OncoLog Volume 51, Number 11, November 2006

Treating Skull Base Tumors Targeting Inflammatory Breast Cancer House Call: On the Job with Cancer DiaLog: Helical CT Screening: Does It Affect Lung Cancer Outcome? by Reginald F. Munden, MD, Professor, Department of Diagnostic Radiologyhttps://openworks.mdanderson.org/oncolog/1186/thumbnail.jp

Amplitude-modulated electromagnetic fields for the treatment of cancer: Discovery of tumor-specific frequencies and assessment of a novel therapeutic approach

<p>Abstract</p> <p>Purpose</p> <p>Because <it>in vitro </it>studies suggest that low levels of electromagnetic fields may modify cancer cell growth, we hypothesized that systemic delivery of a combination of tumor-specific frequencies may have a therapeutic effect. We undertook this study to identify tumor-specific frequencies and test the feasibility of administering such frequencies to patients with advanced cancer.</p> <p>Patients and methods</p> <p>We examined patients with various types of cancer using a noninvasive biofeedback method to identify tumor-specific frequencies. We offered compassionate treatment to some patients with advanced cancer and limited therapeutic options.</p> <p>Results</p> <p>We examined a total of 163 patients with a diagnosis of cancer and identified a total of 1524 frequencies ranging from 0.1 Hz to 114 kHz. Most frequencies (57–92%) were specific for a single tumor type. Compassionate treatment with tumor-specific frequencies was offered to 28 patients. Three patients experienced grade 1 fatigue during or immediately after treatment. There were no NCI grade 2, 3 or 4 toxicities. Thirteen patients were evaluable for response. One patient with hormone-refractory breast cancer metastatic to the adrenal gland and bones had a complete response lasting 11 months. One patient with hormone-refractory breast cancer metastatic to liver and bones had a partial response lasting 13.5 months. Four patients had stable disease lasting for +34.1 months (thyroid cancer metastatic to lung), 5.1 months (non-small cell lung cancer), 4.1 months (pancreatic cancer metastatic to liver) and 4.0 months (leiomyosarcoma metastatic to liver).</p> <p>Conclusion</p> <p>Cancer-related frequencies appear to be tumor-specific and treatment with tumor-specific frequencies is feasible, well tolerated and may have biological efficacy in patients with advanced cancer.</p> <p>Trial registration</p> <p>clinicaltrials.gov identifier NCT00805337</p

Artificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CT

Background: Limited data are available regarding whether computer-aided diagnosis (CAD) improves assessment of malignancy risk in indeterminate pulmonary nodules (IPNs). Purpose: To evaluate the effect of an artificial intelligence-based CAD tool on clinician IPN diagnostic performance and agreement for both malignancy risk categories and management recommendations. Materials and Methods: This was a retrospective multireader multicase study performed in June and July 2020 on chest CT studies of IPNs. Readers used only CT imaging data and provided an estimate of malignancy risk and a management recommendation for each case without and with CAD. The effect of CAD on average reader diagnostic performance was assessed using the Obuchowski-Rockette and Dorfman-Berbaum-Metz method to calculate estimates of area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Multirater Fleiss κ statistics were used to measure interobserver agreement for malignancy risk and management recommendations. Results: A total of 300 chest CT scans of IPNs with maximal diameters of 5-30 mm (50.0% malignant) were reviewed by 12 readers (six radiologists, six pulmonologists) (patient median age, 65 years; IQR, 59-71 years; 164 [55%] men). Readers\u27 average AUC improved from 0.82 to 0.89 with CAD (P \u3c .001). At malignancy risk thresholds of 5% and 65%, use of CAD improved average sensitivity from 94.1% to 97.9% (P = .01) and from 52.6% to 63.1% (P \u3c .001), respectively. Average reader specificity improved from 37.4% to 42.3% (P = .03) and from 87.3% to 89.9% (P = .05), respectively. Reader interobserver agreement improved with CAD for both the less than 5% (Fleiss κ, 0.50 vs 0.71; P \u3c .001) and more than 65% (Fleiss κ, 0.54 vs 0.71; P \u3c .001) malignancy risk categories. Overall reader interobserver agreement for management recommendation categories (no action, CT surveillance, diagnostic procedure) also improved with CAD (Fleiss κ, 0.44 vs 0.52; P = .001). Conclusion: Use of computer-aided diagnosis improved estimation of indeterminate pulmonary nodule malignancy risk on chest CT scans and improved interobserver agreement for both risk stratification and management recommendations

PET/CT and hepatic radiation injury in esophageal cancer patients

This paper evaluates the imaging appearance of radiation injury in the liver on positron emission tomography (PET)/computed tomography (CT) in patients with distal esophageal cancer who underwent pre-operative chemoradiation therapy. Twenty-six patients with distal esophageal cancer who received chemoradiotherapy before esophagectomy were included. All patients had baseline and follow-up PET/CT. Fluorodeoxyglucose (FDG) uptake in both left and right lobes of the liver was evaluated. CT findings suggesting radiation damage were documented. Abnormal FDG uptake in the liver was observed in 5 (19%) patients after therapy. These abnormalities were in the left lobe (12%) and right lobe (12%) of the liver. In the irradiated left lobe, FDG uptake increased focally greater than 50% over baseline in two patients (54% and 133%); in one of these patients, biopsy confirmed radiation injury. In the non-irradiated right lobe, standard uptake values (SUV) increased diffusely in two different patients. In one patient, SUV decreased by at least 50% in both the right and left lobes. In the remaining patients, there were no significant changes in FDG uptake. Atrophy and attenuation changes of irradiated liver on CT were found in 15 (58%) patients. In patients receiving chemoradiotherapy, PET/CT may identify metabolic abnormalities in irradiated liver. Such abnormalities should be correlated with other imaging, clinical and laboratory findings to avoid confusion with hepatic metastases