diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 298be9062c..5419004a9e 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -37,7 +37,7 @@ repos:
     rev: v3.18.0
     hooks:
       - id: pyupgrade
-        args: [--py38-plus, --keep-runtime-typing]
+        args: [--py39-plus, --keep-runtime-typing]
         name: Upgrade code with exceptions
         exclude: |
           (?x)(
diff --git a/monai/apps/detection/networks/retinanet_network.py b/monai/apps/detection/networks/retinanet_network.py
index ec86c3b0e9..ca6a8f5c19 100644
--- a/monai/apps/detection/networks/retinanet_network.py
+++ b/monai/apps/detection/networks/retinanet_network.py
@@ -42,7 +42,7 @@
 import math
 import warnings
 from collections.abc import Callable, Sequence
-from typing import Any, Dict
+from typing import Any
 
 import torch
 from torch import Tensor, nn
@@ -330,7 +330,7 @@ def forward(self, images: Tensor) -> Any:
         features = self.feature_extractor(images)
         if isinstance(features, Tensor):
             feature_maps = [features]
-        elif torch.jit.isinstance(features, Dict[str, Tensor]):
+        elif torch.jit.isinstance(features, dict[str, Tensor]):
             feature_maps = list(features.values())
         else:
             feature_maps = list(features)
diff --git a/monai/apps/detection/transforms/array.py b/monai/apps/detection/transforms/array.py
index d8ffce4584..6b92572954 100644
--- a/monai/apps/detection/transforms/array.py
+++ b/monai/apps/detection/transforms/array.py
@@ -15,7 +15,9 @@
 
 from __future__ import annotations
 
-from typing import Any, Sequence
+from typing import Any
+
+from collections.abc import Sequence
 
 import numpy as np
 import torch
diff --git a/monai/apps/detection/utils/anchor_utils.py b/monai/apps/detection/utils/anchor_utils.py
index cbde3ebae9..145350853a 100644
--- a/monai/apps/detection/utils/anchor_utils.py
+++ b/monai/apps/detection/utils/anchor_utils.py
@@ -39,7 +39,8 @@
 
 from __future__ import annotations
 
-from typing import List, Sequence
+
+from collections.abc import Sequence
 
 import torch
 from torch import Tensor, nn
@@ -106,7 +107,7 @@ class AnchorGenerator(nn.Module):
             anchor_generator = AnchorGenerator(sizes, aspect_ratios)
     """
 
-    __annotations__ = {"cell_anchors": List[torch.Tensor]}
+    __annotations__ = {"cell_anchors": list[torch.Tensor]}
 
     def __init__(
         self,
@@ -364,7 +365,7 @@ class AnchorGeneratorWithAnchorShape(AnchorGenerator):
             anchor_generator = AnchorGeneratorWithAnchorShape(feature_map_scales, base_anchor_shapes)
     """
 
-    __annotations__ = {"cell_anchors": List[torch.Tensor]}
+    __annotations__ = {"cell_anchors": list[torch.Tensor]}
 
     def __init__(
         self,
diff --git a/monai/apps/generation/maisi/networks/autoencoderkl_maisi.py b/monai/apps/generation/maisi/networks/autoencoderkl_maisi.py
index a52274b24a..6251ea8e83 100644
--- a/monai/apps/generation/maisi/networks/autoencoderkl_maisi.py
+++ b/monai/apps/generation/maisi/networks/autoencoderkl_maisi.py
@@ -13,7 +13,7 @@
 
 import gc
 import logging
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 import torch.nn as nn
diff --git a/monai/apps/generation/maisi/networks/controlnet_maisi.py b/monai/apps/generation/maisi/networks/controlnet_maisi.py
index 269086d971..7c13fd7bc6 100644
--- a/monai/apps/generation/maisi/networks/controlnet_maisi.py
+++ b/monai/apps/generation/maisi/networks/controlnet_maisi.py
@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 
diff --git a/monai/apps/pathology/engines/utils.py b/monai/apps/pathology/engines/utils.py
index 02249ed640..c704dc7469 100644
--- a/monai/apps/pathology/engines/utils.py
+++ b/monai/apps/pathology/engines/utils.py
@@ -11,7 +11,9 @@
 
 from __future__ import annotations
 
-from typing import Any, Sequence
+from typing import Any
+
+from collections.abc import Sequence
 
 import torch
 
diff --git a/monai/apps/pathology/inferers/inferer.py b/monai/apps/pathology/inferers/inferer.py
index 71259ca7df..4f034f0ad1 100644
--- a/monai/apps/pathology/inferers/inferer.py
+++ b/monai/apps/pathology/inferers/inferer.py
@@ -11,7 +11,9 @@
 
 from __future__ import annotations
 
-from typing import Any, Callable, Sequence
+from typing import Any, Callable
+
+from collections.abc import Sequence
 
 import numpy as np
 import torch
diff --git a/monai/apps/pathology/metrics/lesion_froc.py b/monai/apps/pathology/metrics/lesion_froc.py
index f4bf51ab28..bbd7bf4905 100644
--- a/monai/apps/pathology/metrics/lesion_froc.py
+++ b/monai/apps/pathology/metrics/lesion_froc.py
@@ -11,7 +11,9 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Iterable
+from typing import TYPE_CHECKING, Any
+
+from collections.abc import Iterable
 
 import numpy as np
 
diff --git a/monai/apps/pathology/transforms/post/array.py b/monai/apps/pathology/transforms/post/array.py
index 035bce2c69..bb50ee4fd9 100644
--- a/monai/apps/pathology/transforms/post/array.py
+++ b/monai/apps/pathology/transforms/post/array.py
@@ -12,7 +12,9 @@
 from __future__ import annotations
 
 import warnings
-from typing import Callable, Sequence
+from typing import Callable
+
+from collections.abc import Sequence
 
 import numpy as np
 import torch
diff --git a/monai/apps/tcia/utils.py b/monai/apps/tcia/utils.py
index 5524b488e9..f023cdbc87 100644
--- a/monai/apps/tcia/utils.py
+++ b/monai/apps/tcia/utils.py
@@ -12,7 +12,7 @@
 from __future__ import annotations
 
 import os
-from typing import Iterable
+from collections.abc import Iterable
 
 import monai
 from monai.config.type_definitions import PathLike
diff --git a/monai/apps/utils.py b/monai/apps/utils.py
index 0c998146a3..c2e17d3247 100644
--- a/monai/apps/utils.py
+++ b/monai/apps/utils.py
@@ -136,10 +136,7 @@ def check_hash(filepath: PathLike, val: str | None = None, hash_type: str = "md5
         return True
     actual_hash_func = look_up_option(hash_type.lower(), SUPPORTED_HASH_TYPES)
 
-    if sys.version_info >= (3, 9):
-        actual_hash = actual_hash_func(usedforsecurity=False)  # allows checks on FIPS enabled machines
-    else:
-        actual_hash = actual_hash_func()
+    actual_hash = actual_hash_func(usedforsecurity=False)  # allows checks on FIPS enabled machines
 
     try:
         with open(filepath, "rb") as f:
diff --git a/monai/apps/vista3d/transforms.py b/monai/apps/vista3d/transforms.py
index 3e8145cd80..bd7fb19493 100644
--- a/monai/apps/vista3d/transforms.py
+++ b/monai/apps/vista3d/transforms.py
@@ -12,7 +12,7 @@
 from __future__ import annotations
 
 import warnings
-from typing import Sequence
+from collections.abc import Sequence
 
 import numpy as np
 import torch
diff --git a/monai/bundle/reference_resolver.py b/monai/bundle/reference_resolver.py
index 050cd75fa7..6c5ca776f5 100644
--- a/monai/bundle/reference_resolver.py
+++ b/monai/bundle/reference_resolver.py
@@ -14,7 +14,9 @@
 import re
 import warnings
 from collections.abc import Sequence
-from typing import Any, Iterator
+from typing import Any
+
+from collections.abc import Iterator
 
 from monai.bundle.config_item import ConfigComponent, ConfigExpression, ConfigItem
 from monai.bundle.utils import DEPRECATED_ID_MAPPING, ID_REF_KEY, ID_SEP_KEY
diff --git a/monai/bundle/workflows.py b/monai/bundle/workflows.py
index ccdb08e208..f425d8fd28 100644
--- a/monai/bundle/workflows.py
+++ b/monai/bundle/workflows.py
@@ -19,7 +19,9 @@
 from copy import copy
 from logging.config import fileConfig
 from pathlib import Path
-from typing import Any, Sequence
+from typing import Any
+
+from collections.abc import Sequence
 
 from monai.apps.utils import get_logger
 from monai.bundle.config_parser import ConfigParser
diff --git a/monai/config/type_definitions.py b/monai/config/type_definitions.py
index 57454a94e1..cf6a2957ee 100644
--- a/monai/config/type_definitions.py
+++ b/monai/config/type_definitions.py
@@ -12,7 +12,9 @@
 from __future__ import annotations
 
 import os
-from typing import Collection, Hashable, Iterable, Sequence, TypeVar, Union
+from typing import TypeVar, Union
+
+from collections.abc import Collection, Hashable, Iterable, Sequence
 
 import numpy as np
 import torch
diff --git a/monai/data/meta_obj.py b/monai/data/meta_obj.py
index 0dccaa9e1c..d951d69b04 100644
--- a/monai/data/meta_obj.py
+++ b/monai/data/meta_obj.py
@@ -14,7 +14,9 @@
 import itertools
 import pprint
 from copy import deepcopy
-from typing import Any, Iterable
+from typing import Any
+
+from collections.abc import Iterable
 
 import numpy as np
 import torch
diff --git a/monai/data/meta_tensor.py b/monai/data/meta_tensor.py
index 2df4da4a35..88e55c74da 100644
--- a/monai/data/meta_tensor.py
+++ b/monai/data/meta_tensor.py
@@ -14,7 +14,9 @@
 import functools
 import warnings
 from copy import deepcopy
-from typing import Any, Sequence
+from typing import Any
+
+from collections.abc import Sequence
 
 import numpy as np
 import torch
diff --git a/monai/engines/evaluator.py b/monai/engines/evaluator.py
index 523c3dcbf6..8c0972ae7f 100644
--- a/monai/engines/evaluator.py
+++ b/monai/engines/evaluator.py
@@ -12,7 +12,9 @@
 from __future__ import annotations
 
 import warnings
-from typing import TYPE_CHECKING, Any, Callable, Iterable, Sequence
+from typing import TYPE_CHECKING, Any, Callable
+
+from collections.abc import Iterable, Sequence
 
 import torch
 from torch.utils.data import DataLoader
diff --git a/monai/engines/trainer.py b/monai/engines/trainer.py
index bbcc9c880b..0ca9d40a26 100644
--- a/monai/engines/trainer.py
+++ b/monai/engines/trainer.py
@@ -12,7 +12,9 @@
 from __future__ import annotations
 
 import warnings
-from typing import TYPE_CHECKING, Any, Callable, Iterable, Sequence
+from typing import TYPE_CHECKING, Any, Callable
+
+from collections.abc import Iterable, Sequence
 
 import torch
 from torch.optim.optimizer import Optimizer
diff --git a/monai/engines/utils.py b/monai/engines/utils.py
index 11a0000989..74612f7116 100644
--- a/monai/engines/utils.py
+++ b/monai/engines/utils.py
@@ -13,7 +13,9 @@
 
 from abc import ABC, abstractmethod
 from collections.abc import Callable, Sequence
-from typing import TYPE_CHECKING, Any, Mapping, cast
+from typing import TYPE_CHECKING, Any, cast
+
+from collections.abc import Mapping
 
 import torch
 import torch.nn as nn
diff --git a/monai/handlers/clearml_handlers.py b/monai/handlers/clearml_handlers.py
index 1cfd6a33fb..11f9dca24f 100644
--- a/monai/handlers/clearml_handlers.py
+++ b/monai/handlers/clearml_handlers.py
@@ -11,7 +11,9 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Mapping, Sequence
+from typing import TYPE_CHECKING, Any
+
+from collections.abc import Mapping, Sequence
 
 from monai.utils import optional_import
 
diff --git a/monai/inferers/utils.py b/monai/inferers/utils.py
index bd99765348..8bb2941529 100644
--- a/monai/inferers/utils.py
+++ b/monai/inferers/utils.py
@@ -13,7 +13,9 @@
 
 import itertools
 from collections.abc import Callable, Mapping, Sequence
-from typing import Any, Iterable
+from typing import Any
+
+from collections.abc import Iterable
 
 import numpy as np
 import torch
diff --git a/monai/metrics/utils.py b/monai/metrics/utils.py
index 340e54a1d7..43bd5a3483 100644
--- a/monai/metrics/utils.py
+++ b/monai/metrics/utils.py
@@ -14,7 +14,9 @@
 import warnings
 from functools import lru_cache, partial
 from types import ModuleType
-from typing import Any, Iterable, Sequence
+from typing import Any
+
+from collections.abc import Iterable, Sequence
 
 import numpy as np
 import torch
diff --git a/monai/networks/blocks/attention_utils.py b/monai/networks/blocks/attention_utils.py
index 8c9002a16e..c5666d7728 100644
--- a/monai/networks/blocks/attention_utils.py
+++ b/monai/networks/blocks/attention_utils.py
@@ -9,7 +9,6 @@
 
 from __future__ import annotations
 
-from typing import Tuple
 
 import torch
 import torch.nn.functional as F
@@ -50,7 +49,7 @@ def get_rel_pos(q_size: int, k_size: int, rel_pos: torch.Tensor) -> torch.Tensor
 
 
 def add_decomposed_rel_pos(
-    attn: torch.Tensor, q: torch.Tensor, rel_pos_lst: nn.ParameterList, q_size: Tuple, k_size: Tuple
+    attn: torch.Tensor, q: torch.Tensor, rel_pos_lst: nn.ParameterList, q_size: tuple, k_size: tuple
 ) -> torch.Tensor:
     r"""
     Calculate decomposed Relative Positional Embeddings from mvitv2 implementation:
diff --git a/monai/networks/blocks/crossattention.py b/monai/networks/blocks/crossattention.py
index bdecf63168..f2bb311288 100644
--- a/monai/networks/blocks/crossattention.py
+++ b/monai/networks/blocks/crossattention.py
@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from typing import Optional, Tuple
+from typing import Optional
 
 import torch
 import torch.nn as nn
@@ -42,7 +42,7 @@ def __init__(
         causal: bool = False,
         sequence_length: int | None = None,
         rel_pos_embedding: Optional[str] = None,
-        input_size: Optional[Tuple] = None,
+        input_size: Optional[tuple] = None,
         attention_dtype: Optional[torch.dtype] = None,
         use_flash_attention: bool = False,
     ) -> None:
diff --git a/monai/networks/blocks/denseblock.py b/monai/networks/blocks/denseblock.py
index 8c67584f5f..ecccab9d5a 100644
--- a/monai/networks/blocks/denseblock.py
+++ b/monai/networks/blocks/denseblock.py
@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 import torch.nn as nn
diff --git a/monai/networks/blocks/pos_embed_utils.py b/monai/networks/blocks/pos_embed_utils.py
index 21586e56da..1bda4d8aea 100644
--- a/monai/networks/blocks/pos_embed_utils.py
+++ b/monai/networks/blocks/pos_embed_utils.py
@@ -13,7 +13,7 @@
 
 import collections.abc
 from itertools import repeat
-from typing import List, Union
+from typing import Union
 
 import torch
 import torch.nn as nn
@@ -33,7 +33,7 @@ def parse(x):
 
 
 def build_sincos_position_embedding(
-    grid_size: Union[int, List[int]], embed_dim: int, spatial_dims: int = 3, temperature: float = 10000.0
+    grid_size: Union[int, list[int]], embed_dim: int, spatial_dims: int = 3, temperature: float = 10000.0
 ) -> torch.nn.Parameter:
     """
     Builds a sin-cos position embedding based on the given grid size, embed dimension, spatial dimensions, and temperature.
diff --git a/monai/networks/blocks/rel_pos_embedding.py b/monai/networks/blocks/rel_pos_embedding.py
index e53e5841b0..c7546bdb4e 100644
--- a/monai/networks/blocks/rel_pos_embedding.py
+++ b/monai/networks/blocks/rel_pos_embedding.py
@@ -9,7 +9,8 @@
 
 from __future__ import annotations
 
-from typing import Iterable, Tuple
+
+from collections.abc import Iterable
 
 import torch
 from torch import nn
@@ -19,7 +20,7 @@
 
 
 class DecomposedRelativePosEmbedding(nn.Module):
-    def __init__(self, s_input_dims: Tuple[int, int] | Tuple[int, int, int], c_dim: int, num_heads: int) -> None:
+    def __init__(self, s_input_dims: tuple[int, int] | tuple[int, int, int], c_dim: int, num_heads: int) -> None:
         """
         Args:
             s_input_dims (Tuple): input spatial dimension. (H, W) or (H, W, D)
diff --git a/monai/networks/blocks/selfattention.py b/monai/networks/blocks/selfattention.py
index ac96b077bd..f582fa68aa 100644
--- a/monai/networks/blocks/selfattention.py
+++ b/monai/networks/blocks/selfattention.py
@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from typing import Tuple, Union
+from typing import Union
 
 import torch
 import torch.nn as nn
@@ -41,7 +41,7 @@ def __init__(
         causal: bool = False,
         sequence_length: int | None = None,
         rel_pos_embedding: str | None = None,
-        input_size: Tuple | None = None,
+        input_size: tuple | None = None,
         attention_dtype: torch.dtype | None = None,
         include_fc: bool = True,
         use_combined_linear: bool = True,
diff --git a/monai/networks/layers/simplelayers.py b/monai/networks/layers/simplelayers.py
index 4acd4a3622..98417f17aa 100644
--- a/monai/networks/layers/simplelayers.py
+++ b/monai/networks/layers/simplelayers.py
@@ -13,7 +13,7 @@
 
 import math
 from copy import deepcopy
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 import torch.nn.functional as F
diff --git a/monai/networks/layers/vector_quantizer.py b/monai/networks/layers/vector_quantizer.py
index 9c354e1009..a865650c44 100644
--- a/monai/networks/layers/vector_quantizer.py
+++ b/monai/networks/layers/vector_quantizer.py
@@ -11,7 +11,8 @@
 
 from __future__ import annotations
 
-from typing import Sequence, Tuple
+
+from collections.abc import Sequence
 
 import torch
 from torch import nn
@@ -87,7 +88,7 @@ def __init__(
             range(1, self.spatial_dims + 1)
         )
 
-    def quantize(self, inputs: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+    def quantize(self, inputs: torch.Tensor) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
         """
         Given an input it projects it to the quantized space and returns additional tensors needed for EMA loss.
 
@@ -164,7 +165,7 @@ def distributed_synchronization(self, encodings_sum: torch.Tensor, dw: torch.Ten
         else:
             pass
 
-    def forward(self, inputs: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
+    def forward(self, inputs: torch.Tensor) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
         flat_input, encodings, encoding_indices = self.quantize(inputs)
         quantized = self.embed(encoding_indices)
 
@@ -211,7 +212,7 @@ def __init__(self, quantizer: EMAQuantizer):
 
         self.perplexity: torch.Tensor = torch.rand(1)
 
-    def forward(self, inputs: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]:
+    def forward(self, inputs: torch.Tensor) -> tuple[torch.Tensor, torch.Tensor]:
         quantized, loss, encoding_indices = self.quantizer(inputs)
         # Perplexity calculations
         avg_probs = (
diff --git a/monai/networks/nets/autoencoderkl.py b/monai/networks/nets/autoencoderkl.py
index af191e748b..a5914d687a 100644
--- a/monai/networks/nets/autoencoderkl.py
+++ b/monai/networks/nets/autoencoderkl.py
@@ -12,7 +12,6 @@
 from __future__ import annotations
 
 from collections.abc import Sequence
-from typing import List
 
 import torch
 import torch.nn as nn
@@ -188,7 +187,7 @@ def __init__(
         self.norm_eps = norm_eps
         self.attention_levels = attention_levels
 
-        blocks: List[nn.Module] = []
+        blocks: list[nn.Module] = []
         # Initial convolution
         blocks.append(
             Convolution(
@@ -338,7 +337,7 @@ def __init__(
 
         reversed_block_out_channels = list(reversed(channels))
 
-        blocks: List[nn.Module] = []
+        blocks: list[nn.Module] = []
 
         # Initial convolution
         blocks.append(
diff --git a/monai/networks/nets/dynunet.py b/monai/networks/nets/dynunet.py
index a2a133a24c..6c87387bd2 100644
--- a/monai/networks/nets/dynunet.py
+++ b/monai/networks/nets/dynunet.py
@@ -11,7 +11,9 @@
 
 # isort: dont-add-import: from __future__ import annotations
 
-from typing import List, Optional, Sequence, Tuple, Union
+from typing import Optional, Union
+
+from collections.abc import Sequence
 
 import torch
 import torch.nn as nn
@@ -32,7 +34,7 @@ class DynUNetSkipLayer(nn.Module):
     forward passes of the network.
     """
 
-    heads: Union[None, List[torch.Tensor]]
+    heads: Union[None, list[torch.Tensor]]
 
     def __init__(self, index, downsample, upsample, next_layer, heads=None, super_head=None):
         super().__init__()
@@ -136,9 +138,9 @@ def __init__(
         strides: Sequence[Union[Sequence[int], int]],
         upsample_kernel_size: Sequence[Union[Sequence[int], int]],
         filters: Optional[Sequence[int]] = None,
-        dropout: Optional[Union[Tuple, str, float]] = None,
-        norm_name: Union[Tuple, str] = ("INSTANCE", {"affine": True}),
-        act_name: Union[Tuple, str] = ("leakyrelu", {"inplace": True, "negative_slope": 0.01}),
+        dropout: Optional[Union[tuple, str, float]] = None,
+        norm_name: Union[tuple, str] = ("INSTANCE", {"affine": True}),
+        act_name: Union[tuple, str] = ("leakyrelu", {"inplace": True, "negative_slope": 0.01}),
         deep_supervision: bool = False,
         deep_supr_num: int = 1,
         res_block: bool = False,
@@ -169,7 +171,7 @@ def __init__(
         self.deep_supervision = deep_supervision
         self.deep_supr_num = deep_supr_num
         # initialize the typed list of supervision head outputs so that Torchscript can recognize what's going on
-        self.heads: List[torch.Tensor] = [torch.rand(1)] * self.deep_supr_num
+        self.heads: list[torch.Tensor] = [torch.rand(1)] * self.deep_supr_num
         if self.deep_supervision:
             self.deep_supervision_heads = self.get_deep_supervision_heads()
             self.check_deep_supr_num()
@@ -323,8 +325,8 @@ def get_upsamples(self):
 
     def get_module_list(
         self,
-        in_channels: List[int],
-        out_channels: List[int],
+        in_channels: list[int],
+        out_channels: list[int],
         kernel_size: Sequence[Union[Sequence[int], int]],
         strides: Sequence[Union[Sequence[int], int]],
         conv_block: nn.Module,
diff --git a/monai/networks/nets/netadapter.py b/monai/networks/nets/netadapter.py
index 452c31be37..f87120ba21 100644
--- a/monai/networks/nets/netadapter.py
+++ b/monai/networks/nets/netadapter.py
@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from typing import Any, Dict
+from typing import Any
 
 import torch
 
@@ -109,7 +109,7 @@ def forward(self, x):
         x = self.features(x)
         if isinstance(x, tuple):
             x = x[0]  # it might be a namedtuple such as torchvision.model.InceptionOutputs
-        elif torch.jit.isinstance(x, Dict[str, torch.Tensor]):
+        elif torch.jit.isinstance(x, dict[str, torch.Tensor]):
             x = x[self.node_name]  # torchvision create_feature_extractor
         if self.pool is not None:
             x = self.pool(x)
diff --git a/monai/networks/nets/quicknat.py b/monai/networks/nets/quicknat.py
index 7e0f9c6b38..ceeb4b863e 100644
--- a/monai/networks/nets/quicknat.py
+++ b/monai/networks/nets/quicknat.py
@@ -11,7 +11,9 @@
 
 from __future__ import annotations
 
-from typing import Optional, Sequence, Tuple, Union
+from typing import Optional, Union
+
+from collections.abc import Sequence
 
 import torch
 import torch.nn as nn
@@ -360,8 +362,8 @@ def __init__(
         # Valid options : NONE, CSE, SSE, CSSE
         se_block: str = "None",
         drop_out: float = 0,
-        act: Union[Tuple, str] = Act.PRELU,
-        norm: Union[Tuple, str] = Norm.INSTANCE,
+        act: Union[tuple, str] = Act.PRELU,
+        norm: Union[tuple, str] = Norm.INSTANCE,
         adn_ordering: str = "NA",
     ) -> None:
         self.act = act
diff --git a/monai/networks/nets/spade_network.py b/monai/networks/nets/spade_network.py
index 9164541f27..e00ca47e45 100644
--- a/monai/networks/nets/spade_network.py
+++ b/monai/networks/nets/spade_network.py
@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from typing import Sequence
+from collections.abc import Sequence
 
 import numpy as np
 import torch
diff --git a/monai/networks/nets/vista3d.py b/monai/networks/nets/vista3d.py
index 6313b7812d..fa426a40c2 100644
--- a/monai/networks/nets/vista3d.py
+++ b/monai/networks/nets/vista3d.py
@@ -12,7 +12,9 @@
 from __future__ import annotations
 
 import math
-from typing import Any, Callable, Optional, Sequence, Tuple
+from typing import Any, Callable, Optional
+
+from collections.abc import Sequence
 
 import numpy as np
 import torch
@@ -692,7 +694,7 @@ def __init__(
 
     def forward(
         self, image_embedding: torch.Tensor, image_pe: torch.Tensor, point_embedding: torch.Tensor
-    ) -> Tuple[torch.Tensor, torch.Tensor]:
+    ) -> tuple[torch.Tensor, torch.Tensor]:
         """
         Args:
             image_embedding: image to attend to. Should be shape
@@ -769,7 +771,7 @@ def __init__(
 
     def forward(
         self, queries: torch.Tensor, keys: torch.Tensor, query_pe: torch.Tensor, key_pe: torch.Tensor
-    ) -> Tuple[torch.Tensor, torch.Tensor]:
+    ) -> tuple[torch.Tensor, torch.Tensor]:
         # Self attention block
         if self.skip_first_layer_pe:
             queries = self.self_attn(q=queries, k=queries, v=queries)
@@ -891,7 +893,7 @@ def _pe_encoding(self, coords: torch.torch.Tensor) -> torch.torch.Tensor:
         # [bs=1, N=2, 128+128=256]
         return torch.cat([torch.sin(coords), torch.cos(coords)], dim=-1)
 
-    def forward(self, size: Tuple[int, int, int]) -> torch.torch.Tensor:
+    def forward(self, size: tuple[int, int, int]) -> torch.torch.Tensor:
         """Generate positional encoding for a grid of the specified size."""
         h, w, d = size
         device: Any = self.positional_encoding_gaussian_matrix.device
@@ -907,7 +909,7 @@ def forward(self, size: Tuple[int, int, int]) -> torch.torch.Tensor:
         return pe.permute(3, 0, 1, 2)
 
     def forward_with_coords(
-        self, coords_input: torch.torch.Tensor, image_size: Tuple[int, int, int]
+        self, coords_input: torch.torch.Tensor, image_size: tuple[int, int, int]
     ) -> torch.torch.Tensor:
         """Positionally encode points that are not normalized to [0,1]."""
         coords = coords_input.clone()
diff --git a/monai/networks/nets/vqvae.py b/monai/networks/nets/vqvae.py
index f198bfbb2b..43ba48585c 100644
--- a/monai/networks/nets/vqvae.py
+++ b/monai/networks/nets/vqvae.py
@@ -12,7 +12,6 @@
 from __future__ import annotations
 
 from collections.abc import Sequence
-from typing import Tuple
 
 import torch
 import torch.nn as nn
@@ -107,7 +106,7 @@ def __init__(
         channels: Sequence[int],
         num_res_layers: int,
         num_res_channels: Sequence[int],
-        downsample_parameters: Sequence[Tuple[int, int, int, int]],
+        downsample_parameters: Sequence[tuple[int, int, int, int]],
         dropout: float,
         act: tuple | str | None,
     ) -> None:
@@ -198,7 +197,7 @@ def __init__(
         channels: Sequence[int],
         num_res_layers: int,
         num_res_channels: Sequence[int],
-        upsample_parameters: Sequence[Tuple[int, int, int, int, int]],
+        upsample_parameters: Sequence[tuple[int, int, int, int, int]],
         dropout: float,
         act: tuple | str | None,
         output_act: tuple | str | None,
@@ -312,12 +311,12 @@ def __init__(
         channels: Sequence[int] = (96, 96, 192),
         num_res_layers: int = 3,
         num_res_channels: Sequence[int] | int = (96, 96, 192),
-        downsample_parameters: Sequence[Tuple[int, int, int, int]] | Tuple[int, int, int, int] = (
+        downsample_parameters: Sequence[tuple[int, int, int, int]] | tuple[int, int, int, int] = (
             (2, 4, 1, 1),
             (2, 4, 1, 1),
             (2, 4, 1, 1),
         ),
-        upsample_parameters: Sequence[Tuple[int, int, int, int, int]] | Tuple[int, int, int, int, int] = (
+        upsample_parameters: Sequence[tuple[int, int, int, int, int]] | tuple[int, int, int, int, int] = (
             (2, 4, 1, 1, 0),
             (2, 4, 1, 1, 0),
             (2, 4, 1, 1, 0),
diff --git a/monai/networks/trt_compiler.py b/monai/networks/trt_compiler.py
index a360f63dbd..d29e20084c 100644
--- a/monai/networks/trt_compiler.py
+++ b/monai/networks/trt_compiler.py
@@ -18,7 +18,7 @@
 from collections import OrderedDict
 from pathlib import Path
 from types import MethodType
-from typing import Any, Dict, List, Union
+from typing import Any, Union
 
 import torch
 
@@ -499,8 +499,8 @@ def trt_forward(self, *argv, **kwargs):
 def trt_compile(
     model: torch.nn.Module,
     base_path: str,
-    args: Dict[str, Any] | None = None,
-    submodule: Union[str, List[str]] | None = None,
+    args: dict[str, Any] | None = None,
+    submodule: Union[str, list[str]] | None = None,
     logger: Any | None = None,
 ) -> torch.nn.Module:
     """
@@ -521,7 +521,7 @@ def trt_compile(
       Always returns same model passed in as argument. This is for ease of use in configs.
     """
 
-    default_args: Dict[str, Any] = {
+    default_args: dict[str, Any] = {
         "method": "onnx",
         "precision": "fp16",
         "build_args": {"builder_optimization_level": 5, "precision_constraints": "obey"},
diff --git a/monai/transforms/intensity/dictionary.py b/monai/transforms/intensity/dictionary.py
index 5dbac485fe..c5e7add79d 100644
--- a/monai/transforms/intensity/dictionary.py
+++ b/monai/transforms/intensity/dictionary.py
@@ -17,7 +17,9 @@
 
 from __future__ import annotations
 
-from typing import Callable, Hashable, Mapping, Sequence
+from typing import Callable
+
+from collections.abc import Hashable, Mapping, Sequence
 
 import numpy as np
 
diff --git a/monai/transforms/lazy/functional.py b/monai/transforms/lazy/functional.py
index 6b95027832..518c74e414 100644
--- a/monai/transforms/lazy/functional.py
+++ b/monai/transforms/lazy/functional.py
@@ -11,7 +11,9 @@
 
 from __future__ import annotations
 
-from typing import Any, Mapping, Sequence
+from typing import Any
+
+from collections.abc import Mapping, Sequence
 
 import torch
 
diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py
index 6e39fb2e19..18ea0da23b 100644
--- a/monai/transforms/spatial/array.py
+++ b/monai/transforms/spatial/array.py
@@ -18,7 +18,9 @@
 from collections.abc import Callable
 from copy import deepcopy
 from itertools import zip_longest
-from typing import Any, Optional, Sequence, Tuple, Union, cast
+from typing import Any, Optional, Union, cast
+
+from collections.abc import Sequence
 
 import numpy as np
 import torch
@@ -116,7 +118,7 @@
     "RandSimulateLowResolution",
 ]
 
-RandRange = Optional[Union[Sequence[Union[Tuple[float, float], float]], float]]
+RandRange = Optional[Union[Sequence[Union[tuple[float, float], float]], float]]
 
 
 class SpatialResample(InvertibleTransform, LazyTransform):
diff --git a/monai/transforms/utility/dictionary.py b/monai/transforms/utility/dictionary.py
index 79d0be522d..da43914aba 100644
--- a/monai/transforms/utility/dictionary.py
+++ b/monai/transforms/utility/dictionary.py
@@ -20,7 +20,9 @@
 import re
 from collections.abc import Callable, Hashable, Mapping
 from copy import deepcopy
-from typing import Any, Sequence, cast
+from typing import Any, cast
+
+from collections.abc import Sequence
 
 import numpy as np
 import torch
diff --git a/monai/transforms/utils_morphological_ops.py b/monai/transforms/utils_morphological_ops.py
index b3134c1865..61d3c5b858 100644
--- a/monai/transforms/utils_morphological_ops.py
+++ b/monai/transforms/utils_morphological_ops.py
@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 import torch.nn.functional as F
diff --git a/monai/utils/component_store.py b/monai/utils/component_store.py
index d1e71eaebf..44be6efe94 100644
--- a/monai/utils/component_store.py
+++ b/monai/utils/component_store.py
@@ -14,7 +14,9 @@
 from collections import namedtuple
 from keyword import iskeyword
 from textwrap import dedent, indent
-from typing import Any, Callable, Iterable, TypeVar
+from typing import Any, Callable, TypeVar
+
+from collections.abc import Iterable
 
 T = TypeVar("T")
 
diff --git a/monai/utils/decorators.py b/monai/utils/decorators.py
index 1c064468e8..0c3bf6ba6f 100644
--- a/monai/utils/decorators.py
+++ b/monai/utils/decorators.py
@@ -15,7 +15,9 @@
 
 __all__ = ["RestartGenerator", "MethodReplacer"]
 
-from typing import Callable, Generator
+from typing import Callable
+
+from collections.abc import Generator
 
 
 class RestartGenerator:
diff --git a/monai/utils/module.py b/monai/utils/module.py
index df5fe873ae..f2acb28119 100644
--- a/monai/utils/module.py
+++ b/monai/utils/module.py
@@ -25,7 +25,9 @@
 from pydoc import locate
 from re import match
 from types import FunctionType, ModuleType
-from typing import Any, Iterable, cast
+from typing import Any, cast
+
+from collections.abc import Iterable
 
 import torch
 
diff --git a/monai/utils/state_cacher.py b/monai/utils/state_cacher.py
index d37e7abde4..255e15a7e4 100644
--- a/monai/utils/state_cacher.py
+++ b/monai/utils/state_cacher.py
@@ -16,7 +16,9 @@
 import pickle
 import tempfile
 from types import ModuleType
-from typing import Any, Hashable
+from typing import Any
+
+from collections.abc import Hashable
 
 import torch
 from torch.serialization import DEFAULT_PROTOCOL
diff --git a/tests/test_compute_panoptic_quality.py b/tests/test_compute_panoptic_quality.py
index a916ea32b2..a915eb64f9 100644
--- a/tests/test_compute_panoptic_quality.py
+++ b/tests/test_compute_panoptic_quality.py
@@ -12,7 +12,6 @@
 from __future__ import annotations
 
 import unittest
-from typing import List
 
 import numpy as np
 import torch
@@ -104,7 +103,7 @@ def test_value_class(self, input_params, y_pred, y_gt, expected_value):
         metric = PanopticQualityMetric(**input_params)
         metric(y_pred, y_gt)
         outputs = metric.aggregate()
-        if isinstance(outputs, List):
+        if isinstance(outputs, list):
             for output, value in zip(outputs, expected_value):
                 np.testing.assert_allclose(output.cpu().numpy(), np.asarray(value), atol=1e-4)
         else:
diff --git a/tests/test_dynunet.py b/tests/test_dynunet.py
index f3c982056c..e173049a95 100644
--- a/tests/test_dynunet.py
+++ b/tests/test_dynunet.py
@@ -13,7 +13,9 @@
 
 import platform
 import unittest
-from typing import Any, Sequence
+from typing import Any
+
+from collections.abc import Sequence
 
 import torch
 from parameterized import parameterized
diff --git a/tests/test_network_consistency.py b/tests/test_network_consistency.py
index 4182501808..6949bb359f 100644
--- a/tests/test_network_consistency.py
+++ b/tests/test_network_consistency.py
@@ -15,7 +15,7 @@
 import os
 import unittest
 from glob import glob
-from typing import Sequence
+from collections.abc import Sequence
 from unittest.case import skipIf
 
 import torch