Nano-X Imaging (NNOX) Change in Accured Expenses (2021 - 2026)
Nano-X Imaging (NNOX) recorded Change in Accured Expenses of $597,000 in the quarter ended Jun 30, 2026, up 655.7% from $79,000 a year earlier.
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Analysis
Nano-X Imaging (NNOX) Change in Accured Expenses (2021 - 2026) Analysis & Trends
On a TTM basis, Nano-X Imaging's Change in Accured Expenses came in at $506,000 as of Jun 30, 2026; for the year ended Dec 31, 2025, it came in at $1.18 million, up 141.2% from the prior year.
- Annual Change in Accured Expenses has a five-year compound annual growth rate of -12.9% (years ended Dec 2020 to Dec 2025).
- Across earlier years, Change in Accured Expenses came in at $490,000 in the year ended Dec 31, 2024, -$8.96 million in the year ended Dec 31, 2023, $10.41 million in the year ended Dec 31, 2022 and -$719,000 in the year ended Dec 31, 2021.
- Quarterly Change in Accured Expenses has ranged from -$8.48 million in the quarter ended Dec 31, 2023 to $9.99 million in the quarter ended Dec 31, 2022 over the past five years.
- Per Business Quant, the preceding three quarters came in at -$2.11 million (quarter ended Mar 31, 2026), $2.44 million (quarter ended Dec 31, 2025) and -$417,000 (quarter ended Sep 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 242.18 Bn | 221.33 Bn | 4.88 Bn | - |
| 2 | Abbott Laboratories | 168.71 Bn | 139.79 Bn | 7.27 Bn | - |
| 3 | Danaher | 150.46 Bn | 134.27 Bn | 3.61 Bn | -249.00 Mn |
| 4 | Intuitive Surgical | 138.71 Bn | 118.26 Bn | 1.96 Bn | 55.00 Mn |
| 5 | Medtronic | 110.54 Bn | 76.41 Bn | 6.34 Bn | -531.00 Mn |
| 6 | Stryker | 105.66 Bn | 91.78 Bn | 4.50 Bn | 298.00 Mn |
| 7 | Boston Scientific | 61.74 Bn | 56.75 Bn | 3.85 Bn | 234.00 Mn |
| 8 | Edwards Lifesciences | 49.09 Bn | 33.21 Bn | 1.35 Bn | 123.70 Mn |
| 9 | Becton Dickinson | 48.16 Bn | 45.31 Bn | 2.32 Bn | - |
| 10 | Nano-X Imaging | 44.54 Mn | -135.14 Mn | -43.67 Mn | 597,000.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 597,000.00 |
| Mar 31, 2026 | -2.11 Mn |
| Dec 31, 2025 | 2.44 Mn |
| Sep 30, 2025 | -417,000.00 |
| Jun 30, 2025 | 79,000.00 |
| Mar 31, 2025 | -919,000.00 |
| Dec 31, 2024 | 564,000.00 |
| Sep 30, 2024 | -99,000.00 |
| Jun 30, 2024 | 323,000.00 |
| Mar 31, 2024 | -298,000.00 |
| Dec 31, 2023 | -8.48 Mn |
| Sep 30, 2023 | -1.17 Mn |
| Jun 30, 2023 | 1.25 Mn |
| Mar 31, 2023 | -559,000.00 |
| Dec 31, 2022 | 9.99 Mn |
| Sep 30, 2022 | -1.37 Mn |
| Jun 30, 2022 | 2.39 Mn |
| Mar 31, 2022 | -596,000.00 |
| Dec 31, 2021 | -1.49 Mn |
| Sep 30, 2021 | 699,000.00 |
API Access
Nano-X Imaging Change in Accured Expenses 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=change-in-accured-expenses&ticker=NNOX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "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=change-in-accured-expenses&ticker=NNOX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();