A novel ultrasound technique to detect early chronic kidney disease

Dulitha K. Hewadikaram, Mudhitha Bandara, Amal N. Pattivedana, Hiran H.E. Jayaweera, Kithsiri M. Jayananda, W. A.Monica Madhavi, Aruna Pallewatte, Channa Jayasumana, Sisira Siribaddana, Janaka P. Wansapura

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Chronic kidney disease (CKD) of unknown etiology is recognized as a major public health challenge and a leading cause of morbidity and mortality in the dry zone in Sri Lanka. CKD is asymptomatic and are diagnosed only in late stages. Evidence points to strong correlation between progression of CKD and kidney fibrosis. Several biochemical markers of renal fibrosis have been associated with progression of CKD. However, no marker is able to predict CKD consistently and accurately before being detected with traditional clinical tests (serum creatinine, and cystatin C, urine albumin or protein, and ultrasound scanning). In this paper, we hypothesize that fibrosis in the kidney, and therefore the severity of the disease, is reflected in the frequency spectrum of the scattered ultrasound from the kidney. We present a design of a simple ultrasound system, and a set of clinical and laboratory studies to identify spectral characteristics of the scattered ultrasound wave from the kidney that correlates with CKD. We believe that spectral parameters identified in these studies can be used to detect and stratify CKD at an earlier stage than what is possible with current markers of CKD.

Original languageEnglish (US)
Article number448
StatePublished - 2019
Externally publishedYes


  • Chronic kidney disease of unknown etiology
  • Kidney fibrosis
  • Ultrasound spectral characteristics

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • Pharmacology, Toxicology and Pharmaceutics(all)


Dive into the research topics of 'A novel ultrasound technique to detect early chronic kidney disease'. Together they form a unique fingerprint.

Cite this