Clinical trial NCT01971905: Perfusion Scanning's for Kidney Tumors
Official title: Perfusion Scanning's for Kidney Tumors
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Kidney Cancer
Lead sponsor: Zealand University Hospital
Sponsor class: OTHER
First posted: 2013-10-29
Enrollment: 56
Sex: ALL
Minimum age (years): 35
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: the cohort will be selected from department of urology, Roskilde Hospital

Brief summary: To investigate the ability of perfusion CT/US-scanning to facilitate recognition of different tumour sub-types in small renal masses less than 7 cm by non-invasive imagining technology.

Detailed description: The number of diagnoses of renal cell carcinoma has increased over the past two decades because of the incidental detection of small renal tumours resulting from increased use of computed tomography \[1,2\]. There are distinct subtypes of renal cell carcinoma (RCC), and the biological aggressiveness and prognoses for these subtypes have been documented. Clear-cell RCC is the most common RCC subtype, followed by papillary RCC, chromophobe RCC and unclassified RCC. Collecting duct carcinoma is a rare and highly malignant type of RCC. Although most enhancing renal masses in adults are RCC, a significant percentage are benign (commonly oncocytoma), and these benign tumours cannot be distinguished from malignant tumours based on our standard imaging technology alone.

Benign primary renal masses include simple renal cysts, psuedotumours, angiomyolipomas, oncocytomas, juxtaglomerular tumours, multilocular cystic nephromas, mesoblastic nephromas and papillary adenomas. In a recent surgical series of 228 patients who underwent partial or radical nephrectomy with lesions ≤4 cm, 26.3% were benign \[3\]. The relatively high percentage of patients with benign renal cortical neoplasms who undergo surgery highlights the importance of new diagnostic technology in avoiding over-treatment.

Ultrasound (US) and CT scanning guided biopsy is the most commonly used method to diagnosis RCC. The sensitivity of biopsy for small masses (≤3 cm) is lower than for large masses \[4\]. Sensitivity is limited by false-negative results, which are due to a failure to properly target a small mass or the presence of impossible-to-differentiate benign from malignant cells due to insufficient cells, morphological overlap or cellular heterogeneity. Non diagnostic biopsy is not necessary benign, as repeated biopsy reveals malignancy diagnosis in the majority\[5\]. There is no radiologic criteria consistent with oncocytoma because of a lack of sensitivity and specificity \[6\]. MR-scanning and CT-scanning are not feasible diagnostic methodologies for oncocytoma because of the possibility of overlapping results from oncocytoma and RCC \[7\].

Hypotheses: To investigate the ability of perfusion CT/US-scanning to facilitate recognition of different tumour sub-types in small renal masses less than 7 cm by non-invasive imagining technology.

Purpose: To recognize different subtype's renal tumor by non invasive scanning. Design: A descriptive study

Eligibility criteria: Inclusion Criteria:

1. Patients suspecting to have renal tumors by CT/UL-scanning.
2. Patients age between 35 and 75 years
3. Normal renal function
4. Can read and understand Danish
5. Non - metastasis disease detected by scanning

Exclusion Criteria:

1. Patients have a nephropathy (defined as e-GFR less than 50 ml/min/1.73cm³).
2. Previous allergic reaction to intravenous contrast material.
3. Untreated hyperthyroidism.
4. Pregnancy.

Primary outcomes:
measure: To recognize different subtype's renal tumor by non invasive scanning.
timeFrame: one year
Secondary outcomes:
Other outcomes:
Locations:
city: Roskilde
country: Denmark
facility: Roskilde Hospital
Study officials:
affiliation: Zealand University Hospital
name: Nessn Azawi, M.D.
role: PRINCIPAL_INVESTIGATOR
References: