The Pharmacological Management of Skeletal-Related Events From Metastatic Tumors

Hitron, Anna; Adams, Val R.

doi:10.3928/01477447-20090301-13

Cited by 13 publications

(11 citation statements)

References 25 publications

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“…Bone metastases affect approximately 400 000 patients per year in the United States (8). Breast and prostate cancer together are thought to account for more than 80% of these bone metastases (9).…”

Section: Patient Populationmentioning

confidence: 99%

“…Informed consent was waived, as the study was conducted as a retrospective analysis of scans from examinations performed as part of prior clinical care. An automated search of our institution's radiology information system database (RadNet; Cerner Millennium, North Kansas City, Mo) was performed frequent and often debilitating, with secondary skeletal complications (skeletal related events) occurring in approximately 50% of patients (8). Overall, the spine is the most frequent location for skeletal metastases (17).…”

Section: Patient Populationmentioning

confidence: 99%

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Automated Detection of Sclerotic Metastases in the Thoracolumbar Spine at CT

Burns

Yao²,

Wiese³

et al. 2013

Radiology

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Purpose:To design and validate a computer system for automated detection and quantitative characterization of sclerotic metastases of the thoracolumbar spine on computed tomography (CT) images. Materials and Methods:This retrospective study was approved by the institutional review board and was HIPAA compliant; informed consent was waived. The data set consisted of CT examinations in 49 patients (14 female, 35 male patients; mean age, 57.0 years; range, 12-77 years), demonstrating a total of 532 sclerotic lesions of the spine of greater than 0.3 cm 3 in volume, and in 10 control case patients (four women, six men; mean age, 55.2 years; range, 19-70 years) without spinal lesions. CT examinations were divided into training and test sets, and images were analyzed according to prototypical fully-automated computer-aided detection (CAD) software. Free-response receiver operating characteristic analysis was performed. Results:Lesion detection sensitivity on images in the training set was 90%, relative to reference-standard marked lesions (95% confidence interval [CI]: 83%, 97%), at a false-positive rate (FPR) of 10.8 per patient (95% CI: 6.6, 15.0). For images in the testing set, sensitivity was 79% (95% CI: 74%, 84%), with an FPR of 10.9 per patient (95% CI: 8.5, 13.3). Conclusion:This CAD system successfully identified and segmented sclerotic lesions in the thoracolumbar spine.q RSNA, 2013

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Section: Patient Populationmentioning

confidence: 99%

Section: Patient Populationmentioning

confidence: 99%

Automated Detection of Sclerotic Metastases in the Thoracolumbar Spine at CT

Burns

Yao²,

Wiese³

et al. 2013

Radiology

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“…Acetaminophen is preferred in patients with thrombocytopenia, renal dysfunction, those receiving nephrotoxic agents, and those at risk for gastrointestinal bleeding. In patients with liver dysfunction, NSAIDs are preferred for mild pain (Hitron & Adams, 2009) In patients who need the next level of treatment for their low back pain, opioid therapy should be added. Common protocols begin with low doses of immediate-release shortacting agents (i.e.…”

Section: Medical Management Of Painmentioning

confidence: 99%

“…Adjunct agents such as anticonvulsants (e.g., gabapentin, lamotrigine, topiramate), tricyclic antidepressants (e.g., amitriptyline, imipramine, desipramine, nortriptyline), venlafaxine, duloxetine, or topical analgesics (e.g., lidocaine or capsaicin) may also help to reduce neuropathic pain caused by nerve compression (Hitron & Adams, 2009). …”

Section: Medical Management Of Painmentioning

confidence: 99%

Evaluation and Management of Lower Back Pain in Oncological Patients

Schroeder¹,

Barzilay²,

Hasharoni³

et al. 2012

Low Back Pain Pathogenesis and Treatment

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“…Their detection can assess the staging of the patient's disease, and therefore has the potential to alter the treatment regimen the patient will undergo [1]. Approximately 490,000 patients per year are affected by metastatic diseases of the skeletal structures in the United States alone [2]. More than 80 % of these bone metastases are thought to originate from breast and prostate cancer [3].…”

Section: Introductionmentioning

confidence: 99%

Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications

Roth

Yao

Lü

et al. 2015

Lecture Notes in Computational Vision and Biomechanics

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Automated detection of sclerotic metastases (bone lesions) in Computed Tomography (CT) images has potential to be an important tool in clinical practice and research. State-of-the-art methods show performance of 79 % sensitivity or truepositive (TP) rate, at 10 false-positives (FP) per volume. We design a two-tiered coarse-to-fine cascade framework to first operate a highly sensitive candidate generation system at a maximum sensitivity of ∼92 % but with high FP level (∼50 per patient). Regions of interest (ROI) for lesion candidates are generated in this step and function as input for the second tier. In the second tier we generate N 2D views, via scale, random translations, and rotations with respect to each ROI centroid coordinates. These random views are used to train a deep Convolutional Neural Network (CNN) classifier. In testing, the CNN is employed to assign individual probabilities for a new set of N random views that are averaged at each ROI to compute a final per-candidate classification probability. This second tier behaves as a highly selective process to reject difficult false positives while preserving high sensitivities. We validate the approach on CT images of 59 patients (49 with sclerotic metastases and 10 normal controls). The proposed method reduces the number of FP/vol. from 4 to 1.2, 7 to 3, and 12 to 9.5 when comparing a sensitivity rates of 60, 70, and 80 % respectively in testing. The Area-Under-the-Curve (AUC) is 0.834. The results show marked improvement upon previous work.

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The Pharmacological Management of Skeletal-Related Events From Metastatic Tumors

Cited by 13 publications

References 25 publications

Automated Detection of Sclerotic Metastases in the Thoracolumbar Spine at CT

Automated Detection of Sclerotic Metastases in the Thoracolumbar Spine at CT

Evaluation and Management of Lower Back Pain in Oncological Patients

Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications

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