import sys

import numpy as np
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import dijkstra

input = sys.stdin.buffer.readline
read = sys.stdin.buffer.read

N, M = map(int, input().split())
uvcds = list(map(int, read().split()))

us = uvcds[0::4]
vs = uvcds[1::4]
cs = uvcds[2::4]
ds = uvcds[3::4]

uv2i = {(min(u, v), max(u, v)): i for i, (u, v) in enumerate(zip(us, vs))}

costs = cs * 2
starts = us + vs
ends = vs + us

graph = csr_matrix((costs, (starts, ends)), shape=(N + 1, N + 1))
dist_vec, predecessor = dijkstra(graph, directed=False, indices=1, return_predecessors=True)

predecessor = list(predecessor)

ans = int(np.round(dist_vec[N]))
v = N
while v != 1:
    p = predecessor[v]
    if p > v:
        p, v = v, p
    i = uv2i[(p, v)]
    costs[i] = costs[i + M] = ds[i]
    v = p

# graph = csr_matrix((costs, (starts, ends)), shape=(N + 1, N + 1))
ans += int(np.round(dijkstra(graph, directed=False, indices=N)[1]))

print(ans)