Role of CT and MR in detection and staging of pancreatic adenocarcinoma

Francis, Isaac R.

doi:10.1102/1470-7330.2003.0026

Cited by 6 publications

(6 citation statements)

References 19 publications

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Section: Clinical Imaging Of Pancreatic Cancer: Current Strategiesmentioning

confidence: 99%

“…Currently, multisectional computed tomography (CT) is the most widely employed technique for assessing possible pancreatic disease, as this instrument offers high spatial resolution with moderately fast scan times . Newer multislice helical computerized tomography (CT) scanners have displayed superior detection and staging accuracy of pancreatic cancer, as compared to traditional CT imaging, with detection accuracies of 90–95% . The procedure for CT imaging of pancreatic cancer includes the use of oral water as a negative intraluminal contrast and intravenously injected iodinated contrast material.…”

Section: Clinical Imaging Of Pancreatic Cancer: Current Strategiesmentioning

confidence: 99%

“…180 Newer multislice helical computerized tomography (CT) scanners have displayed superior detection and staging accuracy of pancreatic cancer, as compared to traditional CT imaging, with detection accuracies of 90−95%. 181 The procedure for CT imaging of pancreatic cancer includes the use of oral water as a negative intraluminal contrast and intravenously injected iodinated contrast material. Ultrasonography (US) examination is another imaging modality commonly utilized for diagnosing pancreatic cancer, yet this method lacks the sensitivity and reliability needed for staging the disease.…”

Section: Clinical Imaging Of Pancreatic Cancer: Current Strategiesmentioning

confidence: 99%

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Molecular Imaging of Pancreatic Cancer with Antibodies

et al. 2015

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Development of novel imaging probes for cancer diagnostics remains critical for early detection of disease, yet most imaging agents are hindered by suboptimal tumor accumulation. To overcome these limitations, researchers have adapted antibodies for imaging purposes. As cancerous malignancies express atypical patterns of cell surface proteins in comparison to noncancerous tissues, novel antibody-based imaging agents can be constructed to target individual cancer cells or surrounding vasculature. Using molecular imaging techniques, these agents may be utilized for detection of malignancies and monitoring of therapeutic response. Currently, there are several imaging modalities commonly employed for molecular imaging. These imaging modalities include positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance (MR) imaging, optical imaging (fluorescence and bioluminescence), and photoacoustic (PA) imaging. While antibody-based imaging agents may be employed for a broad range of diseases, this review focuses on the molecular imaging of pancreatic cancer, as there are limited resources for imaging and treatment of pancreatic malignancies. Additionally, pancreatic cancer remains the most lethal cancer with an overall 5-year survival rate of approximately 7%, despite significant advances in the imaging and treatment of many other cancers. In this review, we discuss recent advances in molecular imaging of pancreatic cancer using antibody-based imaging agents. This task is accomplished by summarizing the current progress in each type of molecular imaging modality described above. Also, several considerations for designing and synthesizing novel antibody-based imaging agents are discussed. Lastly, the future directions of antibody-based imaging agents are discussed, emphasizing the potential applications for personalized medicine.

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Section: Clinical Imaging Of Pancreatic Cancer: Current Strategiesmentioning

confidence: 99%

Section: Clinical Imaging Of Pancreatic Cancer: Current Strategiesmentioning

confidence: 99%

Section: Clinical Imaging Of Pancreatic Cancer: Current Strategiesmentioning

confidence: 99%

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Molecular Imaging of Pancreatic Cancer with Antibodies

et al. 2015

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“…Cancer accounted for 8.2 million deaths worldwide in 2012, and, for some types of cancer, e.g., pancreatic adenocarcinoma (78.000 deaths in Europe in 2012), incidence equals mortality . Most pancreatic adenocarcinomas are still detected at a late stage, and 85% are unresectable at the time of detection . This is due, in part, to the lack of appropriate tools for early detection, accurate staging, and post-therapy monitoring.…”

Section: Introductionmentioning

confidence: 99%

“…3 Most pancreatic adenocarcinomas are still detected at a late stage, and 85% are unresectable at the time of detection. 4 This is due, in part, to the lack of appropriate tools for early detection, accurate staging, and post-therapy monitoring. The maturity of in vivo-minimally invasive imaging methods together with the development of novel nanomaterials-based imaging probes has posed a great expectation in the field of in vivo cancer detection and monitoring.…”

Section: ■ Introductionmentioning

confidence: 99%

Functional Single-Chain Polymer Nanoparticles: Targeting and Imaging Pancreatic Tumors in Vivo

et al. 2016

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The development of tools for the early diagnosis of pancreatic adenocarcinoma is an urgent need in order to increase treatment success rate and reduce patient mortality. Here, we present a modular nanosystem platform integrating soft nanoparticles with a targeting peptide and an active imaging agent for diagnostics. Biocompatible single-chain polymer nanoparticles (SCPNs) based on poly(methacrylic acid) were prepared and functionalized with the somatostatin analogue PTR86 as the targeting moiety, since somatostatin receptors are overexpressed in pancreatic cancer. The gamma emitter Ga was incorporated by chelation and allowed in vivo investigation of the pharmacokinetic properties of the nanoparticles using single photon emission computerized tomography (SPECT). The resulting engineered nanosystem was tested in a xenograph mouse model of human pancreatic adenocarcinoma. Imaging results demonstrate that accumulation of targeted SCPNs in the tumor is higher than that observed for nontargeted nanoparticles due to improved retention in this tissue.

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PanCanAID – Pancreas Cancer Artificial Intelligence Driven Diagnosis in CT Scan Imaging: A Protocol for a Multicentric Ambispective Diagnostic Study

Safavi-Naini,

Behnamnia,

Khorasanizadeh

et al. 2023

Preprint

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IntroductionPancreatic cancer is thought to have an extremely dismal prognosis. Most cancer-related deaths occur from metastasis rather than the primary tumor, although individuals with tumors smaller than 1 cm in diameter have more than 80% 5-year survival. Thus, the current protocol introduces PanCanAID project which intends to develop several computer-aided-diagnosis (CAD) systems to enhance pancreatic cancer diagnosis and management using CT scan imaging.Methods and analysisPatients with pathologically confirmed pancreatic ductal adenocarcinoma (PDAC) or pancreatic neuroendocrine tumor (PNET) will be included as pancreatic cancer cases. The controls will be patients without CT evidence of abdominal malignancy. A data bank of contrast-enhanced abdominopelvic CT scans, survival data, and demographics will be collected from ten medical centers in four provinces. Endosonography images and clinical data, if available, will be added to the data bank. Annotation and manual segmentation will be handled by radiologists and confirmed by a second expert radiologist in abdominal imaging. PanCanAID intelligent system is designed to (1) detect abdominopelvic CT scan phase, (2) segment pancreas organ, (3) diagnose pancreatic cancer and its subtype in arterial phase CT scan, (4) diagnose pancreatic cancer and its subtype in non-contrast CT scan, (5) carry out prognosis (TNM stage and survival) based on arterial phase CT scan, (6) and estimate tumor resectability. A domain adaptation step will be handled to use online data and provide pancreas organ segmentation to reduce the segmentation time. After data collection, a state-of-the-art deep learning algorithm will be developed for each task and benchmarked against rival models.ConclusionPanCanAID is a large-scale, multidisciplinary AI project to assist clinicians in diagnosing and managing pancreas cancer. Here, we present the PanCanAID protocol to assure the quality and replicability of our models. In our experience, the effort to prepare a detailed protocol facilitates a positive interdisciplinary culture and the preemptive identification of errors before they occur.

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Role of CT and MR in detection and staging of pancreatic adenocarcinoma

Abstract: In this review article, the roles of imaging with CT and MRI in the detection and staging of pancreatic carcinoma will be discussed. The frequently employed techniques using these modalities, the common imaging appearances of this tumor, and the limitations of imaging will be addressed.

Cited by 6 publications

References 19 publications

Molecular Imaging of Pancreatic Cancer with Antibodies

Molecular Imaging of Pancreatic Cancer with Antibodies

Functional Single-Chain Polymer Nanoparticles: Targeting and Imaging Pancreatic Tumors in Vivo

PanCanAID – Pancreas Cancer Artificial Intelligence Driven Diagnosis in CT Scan Imaging: A Protocol for a Multicentric Ambispective Diagnostic Study

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