PET-CT-guided interventions in the management of FDG-positive lesions in patients suffering from solid malignancies: initial experiences

Positron emission tomography-computed tomography (PET-CT) has gained widespread acceptance as a staging investigation in the diagnostic workup of malignant tumours and may be used to visualize metabolic changes before the evolution of morphological changes. To make histology of PET findings without distinctive structural changes available for treatment decisions, we developed a protocol for multimodal image-guided interventions using an integrated PET-CT machine. We report our first experience in 12 patients admitted for staging and restaging of breast cancer, non-small cell lung cancer, cervical cancer, soft tissue sarcoma, and osteosarcoma. Patients were repositioned according to the findings in PET-CT and intervention was planned based on a subsequent single-bed PET-CT acquisition of the region concerned. The needle was introduced under CT guidance in a step-by-step technique and correct needle position in the centre of the FDG avid lesion was assured by repetition of a single-bed PET-CT acquisition before sampling. The metabolically active part of lesions was accurately targeted in all patients and representative samples were obtained in 92%. No major adverse effects occurred. We conclude that PET-CT guidance for interventions is feasible and may be promising to optimize the diagnostic yield of CT-guided interventions and to make metabolically active lesions without morphological correlate accessible to percutaneous interventions.

Thoracoabdominal-aortoiliac multidetector-row CT angiography at 80 and 100 kVp: assessment of image quality and radiation dose

OBJECTIVE: To compare image quality and radiation dose of thoracoabdominal computed tomography (CT) angiography at 80 and 100 kVp and to assess the feasibility of reducing contrast medium volume from 60 to 45 mL at 80 kVp. MATERIALS AND METHODS: This retrospective study had institutional review board approval; informed consent was waived. Seventy-five patients who had undergone thoracoabdominal 64-section multidetector-row CT angiography were divided into 3 groups of 25 patients each. Patients of groups A (tube voltage, 100 kVp) and B (tube voltage, 80 kVp) received 60 mL of contrast medium at 4 mL/s. Patients of group C (tube voltage, 80 kVp) received 45 mL of contrast medium at 3 mL/s. Mean aortoiliac attenuation, image noise, and contrast-to-noise ratio were assessed. The measurement of radiation dose was based on the volume CT dose index. Three independent readers assessed the diagnostic image quality. RESULTS: Mean aortoiliac attenuation for group B (621.1 +/- 90.5 HU) was significantly greater than for groups A and C (485.2 +/- 110.5 HU and 483.1 +/- 119.8 HU; respectively) (P < 0.001). Mean image noise was significantly higher for groups B and C than for group A (P < 0.05). The contrast-to-noise ratio did not significantly differ between the groups (group A, 35.0 +/- 13.8; group B, 31.7 +/- 10.1; group C, 27.3 +/- 11.5; P = 0.08). Mean volume CT dose index in groups B and C (5.2 +/- 0.4 mGy and 4.9 +/- 0.3 mGy, respectively) were reduced by 23.5% and 27.9%, respectively, compared with group A (6.8 +/- 0.8 mGy) (P < 0.001). The average overall diagnostic image quality for the 3 groups was graded as good or better. The score for group A was significantly higher than that for group C (P < 0.01), no difference was seen between group A and B (P = 0.92). CONCLUSIONS: Reduction of tube voltage from 100 to 80 kVp for thoracoabdominal CT angiography significantly reduces radiation dose without compromising image quality. Reduction of contrast medium volume to 45 mL at 80 kVp resulted in lower but still diagnostically acceptable image quality.

Is body weight the most appropriate criterion to select patients eligible for low-dose pulmonary CT angiography? Analysis of objective and subjective image quality at 80 kVp in 100 patients

The objective of this retrospective study was to assess image quality with pulmonary CT angiography (CTA) using 80 kVp and to find anthropomorphic parameters other than body weight (BW) to serve as selection criteria for low-dose CTA. Attenuation in the pulmonary arteries, anteroposterior and lateral diameters, cross-sectional area and soft-tissue thickness of the chest were measured in 100 consecutive patients weighing less than 100 kg with 80 kVp pulmonary CTA. Body surface area (BSA) and contrast-to-noise ratios (CNR) were calculated. Three radiologists analyzed arterial enhancement, noise, and image quality. Image parameters between patients grouped by BW (group 1: 0-50 kg; groups 2-6: 51-100 kg, decadally increasing) were compared. CNR was higher in patients weighing less than 60 kg than in the BW groups 71-99 kg (P between 0.025 and <0.001). Subjective ranking of enhancement (P = 0.165-0.605), noise (P = 0.063), and image quality (P = 0.079) did not differ significantly across all patient groups. CNR correlated moderately strongly with weight (R = -0.585), BSA (R = -0.582), cross-sectional area (R = -0.544), and anteroposterior diameter of the chest (R = -0.457; P < 0.001 all parameters). We conclude that 80 kVp pulmonary CTA permits diagnostic image quality in patients weighing up to 100 kg. Body weight is a suitable criterion to select patients for low-dose pulmonary CTA.

Endoleak detection with CT angiography in an abdominal aortic aneurysm phantom: effect of tube energy, simulated patient size, and physical properties of endoleaks

To analyze the detection of endoleaks with low-tube-voltage computed tomographic (CT) angiography.

Effect of automatic tube current modulation on radiation dose and image quality for low tube voltage multidetector row CT angiography: phantom study

RATIONALE AND OBJECTIVES: To evaluate the effect of automatic tube current modulation on radiation dose and image quality for low tube voltage computed tomography (CT) angiography. MATERIALS AND METHODS: An anthropomorphic phantom was scanned with a 64-section CT scanner using following tube voltages: 140 kVp (Protocol A), 120 kVp (Protocol B), 100 kVp (Protocol C), and 80 kVp (Protocol D). To achieve similar noise, combined z-axis and xy-axes automatic tube current modulation was applied. Effective dose (ED) for the four tube voltages was assessed. Three plastic vials filled with different concentrations of iodinated solution were placed on the phantom's abdomen to obtain attenuation measurements. The signal-to-noise ratio (SNR) was calculated and a figure of merit (FOM) for each iodinated solution was computed as SNR(2)/ED. RESULTS: The ED was kept similar for the four different tube voltages: (A) 5.4 mSv +/- 0.3, (B) 4.1 mSv +/- 0.6, (C) 3.9 mSv +/- 0.5, and (D) 4.2 mSv +/- 0.3 (P > .05). As the tube voltage decreased from 140 to 80 kVp, image noise was maintained (range, 13.8-14.9 HU) (P > .05). SNR increased as the tube voltage decreased, with an overall gain of 119% for the 80-kVp compared to the 140-kVp protocol (P < .05). The FOM results indicated that with a reduction of the tube voltage from 140 to 120, 100, and 80 kVp, at constant SNR, ED was reduced by a factor of 2.1, 3.3, and 5.1, respectively, (P < .001). CONCLUSIONS: As tube voltage decreases, automatic tube current modulation for CT angiography yields either a significant increase in image quality at constant radiation dose or a significant decrease in radiation dose at a constant image quality.

Free abdominal fluid without obvious solid organ injury upon CT imaging: an actual problem or simply over-diagnosing?

Whereas a non-operative approach for hemodynamically stable patients with free intraabdominal fluid in the presence of solid organ injury is generally accepted, the presence of free fluid in the abdomen without evidence of solid organ injury not only presents a challenge for the treating emergency physician but also for the surgeon in charge. Despite recent advances in imaging modalities, with multi-detector computed tomography (CT) (with or without contrast agent) usually the imaging method of choice, diagnosis and interpretation of the results remains difficult. While some studies conclude that CT is highly accurate and relatively specific at diagnosing mesenteric and hollow viscus injury, others studies deem CT to be unreliable. These differences may in part be due to the experience and the interpretation of the radiologist and/or the treating physician or surgeon.A search of the literature has made it apparent that there is no straightforward answer to the question what to do with patients with free intraabdominal fluid on CT scanning but without signs of solid organ injury. In hemodynamically unstable patients, free intraabdominal fluid in the absence of solid organ injury usually mandates immediate surgical intervention. For patients with blunt abdominal trauma and more than just a trace of free intraabdominal fluid or for patients with signs of peritonitis, the threshold for a surgical exploration - preferably by a laparoscopic approach - should be low. Based on the available information, we aim to provide the reader with an overview of the current literature with specific emphasis on diagnostic and therapeutic approaches to this problem and suggest a possible algorithm, which might help with the adequate treatment of such patients.

Thoracolumbar spine fractures in patients who have sustained severe trauma: depiction with multi-detector row CT

PURPOSE: To determine if multi–detector row computed tomography (CT) can replace conventional radiography and be performed alone in severe trauma patients for the depiction of thoracolumbar spine fractures. MATERIALS AND METHODS: One hundred consecutive severe trauma patients who underwent conventional radiography of the thoracolumbar spine as well as thoracoabdominal multi–detector row CT were prospectively identified. Conventional radiographs were reviewed independently by three radiologists and two orthopedic surgeons; CT images were reviewed by three radiologists. Reviewers were blinded both to one another’s reviews and to the results of initial evaluation. Presence, location, and stability of fractures, as well as quality of reviewed images, were assessed. Statistical analysis was performed to determine sensitivity and interobserver agreement for each procedure, with results of clinical and radiologic follow-up as the standard of reference. The time to perform each examination and the radiation dose involved were evaluated. A resource cost analysis was performed. RESULTS: Sixty-seven fractured vertebrae were diagnosed in 26 patients. Twelve patients had unstable spine fractures. Mean sensitivity and interobserver agreement, respectively, for detection of unstable fractures were 97.2% and 0.951 for multi–detector row CT and 33.3% and 0.368 for conventional radiography. The median times to perform a conventional radiographic and a multi–detector row CT examination, respectively, were 33 and 40 minutes. Effective radiation doses at conventional radiography of the spine and thoracoabdominal multi–detector row CT, respectively, were 6.36 mSv and 19.42 mSv. Multi–detector row CT enabled identification of 146 associated traumatic lesions. The costs of conventional radiography and multi–detector row CT, respectively, were $145 and $880 per patient. CONCLUSION: Multi–detector row CT is a better examination for depicting spine fractures than conventional radiography. It can replace conventional radiography and be performed alone in patients who have sustained severe trauma.

Evaluation of texture features in hepatic tissue characterization from non-enhanced CT images

Aim of this paper is to evaluate the diagnostic contribution of various types of texture features in discrimination of hepatic tissue in abdominal non-enhanced Computed Tomography (CT) images. Regions of Interest (ROIs) corresponding to the classes: normal liver, cyst, hemangioma, and hepatocellular carcinoma were drawn by an experienced radiologist. For each ROI, five distinct sets of texture features are extracted using First Order Statistics (FOS), Spatial Gray Level Dependence Matrix (SGLDM), Gray Level Difference Method (GLDM), Laws' Texture Energy Measures (TEM), and Fractal Dimension Measurements (FDM). In order to evaluate the ability of the texture features to discriminate the various types of hepatic tissue, each set of texture features, or its reduced version after genetic algorithm based feature selection, was fed to a feed-forward Neural Network (NN) classifier. For each NN, the area under Receiver Operating Characteristic (ROC) curves (Az) was calculated for all one-vs-all discriminations of hepatic tissue. Additionally, the total Az for the multi-class discrimination task was estimated. The results show that features derived from FOS perform better than other texture features (total Az: 0.802+/-0.083) in the discrimination of hepatic tissue.

Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers

The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifiers (ECs), are comparatively assessed.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.