous metaplasia. Abrupt involution also resulted in a significant expansion of the luminal progenitor cell compartment associated with enrichment of Notch and estrogen signaling pathway genes. Breast tissues obtained from healthy women who breastfed for < 6 months vs ≥ 6 months showed significant enrichment of Notch signaling pathway genes, along with a trend for enrichment for luminal progenitor gene signature similar to what is observed in BRCA1 mutation carriers and basal-like breast tumors. CONCLUSIONS: We report here for the first time that forced or abrupt involution of the mammary glands following pregnancy and lack of breastfeeding results in expansion of luminal progenitor cells, higher inflammation, proliferation, and ductal hyperplasia, a known risk factor for developing breast cancer.


Asunto(s)
Lactancia Materna , Neoplasias de la Mama/etiología , Neoplasias de la Mama/metabolismo , Estrógenos/metabolismo , Inflamación/complicaciones , Inflamación/metabolismo , Transducción de Señal , Animales , Biopsia , Neoplasias de la Mama/patología , Colágeno/metabolismo , Modelos Animales de Enfermedad , Susceptibilidad a Enfermedades , Células Epiteliales/metabolismo , Estrógenos/efectos adversos , Femenino , Citometría de Flujo , Perfilación de la Expresión Génica , Humanos , Hiperplasia , Inmunohistoquímica , Inflamación/patología , Lactancia , Ratones , Embarazo , Receptores de Estrógenos/metabolismo , Medición de Riesgo , Factores de Riesgo , Esteroides/metabolismo
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