Nano-X Imaging (NNOX) Amortization - Intangibles (2021 - 2026)
Nano-X Imaging (NNOX) reported Amortization - Intangibles of $2.5 million for the quarter ended Mar 31, 2026, down 5.6% from $2.65 million a year earlier and down 1.8% from the prior quarter.
Nano-X Imaging (NNOX) Amortization - Intangibles (2021 - 2026) Analysis & Trends
Over the twelve months ended Mar 31, 2026, Nano-X Imaging's Amortization - Intangibles came in at $10.36 million, down 2.4% year-over-year; for the year ended Dec 31, 2025, it was $10.51 million, down 1.0% from the prior year.
- Amortization - Intangibles has a four-year compound annual growth rate of 56.1% (years ended Dec 2021 to Dec 2025).
- By year, Amortization - Intangibles came in at $10.61 million in the year ended Dec 31, 2024 (unchanged), $10.61 million in the year ended Dec 31, 2023 (unchanged), $10.61 million in the year ended Dec 31, 2022 (+499.9%) and $1.77 million in the year ended Dec 31, 2021.
- The figure for the quarter ended Mar 31, 2026 ranks as the lowest quarterly Amortization - Intangibles since the quarter ended Dec 31, 2021.
- The high point for year-over-year Amortization - Intangibles in five years was the quarter ended Dec 31, 2022 (growth of 49.8%); the low point was the quarter ended Mar 31, 2026 (a decline of 5.6%).
- Per Business Quant data, the three quarters before the quarter ended Mar 31, 2026 came in at $2.55 million (quarter ended Dec 31, 2025), $2.65 million (quarter ended Sep 30, 2025) and $2.65 million (quarter ended Jun 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn |
| 10 | Nano-X Imaging | 48.02 Mn | -131.66 Mn | -43.67 Mn |
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2026 | 2.50 Mn |
| Dec 31, 2025 | 2.55 Mn |
| Sep 30, 2025 | 2.65 Mn |
| Jun 30, 2025 | 2.65 Mn |
| Mar 31, 2025 | 2.65 Mn |
| Dec 31, 2024 | 2.65 Mn |
| Sep 30, 2024 | 2.65 Mn |
| Jun 30, 2024 | 2.65 Mn |
| Mar 31, 2024 | 2.65 Mn |
| Dec 31, 2023 | 2.65 Mn |
| Sep 30, 2023 | 2.65 Mn |
| Mar 31, 2023 | 2.65 Mn |
| Dec 31, 2022 | 2.65 Mn |
| Sep 30, 2022 | 2.65 Mn |
| Jun 30, 2022 | 2.65 Mn |
| Mar 31, 2022 | 2.65 Mn |
| Dec 31, 2021 | 1.77 Mn |
Nano-X Imaging Amortization - Intangibles API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=amortization-intangibles&ticker=NNOX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "amortization-intangibles", "ticker": "NNOX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=amortization-intangibles&ticker=NNOX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();